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Aim: To develop and evaluate a novel multi-method micro-computed tomography (μCT) imaging protocol for enhanced visualization of both hard and soft tissues in murine mandibles, addressing the limitations of traditional imaging techniques in dental research., Materials and Methods: We employed a contrast-enhanced (CE) μCT imaging technique using Lugol's iodine as a contrast agent to visualize the intricate structures of murine mandibles. The protocol involved the combination of conventional μCT imaging as well as CE-μCT, including decalcification with EDTA, allowing for simultaneous assessment of hard and soft tissues. The method is compared with standard imaging modalities, and the ability to visualize detailed anatomical features is discussed., Results: The CE-μCT imaging technique provided superior visualization of murine mandibular structures, including dental pulp, periodontal ligaments and the surrounding soft tissues, along with conventional μCT imaging of alveolar bone and teeth. This method revealed detailed anatomical features with high specificity and contrast, surpassing traditional imaging approaches., Conclusion: Our findings demonstrate the potential of CE-μCT imaging with Lugol's iodine as a powerful tool for dental research. This technique offers a comprehensive view of the murine mandible, facilitating advanced studies in tissue engineering, dental pathology and the development of dental materials., (© 2024 The Author(s). Journal of Clinical Periodontology published by John Wiley & Sons Ltd.)

This paper presents an in-pixel contrast enhancement circuit that performs image processing directly within the pixel circuit. The circuit leverages HyperFET, a hybrid device combining a MOSFET and a phase transition material (PTM), to enhance performance. It can be tuned for different modes of operation. In foreground enhancement mode, it suppresses low-intensity background pixels to nearly zero, isolating the foreground for better object visibility. In contrast enhancement mode, it improves overall image contrast. The contrast enhancement function is customizable both during the design phase and in real-time, allowing the circuit to adapt to specific applications and varying lighting conditions. A model of the designed pixel circuit is developed and applied to a full pixel array, demonstrating significant improvements in image quality. Simulations performed in HSPICE show a nearly 6x increase in Michelson Contrast Ratio (CR) in the foreground enhancement mode. Furthermore, process variation and Signal-to-Noise Ratio (SNR) analysis has been conducted to evaluate the robustness of the design under manufacturing variations. The simulation results indicate its potential for real-time, adaptive contrast enhancement across various imaging environments., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Purpose: To investigate the prognostic significance of contrast enhancement (CE) in grade 2 oligodendroglioma (ODG) and explore its clinical implications., Methods: Patients diagnosed with isocitrate dehydrogenase (IDH)-mutant, 1p/19q co-deleted ODG between 2009 and 2016 were retrospectively enrolled from a single institution. The presence of CE was identified on preoperative MRIs, and clinical, radiologic, and histopathological data that was extracted. Subgroup analyses were performed to evaluate differences in these factors and prognoses. Cox proportional hazards regression analyses were used to identify prognostic factors., Results: 258 patients with pathologically confirmed WHO grade 2 ODGs were included. The entire cohort was divided into the CE group (n = 133, 51.6%) and the non-CE group (n = 125, 48.4%). Patients with CE on preoperative MRI showed significantly worse progression-free survival (PFS) compared to those without CE (median PFS: 133 months vs. not reached; p < 0.001) and overall survival (OS) (mean OS: 151 months vs. 155 months; median OS: not reached; p = 0.021). Furthermore, CE presence was identified as an independent prognostic factor in the Cox multivariate analysis. Patients within the CE cohort were further categorized into strong and weak CE subgroups based on the pattern of CE. Logistic regression analysis revealed that non-frontal lobe location (OR = 3.287, p = 0.042), higher Ki-67 index (OR = 3.782, p = 0.027), and 1q/19p co-polysomy (OR = 9.658, p = 0.001) were significantly associated with a higher incidence of the strong CE in ODGs. Furthermore, ODG patients in the strong CE subgroup demonstrated the poorest survival outcomes., Conclusion: CE on preoperative MRI is a valuable prognostic marker in the grade 2 ODGs, with strong CE indicating the poorest survival outcomes. Further validation through larger cohort studies will help confirm these findings and refine survival stratification in clinical practice., Competing Interests: Declarations. Competing interests: The authors declare no competing interests. Ethics approval: This study was performed in line with the principles of the Declaration of Helsinki. Ethical approval for this study was waived by the Review Board of Beijing Tiantan Hospital due to the observational retrospective nature of this study. Consent to participate: Written informed consent was obtained from all participants and their families included in the study. Consent to publish: The authors affirm that human research participants provided informed consent for the publication of the images in all Figures., (© 2025. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective: To perform a systematic review and meta-analysis of the diagnostic performance of contrast enhancement to differentiate benign and malignant renal lesions using CT and MRI., Material and Methods: A systematic literature search of databases was performed between January 1, 1980 and September 26, 2022. We included studies reporting the accuracy of CE thresholds on CT and MRI indeterminate renal lesions, with pathologic examination and follow-up as the reference standard. Studies meeting the inclusion criteria underwent quality assessment with the Cochrane recommendation for diagnostic accuracy study Quality Assessment 2. We excluded studies with high risk of bias. Summary estimates of diagnostic performance were obtained with the bivariate Bayesian model for CT and MRI. Effects of different thresholds and index test modalities were investigated through subgroup analysis., Results: Eleven studies (1372 patients) using CT and six studies (218 patients) using MRI were included. Of the eleven studies, 15 parts from 9 studies were considered for the CT meta-analysis, and 6 parts from 3 studies for the MRI meta-analysis. Diagnostic performance meta-analysis on enhancement found a 96% summary sensitivity (95% CI 92, 98) and a 92% summary specificity (95% CI 85, 96) in 2056 renal lesions for CT; and 82% summary sensitivity (95% CI 65, 89) and an 89% summary specificity (95% CI 77, 95) in 634 lesions for MRI., Conclusion: CT and MRI have high accuracy to determine enhancement and classify renal lesions, and both modalities can be used with confidence for this purpose. There are still some controversies about the optimal thresholds. Future research should evaluate outcomes and decision-making pathways to determine whether basing clinical decisions on a specific threshold on CT and MRI would do more harm than good., Competing Interests: Declarations. Competing Interests: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Rationale and Objectives: To determine the role of dynamic contrast-enhanced (DCE) MRI-radiomics in predicting the International Society of Urological Pathology Grade Group (ISUP-GG) in therapy-naïve prostate cancer (PCa) patients., Materials and Methods: In this ethics review board-approved retrospective study on two prospective clinical trials between 2017 and 2020, 73 men with suspected/confirmed PCa were included. All participants underwent multiparametric MRI. On MRI, dominant lesions (per PI-RADS) were identified. DCE-MRI radiomic features were extracted from the segmented volumes following the image biomarker standardisation initiative (IBSI) guidelines through 14 time points. Histopathology evaluation on the cognitive-fusion targeted biopsies was set as the reference standard. Univariate regression was done to evaluate potential predictors across all calculated features. Random forest imputation was used for multivariate modelling., Results: 73 index lesions were reviewed. Histopathology revealed 28, 16, 13 and 16 lesions with ISUP-GG-Negative/1/2, ISUP-GG-3, ISUP-GG-4 and ISUP-GG-5, respectively. From the extracted features, total lesion enhancement (TLE), minimum enhancement intensity and Grey-Level Run Length Matrix (GLRLM) were the most significantly different parameters among ISUP-GGs (Neg/1/2 vs 3/4 vs 5). 16 features with significant cross-sectional associations with ISUP-GGs entered the multivariate analysis. The final DCE partitioning model used only four features (lesion sphericity, TLE, GLRLM and Grey-Level Zone Length Matrix). For the binarized diagnosis (ISUP-GG≤2 vs ISUP-GG>2), the accuracy reached 81%., Conclusion: DCE-MRI radiomics might be used as a non-invasive tool for aiding pathological grade group prediction in therapy-naïve PCa patients, potentially adding complementary information to PI-RADS for supporting tailored diagnostic pathways and treatment planning., Competing Interests: Declaration of Competing Interest Patrick Veit-Haibach—IIS grants: Bayer Switzerland, Roche Pharmaceuticals, Siemens Healthineers, GE Healthcare, Point Biopharma; Speaker fees and travel support: Siemens Healthineers, GE Healthcare; Speaker fees: Ontario Association of Radiologists; Speaker fees: JCA PET/CT course; Springer Nature: Editor fee; Reviewer compensation: Wellcome Trust; German Cancer Center: Strategic panel advisory compensation and travel support. Alejandro Berlin—Participation on a Data Safety Monitoring Board or Advisory Board from Princess Margaret Cancer Center, University Health Network. Ur Metser—Consulting fees from POINT Biopharm; Chair, Ontario PET Steering Committee and Ontario Health-Cancer Care Ontario; The remaining authors of this manuscript declare no relationships with any companies, whose products or services may be related to the subject matter of the article., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

Background: Diabetic Retinopathy (DR) is a leading cause of blindness among individuals aged 18 to 65 with diabetes, affecting 35-60% of this population, according to the International Diabetes Federation. Early diagnosis is critical for preventing vision loss, yet processing raw fundus images using machine learning faces significant challenges, particularly in accurately identifying microaneurysm lesions, which are crucial for diagnosis., Methods: This study proposes a novel pre-processing technique utilizing the Modified Fuzzy C-means Clustering approach combined with a Support Vector Machine classifier. The method includes converting RGB images to HSI colour space, applying median filtering to reduce noise, enhancing contrast through Intensity Histogram Equalization, and identifying false microaneurysm candidates using connected components. Additionally, morphological operations are performed to remove the optic disc from the enhanced images due to its similarity to microaneurysms., Results: The proposed method was evaluated using publicly available datasets, demonstrating superior performance compared to existing state-of-the-art algorithms. The approach achieved an accuracy rate of 99.31%, significantly improving the detection of microaneurysms and reducing false detections., Conclusions: The findings indicate that the proposed pre-processing technique effectively enhances diabetic retinopathy classification by addressing the challenges of false microaneurysm detection. The comparative analysis against state-of-the-art algorithms highlights the effectiveness of the proposed method, particularly in addressing the challenges associated with false microaneurysms., Competing Interests: Declarations. Conflict of interest: The authors declare no competing interests. Ethical approval and informed consent: The study does not involve the participation of human subjects. Therefore, the need for traditional informed consent is not applicable. Patient consent: The study does not involve the participation of human subjects. Therefore, the need for patient consent is not applicable., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

Alzheimer's disease (AD) refers to a neurological disorder that causes damage to brain cells and results in decreasing cognitive abilities and memory. In brain scans, this degeneration can be seen in different ways. The disease can be classified into four stages: Non-demented (ND), moderate demented (MoD), mild demented (MiD), and very mild demented (VMD). To prepare the raw dataset for analysis, the collected magnetic resonance imaging (MRI) images are subjected to several pre-processing techniques in order to improve the performance accuracy of the proposed model. Medical images generally have poor contrast and get affected by noise, which ends up with inaccurate diagnosis. For the different phases of AD to be detected, a clear image is necessary. To address this issue, the influence of the artefacts must be reduced, enhance the contrast, and reduce the loss of information. A novel framework for image enhancement is suggested to increase the accuracy in the detection and identification of AD. In this study, the raw MRI dataset from the Alzheimer's disease neuroimaging initiative (ADNI) database is subjected to skull stripping, contrast enhancement, and image filtering followed by data augmentation to balance the dataset with four types of Alzheimer's classes. The pre-processed data are subjected to five different pre-trained models such as AlexNet, ResNet, VGG 16, EfficientNet, and Inceptionv3 achieving a testing accuracy rate of 91.2%, 88.21%, 92.34%, 93.45%, and 85.12%, respectively. These pre-trained models are compared with the proposed CNN (convolutional neural network) model designed with Adam optimizer and Flatten Swish activation function which reaches the highest accuracy of 96.5% with a learning rate of 0.000001. The five pre-trained CNN models along with the proposed swish-based AD-CNN were tested using various performance metrics to evaluate the model efficiency in classifying and identifying the AD classes. From the result analysis, it is evident that the proposed AD-CNN model outperforms all the other models., Competing Interests: Declarations Conflict of interest The authors declare no competing interests., (© 2024. International Federation for Medical and Biological Engineering.)

This study investigates osteoblastic cell spheroid cultivation methods, exploring flat-bottom, U-bottom, and rotary flask techniques with and without amorphous calcium phosphate (ACP) supplementation to replicate the 3D bone tissue microenvironment. ACP particles derived from eggshell waste exhibit enhanced osteogenic activity in 3D models. However, representative imaging of intricate 3D tissue-engineered constructs poses challenges in conventional imaging techniques due to notable scattering and absorption effects in light microscopy, and hence limited penetration depth. We investigated contrast-enhanced micro-CT as a methodological approach for comprehensive morphological 3D-analysis of the in-vitro model and compared the technique with confocal laser scanning microscopy, scanning electron microscopy and classical histology. Phosphotungstic acid and iodine-based contrast agents were employed for micro-CT imaging in laboratory and synchrotron micro-CT imaging. Results revealed spheroid shape variations and structural integrity influenced by cultivation methods and ACP particles. The study underscores the advantage of 3D spheroid models over traditional 2D cultures in mimicking bone tissue architecture and cellular interactions, emphasising the growing demand for novel imaging techniques to visualise 3D tissue-engineered models. Contrast-enhanced micro-CT emerges as a promising non-invasive imaging method for tissue-engineered constructs containing ACP particles, offering insights into sample morphology, enabling virtual histology before further analysis., (Creative Commons Attribution license.)

Purpose: Contrast enhancement (CE) after mechanical thrombectomy (MT) remains a subject of investigation, with a reported prevalence ranging from 31 to 88%. We examined our patients to identify predictors of CE and its impact on outcomes, an aspect that remains understudied., Methods: We retrospectively analyzed 106 patients who underwent MT at our hospital between 2018 and 2022. The inclusion criteria involved patients who underwent two head CT scans: one immediately after the procedure and a repeat scan within 24 h. This study compared demographic, clinical, laboratory, neuroimaging, and procedure-related variables between patients with CE and those without hyperdensity. Regression analysis was employed to determine the associations between CEs and significant variables., Results: Among the analyzed patients, 32.1% had CE. Hyperlipidemia was more prevalent in the CE group. CE correlated with an increase in the National Institutes of Health Stroke Scale (NIHSS) score ≥ 4 within 24 h, intracerebral hemorrhage (ICH) incidence, elevated NIHSS score, and a decreased rate of modified Rankin scale (mRS) 0-3 upon discharge. The adjusted model demonstrated a significant association between CE and the incidence of hyperlipidemia and ICH, with an increase in NIHSS score ≥ 4 within 24 h of ICH and a lower mRS score of 0-3 upon discharge., Conclusions: CE is associated with hyperlipidemia, ICH, early neurological deterioration, and poor functional outcomes upon discharge. However, no similar association was shown for long-term outcomes. Further studies are required to clarify the pathophysiology of CE and its implications for optimizing stroke care., (© 2024. The Author(s) under exclusive licence to Belgian Neurological Society.)

Background: In POLA cohort, three pathological groups of CNS WHO grade 3 oligodendroglioma IDH-mutant and 1p/19q co-deleted have been described: group 1 (high mitotic count only), group 2 (microvascular proliferation MVP and no necrosis), and group 3 (MVP and necrosis)., Methods: 494 patients from the POLA cohort, with a median follow up of 96 months were included. To identify the impact of the pathological groups and contrast enhancement in group 1 on overall survival (OS) or progression free survival (PFS), survival curves were obtained (Kaplan-Meier method) and compared (log-rank test). Prognostic value of clinical factors and CDKN2A homozygous deletion HD were also tested. Multivariate analysis was performed., Results: Survival analysis demonstrated that the pathological groups were associated with both progression-free survival (PFS P=0.01) and overall survival (OS P=0.001). In group 1, patients with contrast enhancement (1CE+) had a poorer prognosis compared to those without (OS P=0.028, PFS P=0.006). Further stratification into group 1CE-, group 1CE+, group 2, and group 3 provided clearer prognostic distinctions (OS P=0.002, PFS P<0.0001). Other prognostic factors included age (OS P<0.0001, PFS P=0.002), extent of surgical resection (OS P=0.001, PFS P=0.003), KPS (OS P<0.0001, PFS P=0.002), postoperative treatment (OS P=0.007, PFS P<0.0001), and CDKN2A HD (OS and PFS P<0.0001). The pathological groups remained of prognostic significance for PFS in multivariate analysis., Conclusion: Necrosis and CDKN2A HD are adverse prognostic factors of WHO grade 3 oligodendrogliomas, IDH mutant and 1p/19q co-deleted. Besides, in group 1 patients, lack of contrast enhancement is a factor of better prognosis., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site—for further information please contact journals.permissions@oup.com.)

Introduction: Local disease recurrence following focal therapy (FT) for prostate cancer may be due to failure to eradicate focal disease or development of disease in the untreated prostate (in- and out-of-field recurrences). Several studies suggest in-field contrast enhancement (CE) on post-treatment multi-parametric (mp) MRI between 6-12 months following FT indicates residual disease. The present study assesses the incidence and oncologic implications of early CE observed following primary partial gland cryoablation (PPGCA)., Material and Methods: The surveillance protocol for men enrolled in our prospective outcomes study following PPGCA included mpMRI at 6-12 months, 2 years, 3.5 years, and 5 years. All cases of in-field early CE were re-reviewed retrospectively and graded using the previously described Prostate Imaging after Focal Ablation scoring system. All patients exhibiting early CE were re-evaluated by a single radiologist at 2-year mpMRI Results: A total of 320 men enrolled in our PPGCA outcomes study had at least 6 months of follow up. Three hundred fifteen (98%) of these men had undergone post-PPGCA mpMRI at 6-12 months. Of these men, 9 were found to have early in-field CE and 8 underwent repeat MRI at 2 years. In all 8 cases, the CE resolved on the 2-year mpMRI. Of these 8 patients, seven underwent repeat protocol biopsy at 2 years and in-field significant disease was detected in only 1 case., Conclusions: The most compelling evidence that early CE is not indicative of prostate cancer recurrence is that all lesions resolved within 24 months. While incidence of early CE is low, its consistent resolution calls into question the clinical significance of this finding after PPGCA.

Mammography imaging remains the gold standard for breast cancer detection and diagnosis, but challenges in image quality can lead to misdiagnosis, increased radiation exposure, and higher healthcare costs. This comprehensive review evaluates traditional and machine learning-based techniques for improving mammography image quality, aiming to benefit clinicians and enhance diagnostic accuracy. Our literature search, spanning 2015 - 2024, identified 115 articles focusing on contrast enhancement and noise reduction methods, including histogram equalization, filtering, unsharp masking, fuzzy logic, transform-based techniques, and advanced machine learning approaches. Machine learning, particularly architectures integrating denoising autoencoders with convolutional neural networks, emerged as highly effective in enhancing image quality without compromising detail. The discussion highlights the success of these techniques in improving mammography images' visual quality. However, challenges such as high noise ratios, inconsistent evaluation metrics, and limited open-source datasets persist. Addressing these issues offers opportunities for future research to further advance mammography image enhancement methodologies., (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.)

Aim: To evaluate the possibilities of post-processing of multidetector computed tomography (CT) results in the non-invasive diagnosis of pancreatic fibrosis (PF)., Materials and Methods: The study included 165 patients aged 57.91±13.5 years who underwent preoperative CT during surgical treatment for chronic pancreatitis and pancreatic cancer from April 2022 to February 2024. The normalized contrast ratios of pancreatic tissue in the pancreatic (NCPP) and venous (NCVP) phases, as well as the contrast ratio (CR) were measured. Pathomorphological assessment of PF performed in tissues outside neoplasm or desmoplastic reaction by the Kloppel and Maillet scale., Results: The values of post-processing CT results were compared in groups with different degrees of PF. Mean CR values were significantly higher ( p= 0.001) in patients with severe PF (CR 1.16±0.65 HU) than in patients with mild PF (CR 0.78±0.31 HU). CR value significant increase ( p= 0.03) was found in patients with signs of inflammatory changes in the pancreas tissue (CR 1.14±0.6 HU) than in those without them (CR 0.81±0.3 HU). There were no significant differences between the values of NCPP and NCVP, and the degree of PF., Conclusion: The CR value increased in patients with severe degree of PF. There was a relationship between CR value increase and the radiological density of pancreatic tissue in non-contrast phase and presence of early signs of pancreatic inflammatory changes. Thus, there was a relationship between CT postprocessing results and morphological signs of PF, which can be used for pancreatic fibrosis non-invasive diagnosis and identification of additional signs of early chronic pancreatitis.

Background: The best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined., Purpose: To determine the optimal settings of the DLIR algorithm for abdominal low-keV VMI., Material and Methods: The portal-venous phase computed tomography (CT) scans of 109 participants with 152 lesions were reconstructed into four image series: VMI at 50 keV using adaptive statistical iterative reconstruction (Asir-V) at 50% blending (AV-50); and VMI at 40 keV using AV-50 and DLIR at medium (DLIR-M) and high strength (DLIR-H). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of nine anatomical sites were calculated. Noise power spectrum (NPS) using homogenous region of liver, and edge rise slope (ERS) at five edges were measured. Five radiologists rated image quality and diagnostic acceptability, and evaluated the lesion conspicuity., Results: The SNR and CNR values, and noise and noise peak in NPS measurements, were significantly lower in DLIR images than AV-50 images in all anatomical sites (all P  < 0.001). The ERS values were significantly higher in 40-keV images than 50-keV images at all edges (all P  < 0.001). The differences of the peak and average spatial frequency among the four reconstruction algorithms were significant but relatively small. The 40-keV images were rated higher with DLIR-M than DLIR-H for diagnostic acceptance ( P  < 0.001) and lesion conspicuity ( P  = 0.010)., Conclusion: DLIR provides lower noise, higher sharpness, and more natural texture to allow 40 keV to be a new standard for routine VMI reconstruction for the abdomen and DLIR-M gains higher diagnostic acceptance and lesion conspicuity rating than DLIR-H., Competing Interests: Declaration of conflicting interestsThe authors disclosed receipt of the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: WL and JL are employees of GE Healthcare. However, they neither had access to nor control over the data acquisition and analysis. Authors who are not GE Healthcare employees had total control of the data and analysis used in the study. JZ acknowledges his position as a member of the Scientific Editorial Board Member of European Radiology and BMC Medical Imaging. All other authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

Background: Adequate image enhancement of organs and blood vessels of interest is an important aspect of image quality in contrast-enhanced computed tomography (CT). There is a need for an objective method for evaluation of vessel contrast that can be automatically and systematically applied to large sets of CT exams., Purpose: The purpose of this work was to develop a method to automatically segment and measure attenuation Hounsfield Unit (HU) in the portal vein (PV) in contrast-enhanced abdomen CT examinations., Methods: Input CT images were processed by a vessel enhancing filter to determine candidate PV segmentations. Multiple machine learning (ML) classifiers were evaluated for classifying a segmentation as corresponding to the PV based on segmentation shape, location, and intensity features. A public data set of 82 contrast-enhanced abdomen CT examinations was used to train the method. An optimal ML classifier was selected by training and tuning on 66 out of the 82 exams (80% training split) in the public data set. The method was evaluated in terms of segmentation classification accuracy and PV attenuation measurement accuracy, compared to manually determined ground truth, on a test set of the remaining 16 exams (20% test split) held out from public data set. The method was further evaluated on a separate, independently collected test set of 21 examinations., Results: The best classifier was found to be a random forest, with a precision of 0.892 in the held-out test set to correctly identify the PV from among the input candidate segmentations. The mean absolute error of the measured PV attenuation relative to ground truth manual measurement was 13.4 HU. On the independent test set, the overall precision decreased to 0.684. However, the PV attenuation measurement remained relatively accurate with a mean absolute error of 15.2 HU., Conclusions: The method was shown to accurately measure PV attenuation over a large range of attenuation values, and was validated in an independently collected dataset. The method did not require time-consuming manual contouring to supervise training. The method may be applied to systematic quality control of contrast-enhanced CT examinations., (© 2024 American Association of Physicists in Medicine.)

Background and Objectives: Contrast enhancement in glioblastoma, IDH-wildtype is common but not systematic. In the era of the WHO 2021 Classification of CNS Tumors, the prognostic impact of a contrast enhancement and the pattern of contrast enhancement is not clearly elucidated., Methods: We performed an observational, retrospective, single-centre cohort study at a tertiary neurosurgical oncology centre (January 2006 - December 2022). We screened adult patients with a newly-diagnosed glioblastoma, IDH-wildtype in order to assess the prognosis role of the contrast enhancement and the pattern of contrast enhancement., Results: We included 1149 glioblastomas, IDH-wildtype: 26 (2.3%) had a no contrast enhancement, 45 (4.0%) had a faint and patchy contrast enhancement, 118 (10.5%) had a nodular contrast enhancement, and 960 (85.5%) had a ring-like contrast enhancement. Overall survival was longer in non-contrast enhanced glioblastomas (26.7 months) than in contrast enhanced glioblastomas (10.9 months) (p < 0.001). In contrast enhanced glioblastomas, a ring-like pattern was associated with shorter overall survival than in faint and patchy and nodular patterns (10.0 months versus 13.0 months, respectively) (p = 0.033). Whatever the presence of a contrast enhancement and the pattern of contrast enhancement, surgical resection was an independent predictor of longer overall survival, while age ≥ 70 years, preoperative KPS score < 70, tumour volume ≥ 30cm 3 , and postoperative residual contrast enhancement were independent predictors of shorter overall survival., Conclusion: A contrast enhancement is present in the majority (97.7%) of glioblastomas, IDH-wildtype and, regardless of the pattern, is associated with a shorter overall survival. The ring-like pattern of contrast enhancement is typical in glioblastomas, IDH-wildtype (85.5%) and remains an independent predictor of shorter overall survival compared to other patterns (faint and patchy and nodular)., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: The widely used magnetization-prepared rapid gradient-echo (MPRAGE) sequence makes enhancing lesions and blood vessels appear bright after gadolinium administration. However, dark blood imaging using T1-weighted Sampling Perfection with Application optimized Contrast using different flip angle Evolution (T1 SPACE) can be advantageous since it improves the conspicuity of small metastases and leptomeningeal disease. As a potential alternative to T1 SPACE, we evaluated a new dark blood sequence called echo-uT 1 RESS (unbalanced T1 Relaxation-Enhanced Steady-State)., Purpose: We compared the performance of echo-uT 1 RESS with Dixon fid-uT 1 RESS, MPRAGE, and T1 SPACE., Study Type: Retrospective, IRB approved., Subjects/phantom: Phantom to assess flow properties of echo-uT 1 RESS. Twenty-one patients (14 female, age range 35-82 years) with primary and secondary brain tumors., Field Strength/sequences: 3 Tesla/MPRAGE, T1 SPACE, Dixon fid-uT 1 RESS, echo-uT 1 RESS., Assessment: Flow phantom signal vs. velocity as a function of flip angle and sequence. Qualitative image assessment on 4-point scale. Quantitative evaluation of tumor-to-brain contrast, apparent contrast-to-noise ratio (aCNR), and vessel-to-brain aCNR., Statistical Tests: Friedman and Mann-Whitney U tests. A P value <0.05 was considered statistically significant., Results: In the phantom, echo-uT 1 RESS showed greater flow-dependent signal loss than fid-uT 1 RESS. In patients, blood vessels appeared bright with MPRAGE, gray with fid-uT 1 RESS, and dark with T1 SPACE and echo-uT 1 RESS. For MPRAGE, Dixon fid-uT 1 RESS, echo-uT 1 RESS, and T1 SPACE, respective tumor-to-brain contrast values were 0.6 ± 0.3, 1.3 ± 0.5, 1.0 ± 0.4, and 0.6 ± 0.4, while normalized aCNR values were 68.9 ± 50.9, 128.4 ± 59.2, 74.2 ± 42.1, and 99.4 ± 73.9., Data Conclusion: Volumetric dark blood contrast-enhanced brain MRI is feasible using echo-uT 1 RESS. The dark blood effect was improved vs. fid-uT 1 RESS, while both uT 1 RESS versions provided better tumor-to-brain contrast than MPRAGE. Whereas T1 SPACE provided better tumor aSNR, echo-uT 1 RESS provided better Weber contrast, lesion sharpness and a more consistent dark blood effect., Evidence Level: 3 TECHNICAL EFFICACY: Stage 1., (© 2023 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Introduction: The implications of shorter scan time and lower tube voltage in the dual-source CT coronary angiography (CTCA) scan protocol necessitate the adaptation of contrast media (CM) injection parameters. This audit evaluates the coronary arteries' vascular attenuation and image quality by comparing the personalised patient protocol technology (P3T) contrast injection software with standard injection protocol. The secondary aim is to determine the relationship between CM volume and the patient's weight., Methodology: A Siemens Somatom Definition Force CT Unit was used to scan 30 sets of patients between August 2020 and October 2020. Patients were selected retrospectively and separated into Standard Injection and P3T injection protocols. An experienced radiologist blinded to the groups reviewed the coronary vessels' contrast enhancement and image quality., Results: Overall, the mean HU of all the main coronary artery vessels obtained from P3T injection software reached above 350 HU and was diagnostically sufficient. The mean attenuation at the proximal region of RCA in the 80-99 kg weight category was significantly higher in the P3T injection software than the standard injection protocol (p < 0.001). The CM volume proposed by P3T injection software for 40-59 kg was approximately 57 ± 5 mls, while 75 ml was used for the standard injection protocol., Conclusion: P3T injection software in CTCA resulted in an adequate diagnostic attenuation of coronary arteries (>350HU) in all weight groups, most effectively in the higher weight group, while maintaining diagnostic image quality. Further, the P3T software reduces CM volumes in lower-weight patients., Implications: P3T software enables reducing CM volume in lower-weight patients while improving vascular enhancement in CTCA scans in higher-weight patients., Competing Interests: Conflict of interest statement The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.)

Background and Purpose: We aimed to test whether synthetic T1-weighted imaging derived from a post-contrast Quantitative Transient-state Imaging (QTI) acquisition enabled revealing pathological contrast enhancement in intracranial lesions., Methods: The analysis included 141 patients who underwent a 3 Tesla-MRI brain exam with intravenous contrast media administration, with the post-contrast acquisition protocol comprising a three-dimensional fast spoiled gradient echo (FSPGR) sequence and a QTI acquisition. Synthetic T1-weighted images were generated from QTI-derived quantitative maps of relaxation times and proton density. Two neuroradiologists assessed synthetic and conventional post-contrast T1-weighted images for the presence and pattern of pathological contrast enhancement in intracranial lesions. Enhancement volumes were quantitatively compared., Results: Using conventional imaging as a reference, synthetic T1-weighted imaging was 93% sensitive in revealing the presence of contrast enhancing lesions. The agreement for the presence/absence of contrast enhancement was almost perfect both between readers (k = 1 for both conventional and synthetic imaging) and between sequences (k = 0.98 for both readers). In 91% of lesions, synthetic T1-weighted imaging showed the same pattern of contrast enhancement visible in conventional imaging. Differences in enhancement pattern in the remaining lesions can be due to the lower spatial resolution and the longer acquisition delay from contrast media administration of QTI compared to FSPGR. Overall, enhancement volumes appeared larger in synthetic imaging., Conclusions: QTI-derived post-contrast synthetic T1-weighted imaging captures pathological contrast enhancement in most intracranial enhancing lesions. Further comparative studies employing quantitative imaging with higher spatial resolution is needed to support our data and explore possible future applications in clinical trials., (© 2024 The Authors. Journal of Neuroimaging published by Wiley Periodicals LLC on behalf of American Society of Neuroimaging.)

Background: Low-iodine-dose computed tomography (CT) protocols have emerged to mitigate the risks associated with contrast injection, often resulting in decreased image quality., Objective: To evaluate the image quality of low-iodine-dose CT combined with an artificial intelligence (AI)-based contrast-boosting technique in abdominal CT, compared to a standard-iodine-dose protocol in children., Materials and Methods: This single-center retrospective study included 35 pediatric patients (mean age 9.2 years, range 1-17 years) who underwent sequential abdominal CT scans-one with a standard-iodine-dose protocol (standard-dose group, Iobitridol 350 mgI/mL) and another with a low-iodine-dose protocol (low-dose group, Iohexol 240 mgI/mL)-within a 4-month interval from January 2022 to July 2022. The low-iodine CT protocol was reconstructed using an AI-based contrast-boosting technique (contrast-boosted group). Quantitative and qualitative parameters were measured in the three groups. For qualitative parameters, interobserver agreement was assessed using the intraclass correlation coefficient, and mean values were employed for subsequent analyses. For quantitative analysis of the three groups, repeated measures one-way analysis of variance with post hoc pairwise analysis was used. For qualitative analysis, the Friedman test followed by post hoc pairwise analysis was used. Paired t-tests were employed to compare radiation dose and iodine uptake between the standard- and low-dose groups., Results: The standard-dose group exhibited higher attenuation, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) of organs and vessels compared to the low-dose group (all P-values < 0.05 except for liver SNR, P = 0.12). However, noise levels did not differ between the standard- and low-dose groups (P = 0.86). The contrast-boosted group had increased attenuation, CNR, and SNR of organs and vessels, and reduced noise compared with the low-dose group (all P < 0.05). The contrast-boosted group showed no differences in attenuation, CNR, and SNR of organs and vessels (all P > 0.05), and lower noise (P = 0.002), than the standard-dose group. In qualitative analysis, the contrast-boosted group did not differ regarding vessel enhancement and lesion conspicuity (P > 0.05) but had lower noise (P < 0.05) and higher organ enhancement and artifacts (all P < 0.05) than the standard-dose group. While iodine uptake was significantly reduced in low-iodine-dose CT (P < 0.001), there was no difference in radiation dose between standard- and low-iodine-dose CT (all P > 0.05)., Conclusion: Low-iodine-dose abdominal CT, combined with an AI-based contrast-boosting technique exhibited comparable organ and vessel enhancement, as well as lesion conspicuity compared to standard-iodine-dose CT in children. Moreover, image noise decreased in the contrast-boosted group, albeit with an increase in artifacts., (© 2024. The Author(s).)

The aim of this study was to assess the usefulness of postmortem contrast-enhanced CT (PMeCT) performed via direct large-vessel puncture when routine postmortem CT suggests a vascular lesion as the cause of death. PMeCT was performed in 9 cases (4 male, 5 female) with a mean age of 76 years (range 52-92) at the time of death. The mean time elapsed since death was 29.1 h (12.0-72.0). The location of the target vessel for puncture was determined based on the CT table position and a grid placed on the body surface. An 18-G spinal needle was advanced to the puncture site, and the needle tip was confirmed to have reached the intended blood vessel. Using negative pressure with a 20-ml syringe, the needle tip was advanced until reverse bleeding was confirmed. Diluted contrast medium was injected slowly to ensure its dispersion within the blood vessels. Following confirmation of no extravasation, additional doses of diluted contrast agent were injected in 3-4 divided doses, with CT scans obtained at each step to track the distribution of contrast agent over time. PMeCT was successful in all cases, revealing cardiac tamponade in 7 (ascending aortic dissection, n = 6; cardiac rupture, n = 1), thoracic aortic aneurysm rupture, n = 1, and iliac artery aneurysm rupture, n = 1. There were no cases of procedure-related extravasation (pseudo-lesions). When postmortem CT reveals pericardial hematoma or bleeding in the thoracic or abdominal cavity, PMeCT can identify the source of bleeding., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

In the autonomous driving industry, there is a growing trend to employ long-wave infrared (LWIR)-based uncooled thermal-imaging cameras, capable of robustly collecting data even in extreme environments. Consequently, both industry and academia are actively researching contrast-enhancement techniques to improve the quality of LWIR-based thermal-imaging cameras. However, most research results only showcase experimental outcomes using mass-produced products that already incorporate contrast-enhancement techniques. Put differently, there is a lack of experimental data on contrast enhancement post-non-uniformity (NUC) and temperature compensation (TC) processes, which generate the images seen in the final products. To bridge this gap, we propose a histogram equalization (HE)-based contrast enhancement method that incorporates a region-based clipping technique. Furthermore, we present experimental results on the images obtained after applying NUC and TC processes. We simultaneously conducted visual and qualitative performance evaluations on images acquired after NUC and TC processes. In the visual evaluation, it was confirmed that the proposed method improves image clarity and contrast ratio compared to conventional HE-based methods, even in challenging driving scenarios such as tunnels. In the qualitative evaluation, the proposed method demonstrated upper-middle-class rankings in both image quality and processing speed metrics. Therefore, our proposed method proves to be effective for the essential contrast enhancement process in LWIR-based uncooled thermal-imaging cameras intended for autonomous driving platforms.

Introduction: Contrast Enhanced Computed Tomography (CECT) abdomen and pelvis is a common imaging procedure. Hospitals typically follow fixed protocols of contrast volume administration for triple-phase CECT abdomen and pelvis scans and have found that patients are either underdosed or overdosed with respect to their body habitus. The aim of the study was to correlate different patient characteristics such as Total body weight (TBW), Lean Body Mass (LBM), Body Mass Index (BMI), Body Surface Area (BSA) and Blood Volume (BV) with aortic enhancement in the arterial and portal venous phases for CECT Abdomen and pelvis., Methods: A total of 106 patients who underwent triple-phase CECT abdomen & pelvis were retrospectively studied. A circular region-of-interest (ROI) of 100 mm 2 was positioned on descending aorta for unenhanced, arterial, and portal venous phases to measure the aortic enhancement in Hounsfield's units. Measure of contrast attenuation (ΔH) was calculated from the difference of CT values on unenhanced images and contrast images. Correlation analysis was performed to evaluate the relation of patient body characteristics with aortic enhancement., Results: Correlation analysis revealed that BMI exhibited the least correlation when compared to the other characteristics in both arterial (r = -0.3; p = 0.002) and portovenous phases (r = -0.35; p < 0.001) whereas TBW, LBW, BSA and BV reported moderate inverse correlations. BV was found to be the strongest of all characteristics under linear regression., Conclusion: The study supports the use of protocols that adjust contrast volume to either TBW, LBW, BSA, or BV for CT abdomen and pelvis scan., Implication of Practice: The right body parameter ensures optimal contrast enhancement, improving the visualization of anatomical structures and helps in adapting tailored contrast injection protocols., Competing Interests: Conflict of interest statement None., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: Many spine disorders are caused by disc degeneration or endplate defects. Because nutrients entering the avascular disc are channeled through the cartilaginous endplate (CEP), structural and compositional changes in the CEP may block this solute channel, thereby hindering disc cell function. Therefore, imaging the CEP region is important to improve the diagnostic accuracy of spine disorders. Methods: A clinically available T1-weighted and fat-suppressed spoiled gradient recalled-echo (FS-SPGR) sequence was optimized for high-contrast CEP imaging, which utilizes the short T1 property of the CEP. The FS-SPGR scans with and without breath-hold were performed for comparison on healthy subjects. Then, the FS-SPGR sequence which produced optimal image quality was employed for patient scans. In this study, seven asymptomatic volunteers and eight patients with lower back pain were recruited and scanned on a 3T whole-body MRI scanner. Clinical T2-weighted fast spin-echo (T2w-FSE) and T1-weighted FSE (T1w-FSE) sequences were also scanned for comparison. Results: For the asymptomatic volunteers, the FS-SPGR scans under free breathing conditions with NEX = 4 showed much higher contrast-to-noise ratio values between the CEP and bone marrow fat (BMF) (CNR CEP-BMF ) (i.e., 7.8 ± 1.6) and between the CEP and nucleus pulposus (NP) (CNR CEP-NP ) (i.e., 6.1 ± 1.2) compared to free breathing with NEX = 1 (CNR CEP-BMF : 4.0 ± 1.1 and CNR CEP-NP : 2.5 ± 0.9) and breath-hold condition with NEX = 1 (CNR CEP-BMF : 4.2 ± 1.3 and CNR CEP-NP : 2.8 ± 1.3). The CEP regions showed bright linear signals with high contrast in the T1-weighted FS-SPGR images in the controls, while irregularities of the CEP were found in the patients. Discussion: We have developed a T1-weighted 3D FS-SPGR sequence to image the CEP that is readily translatable to clinical settings. The proposed sequence can be used to highlight the CEP region and shows promise for the detection of intervertebral disc abnormalities., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The authors declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision., (Copyright © 2024 Athertya, Statum, Chen, Du, Shin, Jerban, Chung, Chang and Ma.)

Minimally invasive ablation techniques for renal cancer are becoming more popular due to their low complication rate and rapid recovery period. Despite excellent visualisation, one drawback of the use of computed tomography (CT) in these procedures is the requirement for iodine-based contrast agents, which are associated with adverse reactions and require a higher x-ray dose. The purpose of this work is to examine the use of time information to generate synthetic contrast enhanced images at arbitrary points after contrast agent injection from non-contrast CT images acquired during renal cryoablation cases. To achieve this, we propose a new method of conditioning generative adversarial networks with normalised time stamps and demonstrate that the use of a HyperNetwork is feasible for this task, generating images of competitive quality compared to standard generative modelling techniques. We also show that reducing the receptive field can help tackle challenges in interventional CT data, offering significantly better image quality as well as better performance when generating images for a downstream segmentation task. Lastly, we show that all proposed models are robust enough to perform inference on unseen intra-procedural data, while also improving needle artefacts and generalising contrast enhancement to other clinically relevant regions and features., (Creative Commons Attribution license.)

Purpose: To investigate the pharmacokinetics, safety, and tolerability of the novel tetrameric high-relaxivity gadolinium-based contrast agent gadoquatrane in Japanese (Study 1) and Chinese men (Study 2)., Participants and Methods: In two similarly designed single-center, randomized, single-blind, placebo-controlled, consecutive-cohort dose-escalation studies, healthy volunteers were randomly assigned to intravenous administration of gadoquatrane (0.01-0.1 mmol gadolinium/kg body weight) or placebo. Study procedures included blood sampling and collection of urine for pharmacokinetic analyses and safety assessments., Results: Twenty-five healthy Japanese men (mean age ± standard deviation: 26±5.9 years) and 23 healthy Chinese men (31±7.6 years old) were evaluated. In both studies, the pharmacokinetic profile of gadoquatrane was characterized by rapid distribution of the drug into the extracellular space and fast renal elimination. Postdose gadolinium concentrations rapidly declined with a geometric mean effective half-life of 1.3-1.4 h. The exposure increased approximately dose-proportionally with dose. The body weight-normalized volume of distribution was constant across dose levels (0.21-0.24 L/kg). Total recovery of gadolinium in urine amounted to 82-95 % (Study 1) and 96-99 % (Study 2) of the dose administered. Only a few mild, transient adverse events were reported, none of which gave rise to any safety concerns. Exploratory drug concentration-QTc modeling indicated no risk of a clinically relevant QT/QTc prolongation at the anticipated diagnostic dose., Conclusion: Gadoquatrane was safe and well tolerated at all doses tested. The pharmacokinetic profile was essentially the same as that of other extracellular macrocyclic gadolinium-based contrast agents and was consequentially also similar for Japanese and Chinese participants., Competing Interests: Declaration of competing interest XH, KL, and SM have no conflicts of interest to declare. BMH, KM, GS, and YS are employed by Bayer AG. MR was employed by Bayer Healthcare Co. Ltd., Beijing, PR of China, when the study was conducted., (Copyright © 2024. Published by Elsevier B.V.)

Objectives: The current methods for detecting myelin changes in ischemic stroke are indirect and cannot accurately reflect their status. This study aimed to develop a novel fluorescent-magnetic resonance dual-modal molecular imaging probe for direct imaging of myelin., Methods: Compounds 7a and 7b were synthesized by linking the MeDAS group and Gadolinium (III) 1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetate. Compound 7a was selected for characterization and further study. Cell uptake, cytotoxicity, and magnetic resonance imaging scans were performed on cells. In vitro experiments on frozen brain sections from 7-day-old, 8-week-old, and ischemic stroke rats were compared with commercially available Luxol Fast Blue staining. After HPLC and MR scanning, brain tissue was soaked in 7a and scanned using T 1 WI and T 1 maps sequences., Results: Spectrophotometer results showed that compounds 7a and 7b had fluorescent properties. MR scans indicated that the compounds had contrast agent properties. Cells could uptake 7a and exhibited high signals in imaging scans. Compound 7a brain tissue staining showed more fluorescence in myelin-rich regions and identified injury sites in ischemic stroke rats. MR scanning of brain sections provided clear myelin contrast., Conclusion: A novel fluorescent-magnetic resonance dual-modal molecular imaging probe for direct imaging of myelin was successfully developed and tested in rats with ischemic stroke. These findings provide new insights for the clinical diagnosis of demyelinating diseases., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Inc.)

Background: Microarray is a sophisticated tool that concurrently analyzes the expression levels of thousands of genes, giving scientists an overview of DNA and RNA study. This procedure is divided into three stages: contact with biological samples, data extraction, and data analysis. Because expression levels are disclosed by the interplay of light with fluorescent markers, the data extraction stage relies on image processing methods. To extract quantitative information from the microarray image (MAI), four steps of preprocessing, gridding, segmentation, and intensity quantification are required. During the generation of MAIs, a large number of error-prone processes occur, leading to structural problems and reduced quality in the resulting data, affecting the identification of expressed genes., Methods: In this article, the first stage has been examined. In the preprocessing stage, the contrast of the images is first enhanced using the genetic algorithm, then the source noises that appear as small artifacts are removed using morphology, and finally, to confirm the effect of the contrast enhancement (CE) on the main stages of microarray data processing, gridding is checked on complementary deoxyribonucleic acid MAIs., Results: The comparison of the obtained results with an adaptive histogram equalization (AHE) and multi-decomposition histogram equalization (M-DHE) methods shows the superiority and efficiency of the proposed method. For example, the image contrast of the Genomic Medicine Research Center Laboratory dataset is 3.24, which is 42.91 with the proposed method and 13.48 and 32.40 with the AHE and M-DHE methods, respectively., Conclusions: The performance of the proposed methods for CE is evaluated on 3 databases and a general conclusion is obtained as to which CE method is more suitable for each dataset., Competing Interests: There are no conflicts of interest., (Copyright: © 2024 Journal of Medical Signals & Sensors.)

Although manganese (Mn) is a trace metal essential for humans, chronic exposure to Mn can cause accumulation of this metal ion in the brain leading to an increased risk of neurological and neurobehavioral health effects. This is a concern for welders exposed to Mn through welding fumes. While brain Mn accumulation in occupational settings has mostly been reported in the basal ganglia, several imaging studies also revealed elevated Mn in other brain areas. Since Mn functions as a magnetic resonance imaging (MRI) T1 contrast agent, we developed a whole-brain MRI approach to map in vivo Mn deposition differences in the brains of non-exposed factory controls and exposed welders. This is a cross-sectional analysis of 23 non-exposed factory controls and 36 exposed full-time welders from the same truck manufacturer. We collected high-resolution 3D MRIs of brain anatomy and R1 relaxation maps to identify regional differences using voxel-based quantification (VBQ) and statistical parametric mapping. Furthermore, we investigated the associations between excess Mn deposition and neuropsychological and motor test performance. Our results indicate that: (1) Using whole-brain MRI relaxometry methods we can generate excess Mn deposition maps in vivo, (2) excess Mn accumulation due to occupational exposure occurs beyond the basal ganglia in cortical areas associated with motor and cognitive functions, (3) Mn likely diffuses along white matter tracts in the brain, and (4) Mn deposition in specific brain regions is associated with exposure (cerebellum and frontal cortex) and motor metrics (cerebellum and hippocampus)., Competing Interests: Declaration of competing interest UD reports recent consulting with American Regent, Inc. The other authors do not have any financial conflicts of interest to disclose., (Copyright © 2024. Published by Elsevier Inc.)

Objectives: To evaluate the diagnostic utility of multiphase postmortem CT angiography (PMCTA) to detect plaque enhancement as a surrogate marker of inflammation, using fatal coronary plaques obtained from autopsies following sudden cardiac death., Methods: In this retrospective study, we included 35 cases (12 women, 34%; median [IQR] age, 52 [11] years), with autopsy-proven coronary thrombosis, histological examination, and multiphase PMCTA. Two radiologists blinded towards histological findings assessed PMCTA for plaque enhancement of the culprit lesion in consensus. Two forensic pathologists determined the culprit lesion and assessed histological samples in consensus. Cases with concomitant vasa vasorum density increase and intraplaque and periadventital inflammation were considered positive for plaque inflammation. Finally, we correlated radiology and pathology findings., Results: All 35 cases had histological evidence of atherosclerotic plaque disruption and thrombosis; 30 (85.7%) had plaque inflammation. Plaque enhancement at multiphase PMCTA was reported in 21 (60%) and resulted in a PPV of 95.2% (77.3-99.2%) and an NPV of 28.6% (17-43.9%). Median histological ratings indicated higher intraplaque inflammation (p = .024) and vasa vasorum density (p = .032) in plaques with enhancement. We found no evidence of a difference in adventitial inflammation between CT-negative and CT-positive plaques (p = .211)., Conclusions: Plaque enhancement was found in 2/3 of fatal atherothrombotic occlusions at coronary postmortem CT angiography. Furthermore, plaque enhancement correlated with histopathological plaque inflammation and increased vasa vasorum density. Plaque enhancement on multiphase CT angiography could potentially serve as a noninvasive marker of inflammation in high-risk populations., Clinical Relevance Statement: Phenotyping coronary plaque more comprehensively is one of the principal challenges cardiac imaging is facing. Translating our ex vivo findings of CT-based plaque inflammation assessment into clinical studies might help pave the way in defining high-risk plaque better., Key Points: • Most thrombosed coronary plaques leading to fatality in our series had histological signs of inflammation. • Multiphase postmortem CT angiography can provide a noninvasive interrogation of plaque inflammation through contrast enhancement. • Atherosclerotic plaque enhancement at multiphase postmortem CT angiography correlated with histopathological signs of plaque inflammation and could potentially serve as an imaging biological marker of plaque vulnerability., (© 2023. The Author(s).)

Background: Some patients with suspected brain metastases (BM) could not tolerate longer scanning examinations according to the standardized MRI protocol., Objective: The purpose of this study was to evaluate the clinical value of contrast-enhanced fast fluid-attenuated inversion recovery (CE FLAIR) imaging in combination with contrast-enhanced T1 weighted imaging (CE T1WI) in detecting BM of lung cancer and explore a quick and effective MRI protocol., Material and Methods: In 201 patients with lung cancers and suspected BM, T1WI and FLAIR were performed before and after administration of gadopentetate dimeglumine. Two radiologists reviewed pre- and post-contrast images to determine the presence of abnormal contrast enhancement or signal intensity and decided whether it was metastatic or not on CE T1WI (Group 1) and CE FLAIR (Group 2). The number, locations and features of abnormal findings in two groups were recorded. Receiver Operating Characteristic (ROC) analyses were conducted in three groups: Group 1, 2 and 3(combination of CE FLAIR and CE T1WI)., Results: A total of 714 abnormal findings were revealed, of which 672 were considered as BM and 42 nonmetastatic. Superficial and small metastases(≤10mm) in parenchyma and ependyma, leptomeningeal and non-expansive skull metastases were typically better seen on CE FLAIR. The areas under ROC in the three groups were 0.720,0.887 and 0.973, respectively. Group 3 was significantly better in diagnostic efficiency of BMs than Group 1 (p<0.0001) or Group 2 (p=0.0006)., Conclusion: The combination of CE T1WI and CE FLAIR promotes diagnostic performance and results in better observation and characterization of BM in patients with lung cancers. It provides a quick and efficient way of detecting BM., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

The purpose of this study was to investigate the correlation between patient characteristics and contrast enhancement during the hepatic arterial phase (HAP) and portal venous phase (PVP) CT scanning. All were examined using a hepatic dynamic CT protocol; the scanning parameters were tube voltage 120 kVp, tube current 50 to 600 mA (noise index 8.0 HU), 0.5-s rotation, 5-mm detector row width, 0.813 or 0.825 beam pitch, and the contrast material 600 mg/kg iodine. We calculated contrast enhancement (per gram of iodine: ΔHU/gI) of the abdominal aorta during the HAP and that of the hepatic parenchyma during the PVP. There was a significant difference in the contrast enhancement of the abdominal aorta during the HAP (8.6±2.7 ΔHU/gI) and (9.5±1.7 ΔHU/gI) and that of the hepatic parenchyma during the PVP (1.4±0.5 ΔHU/gI) and (2.9±0.5 ΔHU/gI) between male and female patients (p<0.05). A significant positive correlation was seen between the ΔHU/gI of aortic enhancement and age in male and female patients (r=-0.382 and 0.213) (p<0.05). A significant inverse correlation was observed between the ΔHU/gI of aortic enhancement and the height (HT; r=-0.466 and -0.251), total body weight (TBW; r=-0.609 and -0.535), body mass index (BMI; r=-0.505 and -0.465), lean body weight (LBW; r=-0.642 and -0.576), and body surface area (BSA; r=-0.644 and -0.557) (p<0.05 for all) in male and female patients. A significant positive correlation was seen between the ΔHU/gI of hepatic parenchymal enhancement and the patient age in male and female patients (r=0.258 and 0.150) (p<0.05). A significant inverse correlation was observed between the ΔHU/gI of hepatic parenchymal enhancement and the HT (r=-0.487 and -0.321), TBW (r=-0.580 and -0.525), BMI (r=-0.473 and -0.413), LBW (r=-0.615 and -0.576) (p<0.05 for all), and BSA (r=-0.617 and -0.558) in male and female patients. The BSA was significantly correlated with the ΔHU/gI of aortic and hepatic parenchymal enhancement of the hepatic dynamic CT in male patients. However, LBW was significantly correlated with the ΔHU/gI of aortic and hepatic parenchymal enhancement of the hepatic dynamic CT in female patients. Since the patient factors that affect the contrast enhancement of the abdominal aorta and hepatic parenchyma may differ from facility to facility, we should therefore consider reassessing at each facility.

Brain tumor classification is one of the most difficult tasks for clinical diagnosis and treatment in medical image analysis. Any errors that occur throughout the brain tumor diagnosis process may result in a shorter human life span. Nevertheless, most currently used techniques ignore certain features that have particular significance and relevance to the classification problem in favor of extracting and choosing deep significance features. One important area of research is the deep learning-based categorization of brain tumors using brain magnetic resonance imaging (MRI). This paper proposes an automated deep learning model and an optimal information fusion framework for classifying brain tumor from MRI images. The dataset used in this work was imbalanced, a key challenge for training selected networks. This imbalance in the training dataset impacts the performance of deep learning models because it causes the classifier performance to become biased in favor of the majority class. We designed a sparse autoencoder network to generate new images that resolve the problem of imbalance. After that, two pretrained neural networks were modified and the hyperparameters were initialized using Bayesian optimization, which was later utilized for the training process. After that, deep features were extracted from the global average pooling layer. The extracted features contain few irrelevant information; therefore, we proposed an improved Quantum Theory-based Marine Predator Optimization algorithm (QTbMPA). The proposed QTbMPA selects both networks' best features and finally fuses using a serial-based approach. The fused feature set is passed to neural network classifiers for the final classification. The proposed framework tested on an augmented Figshare dataset and an improved accuracy of 99.80%, a sensitivity rate of 99.83%, a false negative rate of 17%, and a precision rate of 99.83% is obtained. Comparison and ablation study show the improvement in the accuracy of this work., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Ullah, Khan, Masood, Mzoughi, Saidani and Alturki.)

Background: Two Bispectral contrast enhancement approaches for the fluorescence diagnosis with chlorine-e6 and a wide field-of-view imaging system with fluorescence excitation at 405 nm and time-resolved background suppression were analyzed and compared., Methods: Two techniques for the contrast enhancement of a fluorescent video system (Red/Green (R/G) ratio and Red-Green (R-G)) with time-resolved background suppression for fluorescent diagnosis (FD) were tested in four patients with basal cell carcinoma (BCC)., Results: The results of both contrast enhancement methods were compared for the diagnostic efficiency for FD of BCC. Both techniques successfully determined the boundaries of the lesions and the fluorescence intensity., Conclusions: Both contrast enhancement modes have proven effective in identifying tumor borders in cases of low contrast in BCC FD with Ce6. While the Red/Green (R/G) mode provides sharper lesion borders, the Red minus Green (R-G) mode visualizes more fluorescent features and makes it easier to assess the lesion margins., (Copyright © 2023 The Author(s). Published by Elsevier B.V. All rights reserved.)

Objective: The aims of our study were to analyze agreement among readers with different levels of expertise and diagnostic performance of individual and combined imaging signs for the diagnosis of adhesive capsulitis of the shoulder., Methods: In a retrospective study, contrast-enhanced shoulder MRIs of 60 patients with and 120 without clinically diagnosed adhesive capsulitis were evaluated by three readers independently. As non-enhanced imaging signs, readers evaluated signal intensity and thickness of the axillary recess capsule, thickness of the rotator interval capsule and the coracohumeral ligament as well as obliteration of subcoracoid fat. Furthermore, contrast enhancement of axillary recess and rotator interval capsule were evaluated. Data analysis included interreader reliability, ROC analysis, and logistic regression (p < 0.05)., Results: Contrast-enhanced parameters showed substantially higher agreement among readers (ICC 0.79-0.80) than non-enhanced parameters (0.37-0.45). AUCs of contrast-enhanced signs (95.1-96.6%) were significantly higher (p < 0.01) than of non-enhanced imaging signs (61.5-85.9%) when considered individually. Combined evaluation of axillary recess signal intensity and thicknesses of axillary recess or rotator interval-when at least one of two signs was rated positive-increased accuracy compared to individual imaging signs, however not statistically significant., Conclusion: Contrast-enhanced imaging signs show both distinctly higher agreement among readers and distinctly higher diagnostic performance compared to non-enhanced imaging signs based on the imaging protocol used in this study. Combined evaluation of parameters showed a tendency to increase discrimination; however, the effect on diagnosis of ACS was not statistically significant., (© 2023. The Author(s).)

Background: Resection of the contrast-enhancing (CE) tumor represents the standard of care in newly diagnosed glioblastoma. However, some tumors ultimately diagnosed as glioblastoma lack contrast enhancement and have a 'low-grade appearance' on imaging (non-CE glioblastoma). We aimed to (a) volumetrically define the value of non-CE tumor resection in the absence of contrast enhancement, and to (b) delineate outcome differences between glioblastoma patients with and without contrast enhancement., Methods: The RANO resect group retrospectively compiled a global, eight-center cohort of patients with newly diagnosed glioblastoma per WHO 2021 classification. The associations between postoperative tumor volumes and outcome were analyzed. Propensity score-matched analyses were constructed to compare glioblastomas with and without contrast enhancement., Results: Among 1323 newly diagnosed IDH-wildtype glioblastomas, we identified 98 patients (7.4%) without contrast enhancement. In such patients, smaller postoperative tumor volumes were associated with more favorable outcome. There was an exponential increase in risk for death with larger residual non-CE tumor. Accordingly, extensive resection was associated with improved survival compared to lesion biopsy. These findings were retained on a multivariable analysis adjusting for demographic and clinical markers. Compared to CE glioblastoma, patients with non-CE glioblastoma had a more favorable clinical profile and superior outcome as confirmed in propensity score analyses by matching the patients with non-CE glioblastoma to patients with CE glioblastoma using a large set of clinical variables., Conclusions: The absence of contrast enhancement characterizes a less aggressive clinical phenotype of IDH-wildtype glioblastomas. Maximal resection of non-CE tumors has prognostic implications and translates into favorable outcome., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Neuro-Oncology.)

Background: This study aims to investigate the efficacy of multifactorial MRI in diagnosing breast cancer, specifically in the context of predicting lymphovascular invasion (LVI). Materials & methods: The patients were stratified into two groups: the primary group (100 patients) and the validation group (100 patients), based on essential characteristics. Multifactorial MRI, encompassing tumor size evaluation, diffusion coefficient assessment and dynamic contrast enhancement, was employed for patient examination. Results: Statistically significant differences were observed in tumor size, diffusion coefficient and dynamic contrast enhancement between groups with LVI (LVI+) and those without (LVI-). Key parameters were identified for predicting the degree of invasion. Conclusion: The results affirm the effectiveness of multifactorial MRI in forecasting LVI.

Introduction: To compare CT (computed tomography) values for enhancement of the abdominal aorta and liver parenchyma during dynamic contrast enhancement (CE) CT in cirrhotic patients with and without splenomegaly (SM)., Methods: We considered 258 patients (83 males and 46 females for the splenomegaly group, and 83 males and 46 females for the control group) for this retrospective study. We measured CT values in the abdominal aorta and hepatic parenchyma during the hepatic arterial (HAP) and portal venous (PVP) phases. The aortic CE at HAP and the hepatic parenchymal CE at PVP were compared between the two groups. For success rate of scans, we also calculated the optimal CE rates (>280 HU in the abdominal aorta and >50 HU in the hepatic parenchyma) for each group., Results: In the SM group, the CE for abdominal aorta was decreased during the aortic phase for a dynamic CE-CT (p < 0.05). When evaluating the success rates, they were found to be 65.1 % and 58.9 % in the SM group and 81.4 % and 72.3 % in the non-SM group (p < 0.05)., Conclusion: The success rate of scans and CE for the abdominal aorta during the aortic phase exhibited a significant decrease during dynamic CE-CT scans on patients with SM. Patients with SM may have reduced diagnostic ability with typical contrast injection protocols., Implications for Practice: It may be necessary to change the injection rates and contrast medium volume during CE-CT depending on the presence or absence of SM., Competing Interests: Conflict of interest statement None., (Copyright © 2023 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.)

Introduction: This study aimed to compare the vascular enhancement and radiation dose in preoperative transcatheter aortic valve implantation (TAVI) computed tomography (CT) with a reduced contrast medium (CM) using volume scans in 256-multidetector row CT (MDCT) with a standard CM using 64-MDCT., Methods: This study included 78 patients with preoperative TAVI CT with either 64- or 256-MDCT. The CM was injected at 1.5 mL/kg in the 64-MDCT group and 1.0 mL/kg in the 256-MDCT group. We compared vascular enhancement of the aortic root and access routes, image quality (IQ) scores, and radiation dose in both groups., Results: Despite the reduced CM (by 33 %) in the 256-MDCT group, the mean vascular enhancement of the right and left subclavian arteries was significantly higher than that in the 64-MDCT group [284 and 267 Hounsfield units (HU) vs. 376 and 359 HU; p < 0.05]; however, no significant differences in the mean vascular enhancement in the ascending aorta, abdominal aorta at the celiac level, and bilateral common femoral arteries were observed between the two groups (p > 0.05 for all). The median IQ scores at the aortic root were higher in the 256-MDCT group than in the 64-MDCT group (3 vs. 4; p < 0.05), and those at the femoral access routes were comparable (4 vs. 4; p = 0.33). The mean effective dose was significantly reduced by 30 % in the 256-MDCT group (23.6 vs. 16.3 mSv; p < 0.05)., Conclusion: In preoperative TAVI CT, volume scans using 256-MDCT provide comparable or better vascular enhancement and IQ with a 30 % reduction in CM and radiation dose than those using 64-MDCT., Implications for Practice: Volume scan using 256-MDCT for preoperative TAVI CT may reduce CM and radiation dose in TAVI patients with renal dysfunction., (Copyright © 2023 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.)

We report a case of a young man with a slow progression of cervical spondylotic myelopathy (CSM). Cervical magnetic resonance imaging (MRI) revealed a mild cervical discbulging at C5-C6 and an area of atypically enlarged intramedullary high signal intensity extending from C4-C7 (T2-weighted) with contrast enhancement at C5-C6 (T1-weighted). Neurological and radiological diagnoses tend to favor demyelinating diseases, which interfere with the diagnosis of CSM. Patients were followed up and examined by MRI at 3 months, 1 year, and 2 years after surgery. The patient's symptoms improved immediately postoperatively. The functional result according to the modified Japanese Orthopedic Association (JOA) score improved from 10 to 13 within 3 months. He continued to improve neurologically over the first postoperative year. Two years postoperatively, a T2-weighted MRI showed that the edema signal had disappeared completely, and a fat-saturated T2-weighted MRI showed only slight abnormal signal. The numbness and weakness of the extremities had improved, and his JOA score was 16. Spinal cord edema is occasionally seen with CSM. In the case presented, the contrast enhancement was localized at the site of the greatest narrowing of the spinal canal and compression of the spinal cord. This coincidence was the best indicator of a mechanical cause of the spinal cord changes. This feature should increase physician's confidence in distinguishing CSM from intramedullary tumors and myelitis. Surgical decompression may be beneficial in improving neurologic outcomes., Competing Interests: The authors declare that they have no competing interests., (© 2023 The Authors. Clinical Case Reports published by John Wiley & Sons Ltd.)

Porosity defects can be found in many engineering structures and their inspection remains a challenge in the field of ultrasonic non-destructive testing. In this paper, ultrasonic array imaging of porosity defects has been studied with the aim of improving the image quality in the "dead zone", which is caused by the masking effects of the uppermost pores. The proposed approach first extracts contributions of the uppermost pores based on a single scattering model by adopting convolutional sparse coding. The extracted dominant contributions are then subtracted from the array data before forming an image, facilitating detection and localization of pores in the shadow zone. The performance of the proposed approach has been studied in simulation and experiments, and the mean localization errors of the pores are small (i.e., within 0.27 mm or 0.14λ). In addition, the effects of measurement noise and imaging parameters on robustness of the imaging result have been analyzed, providing guidelines for practical implementation of the proposed approach., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Computed tomography (CT) angiography (CTA) is a non-invasive imaging method used to detect arteries and examine various brain diseases. When CTA is performed for follow-up or postoperative evaluation, reproducibility of vessel delineation is required. A reproducible and stable contrast enhancement can be achieved by manipulating the factors affecting it. Previous studies have investigated several factors that alter the contrast enhancement of arteries. However, no reports establishing the effect of different operators on contrast enhancement exist., Purpose: To assess the differences between inter-operator arterial contrast enhancement in cerebral CTA using Bayesian statistical modeling., Methods: Image data were obtained using a multistage sampling method from the cerebral CTA scans of patients who underwent the process between January 2015 and December 2018. Several Bayesian statistical models were developed, and the objective variable was the mean CT number of the bilateral internal carotid arteries after contrast enhancement. The explanatory variables were sex, age, fractional dose (FD), and the operator's information. The posterior distributions of the parameters were computed via Bayesian inference using the Markov chain Monte Carlo (MCMC) method, with the Hamiltonian Monte Carlo method employed as the algorithm. The posterior predictive distributions were computed using the posterior distributions of the parameters. Finally, the differences between inter-operator arterial contrast enhancement on the CT number in cerebral CTA were estimated., Results: The posterior distributions showed that all parameters representing the difference between operators included zero at the 95% credible intervals (CIs). The maximum mean difference between inter-operator CT number in the posterior predictive distribution was only 12.59 Hounsfield units (HUs)., Conclusions: The Bayesian statistical modeling results suggest that contrast enhancement of cerebral CTA examination between operator-to-operator differences in postcontrast CT number was small compared to those within-operator differences resulting from factors not considered in the model., (© 2023 American Association of Physicists in Medicine.)

Micro-computed tomography (micro-CT) provides valuable data for studying soft tissue, though it is often affected by sample movement during scans and low contrast in X-ray absorption. This can result in lower image quality and geometric inaccuracies, collectively known as 'artefacts'. To mitigate these issues, samples can be embedded in hydrogels and enriched with heavy metals for contrast enhancement. However, the long-term durability of these enhancements remains largely unexplored. In this study, we examine the effects of two contrast enhancement agents - iodine and phosphotungstic acid (PTA) - and two hydrogels - agarose and Poloxamer 407 - over a 14-day period. We used Drosophila melanogaster as a test model for our investigation. Our findings reveal that PTA and agarose are highly durable, while iodine and poloxamer hydrogel exhibits higher leakage rates. These observations lay the foundation for estimating contrast stabilities in contrast-enhanced micro-CT with hydrogel embedding and serve to inform future research in this field., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: In image processing, image segmentation is a more challenging task due to different shapes, locations, image intensities, etc. Brain tumors are one of the most common diseases in the world. So, the detection and segmentation of brain tumors are important in the medical field., Objective: The primary goal of this work is to use the proposed methodology to segment brain MRI images into tumor and non-tumor segments or pixels., Methods: In this work, we first selected the MRI medical images from the BraTS2020 database and transferred them to the contrast enhancement phase. Then, we applied thresholding for contrast enhancement to enhance the visibility of structures like blood arteries, tumors, or abnormalities. After the contrast enhancement process, the images were transformed into the image denoising phase. In this phase, a fourth-order partial differential equation was used for image denoising. After the image denoising process, these images were passed on to the segmentation phase. In this segmentation phase, we used an elephant herding algorithm for centroid optimization and then applied the multi-kernel fuzzy c-means clustering for image segmentation., Results: Peak signal-to-noise ratio, mean square error, sensitivity, specificity, and accuracy were used to assess the performance of the proposed methods. According to the findings, the proposed strategy produced better outcomes than the conventional methods., Conclusion: Our proposed methodology was reported to be a more effective technique than existing techniques., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Competing Interests: None

Purpose: The usage of iodinated contrast media (ICM) can improve the sensitivity and specificity of computed tomography (CT) for many clinical indications. However, the adverse effects of ICM administration can include renal injury, life-threatening allergic-like reactions, and environmental contamination. Deep learning (DL) models can generate full-dose ICM CT images from non-contrast or low-dose ICM administration or generate non-contrast CT from full-dose ICM CT. Eliminating the need for both contrast-enhanced and non-enhanced imaging or reducing the amount of required contrast while maintaining diagnostic capability may reduce overall patient risk, improve efficiency and minimize costs. We reviewed the current capabilities of DL to reduce the need for contrast administration in CT., Methods: We conducted a systematic review of articles utilizing DL to reduce the amount of ICM required in CT, searching MEDLINE, Embase, Compendex, Inspec, and Scopus to identify papers published from 2016 to 2022. We classified the articles based on the DL model and ICM reduction., Results: Eighteen papers met the inclusion criteria for analysis. Of these, ten generated synthetic full-dose (100%) ICM from real non-contrast CT, while four augmented low-dose to full-dose ICM CT. Three used DL to create synthetic non-contrast CT from real 100% ICM CT, while one paper used DL to translate the 100% ICM to non-contrast CT and vice versa. DL models commonly used generative adversarial networks trained and tested by paired contrast-enhanced and non-contrast or low ICM CTs. Image quality metrics such as peak signal-to-noise ratio and structural similarity index were frequently used for comparing synthetic versus real CT image quality., Conclusion: DL-generated contrast-enhanced or non-contrast CT may assist in diagnosis and radiation therapy planning; however, further work to optimize protocols to reduce or eliminate ICM for specific pathology is still needed along with a dedicated assessment of the clinical utility of these synthetic images., (© 2023. CARS.)

Cancer is one of the leading significant causes of illness and chronic disease worldwide. Skin cancer, particularly melanoma, is becoming a severe health problem due to its rising prevalence. The considerable death rate linked with melanoma requires early detection to receive immediate and successful treatment. Lesion detection and classification are more challenging due to many forms of artifacts such as hairs, noise, and irregularity of lesion shape, color, irrelevant features, and textures. In this work, we proposed a deep-learning architecture for classifying multiclass skin cancer and melanoma detection. The proposed architecture consists of four core steps: image preprocessing, feature extraction and fusion, feature selection, and classification. A novel contrast enhancement technique is proposed based on the image luminance information. After that, two pre-trained deep models, DarkNet-53 and DensNet-201, are modified in terms of a residual block at the end and trained through transfer learning. In the learning process, the Genetic algorithm is applied to select hyperparameters. The resultant features are fused using a two-step approach named serial-harmonic mean. This step increases the accuracy of the correct classification, but some irrelevant information is also observed. Therefore, an algorithm is developed to select the best features called marine predator optimization (MPA) controlled Reyni Entropy. The selected features are finally classified using machine learning classifiers for the final classification. Two datasets, ISIC2018 and ISIC2019, have been selected for the experimental process. On these datasets, the obtained maximum accuracy of 85.4% and 98.80%, respectively. To prove the effectiveness of the proposed methods, a detailed comparison is conducted with several recent techniques and shows the proposed framework outperforms.

Introduction: Trigeminal ganglion contrast enhancement (TGCE) is reported to be a normal and a common finding on magnetic resonance imaging studies of dogs, cats and humans. The intent of the present study was to describe the anatomical characteristics of the trigeminal ganglion, its surrounding structures, and histological features that are relevant to explain or hypothesize on the reason for TGCE on T1-weighted post-contrast MRI studies of the brain in dogs., Methods: Eight dog cadavers were dissected to study the anatomy of the trigeminal ganglion. The presence and anatomy of vessels was studied by dissection and by histological techniques. Two trigeminal ganglia were isolated and stained with hematoxylin-eosin (HE). Two other trigeminal ganglia included in the trigeminal canal and trigeminal cavity were decalcified with formic acid/formalin for 12 weeks and stained with HE to study the related vessels. Additionally, a corrosion cast was obtained from a separate canine specimen., Results: Leptomeninges and a subarachnoid space were identified at the level of the trigeminal nerve roots and the trigeminal ganglion. No subarachnoid space was identified and leptomeninges were no longer present at the level of the three trigeminal nerve branches. Small arterial vessels ran to and supplied the trigeminal ganglion, passing through the dura mater. No venous plexus was visualized at the level of the trigeminal ganglion in the dissections. A complex arterial vascular network was identified within the leptomeningeal covering of the trigeminal ganglion and was best appreciated in the corrosion cast. Histological examination revealed small-to moderate-sized blood vessels located in the epineurium around the ganglion; from there a multitude of arterioles penetrated into the perineurium. Small endoneurial branches and capillaries penetrated the ganglion and the trigeminal nerve branches., Discussion: Limitations to this study include the limited number of canine specimens included and the lack of electron microscopy to further support current hypotheses included in our discussion. In conclusion, this study provides further support to the theory that TGCE in dogs may be due an incomplete blood-nerve barrier or blood-ganglion barrier at the interface between the central nervous system and the peripheral nervous system., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Santifort, Glass, Pumarola and Aige Gil.)

Background: The presence of contrast enhancement (CE) on magnetic resonance imaging (MRI) is one of the principal criteria for diagnosis and disease activity of multiple sclerosis (MS). Therefore, MS patients are frequently exposed to contrast agents, which may cause deposition in the brain, restricting its use in repeat examinations. Thus, serum biomarkers may be valuable as surrogate parameters to evaluate MS activity., Methods: REDUCE-GAD was a prospective, multicentric, biobanking study to determine whether established serum markers (neurofilament light chain [NfL], glial fibrillary acidic protein [GFAP], tau protein, ubiquitin-carboxyl-terminal-hydrolase (UCH-L1), S100B and matrix-metalloproteinase 9 [MMP9]) are predictive of CE-positive MRI lesions. Blood samples were obtained from patients undergoing MRI 5 days before or after collection., Results: Patients (N = 102) from four different centers with confirmed MS or related disorders were included; n = 57 (55.9%) showed CE on MRI versus n = 45 (44.1%) without CE. Only higher NfL values indicated CE (odds ratio [OR] 1.05; 95% CI 1.0-1.09) and were correlated with number (ρ = 0.47; p < 0.001) and diameter of CE lesions (ρ = 0.58; p < 0.001). Nfl Z-scores improved diagnostic accuracy (OR 1.52; 95% CI 1.06-2.18). Receiver operator characteristic analysis revealed a reasonable cut-off value for NfL at 14.1 pg/mL (sensitivity 49.1%; specificity 82.2%; positive predictive value 77.8%; negative predictive value 56.0%). NfL ≥59.2 pg/mL was exclusively observed in patients with CE., Conclusions: Evaluation of several possible serum biomarkers for CE in MS patients provided the most robust results for NfL, particularly as Z-scores. Following further evaluation, biomarkers may help stratify the application of contrast agents for brain imaging in MS patients., (© 2023 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Purpose: Minimally invasive treatments for renal carcinoma offer a low rate of complications and quick recovery. One drawback of the use of computed tomography (CT) for needle guidance is the use of iodinated contrast agents, which require an increased X-ray dose and can potentially cause adverse reactions. The purpose of this work is to generalise the problem of synthetic contrast enhancement to allow the generation of multiple phases on non-contrast CT data from a real-world, clinical dataset without training multiple convolutional neural networks., Methods: A framework for switching between contrast phases by conditioning the network on the phase information is proposed and compared with separately trained networks. We then examine how the degree of supervision affects the generated contrast by evaluating three established architectures: U-Net (fully supervised), Pix2Pix (adversarial with supervision), and CycleGAN (fully adversarial)., Results: We demonstrate that there is no performance loss when testing the proposed method against separately trained networks. Of the training paradigms investigated, the fully adversarial CycleGAN performs the worst, while the fully supervised U-Net generates more realistic voxel intensities and performed better than Pix2Pix in generating contrast images for use in a downstream segmentation task. Lastly, two models are shown to generalise to intra-procedural data not seen during the training process, also enhancing features such as needles and ice balls relevant to interventional radiological procedures., Conclusion: The proposed contrast switching framework is a feasible option for generating multiple contrast phases without the overhead of training multiple neural networks, while also being robust towards unseen data and enhancing contrast in features relevant to clinical practice., (© 2023. The Author(s).)