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Background Breast cancer (BC) is one of the main causes of cancer-related mortality among women. For clinical management to help patients survive longer and spend less time on treatment, early and precise cancer identification and differentiation of breast lesions are crucial. To investigate the accuracy of radiomic features (RF) extracted from dynamic contrast-enhanced Magnetic Resonance Imaging (DCE MRI) for differentiating invasive ductal carcinoma (IDC) from invasive lobular carcinoma (ILC). Methods This is a retrospective study. The IDC of 30 and ILC of 28 patients from Dukes breast cancer MRI data set of The Cancer Imaging Archive (TCIA), were included. The RF categories such as shape based, Gray level dependence matrix (GLDM), Gray level co-occurrence matrix (GLCM), First order, Gray level run length matrix (GLRLM), Gray level size zone matrix (GLSZM), NGTDM (Neighbouring gray tone difference matrix) were extracted from the DCE-MRI sequence using a 3D slicer. The maximum relevance and minimum redundancy (mRMR) was applied using Google Colab for identifying the top fifteen relevant radiomic features. The Mann-Whitney U test was performed to identify significant RF for differentiating IDC and ILC. Receiver Operating Characteristic (ROC) curve analysis was performed to ascertain the accuracy of RF in distinguishing between IDC and ILC. Results Ten DCE MRI-based RFs used in our study showed a significant difference (p Conclusions MRI-based RF derived from DCE sequences can be used in clinical settings to differentiate malignant lesions of the breast, such as IDC and ILC, without requiring intrusive procedures.

Background Breast cancer (BC) is one of the main causes of cancer-related mortality among women. For clinical management to help patients survive longer and spend less time on treatment, early and precise cancer identification and differentiation of breast lesions are crucial. To investigate the accuracy of radiomic features (RF) extracted from dynamic contrast-enhanced Magnetic Resonance Imaging (DCE MRI) for differentiating invasive ductal carcinoma (IDC) from invasive lobular carcinoma (ILC). Methods This is a retrospective study. The IDC of 30 and ILC of 28 patients from Dukes breast cancer MRI data set of The Cancer Imaging Archive (TCIA), were included. The RF were extracted from the DCE-MRI sequence using a 3D slicer. The relevance of RF for differentiating IDC from ILC was evaluated using the maximum relevance minimum redundancy (mRMR) and Mann-Whitney test. Receiver Operating Characteristic (ROC) curve analysis was performed to ascertain the accuracy of RF in distinguishing between IDC and ILC. Results Ten DCE MRI-based RFs used in our study showed a significant difference (p Conclusions MRI-based RF derived from DCE sequences can be used in clinical settings to differentiate malignant lesions of the breast, such as IDC and ILC, without requiring intrusive procedures.

As magnetic resonance imaging (MRI) becomes increasingly integrated into radiotherapy (RT) for enhanced treatment planning and adaptation, the inherent geometric distortion in acquired MR images pose a potential challenge to treatment accuracy. This study aimed to evaluate the geometric distortion levels in the clinical MRI protocols used across Danish RT centers and discuss influence of specific sequence parameters. Based on the variety in geometric performance across centers, we assess if harmonization of MRI sequences is a relevant measure. Nine centers participated with 12 MRI scanners and MRI-Linacs (MRL). Using a travelling phantom approach, a reference MRI sequence was used to assess variation in baseline distortion level between scanners. The phantom was also scanned with local clinical MRI sequences for brain, head/neck (H/N), abdomen, and pelvis. The influence of echo time, receiver bandwidth, image weighting, and 2D/3D acquisition was investigated. We found a large variation in geometric accuracy across 93 clinical sequences examined, exceeding the baseline variation found between MRI scanners (σ = 0.22 mm), except for abdominal sequences where the variation was lower. Brain and abdominal sequences showed lowest distortion levels ([0.22, 2.26] mm), and a large variation in performance was found for H/N and pelvic sequences ([0.19, 4.07] mm). Post hoc analyses revealed that distortion levels decreased with increasing bandwidth and a less clear increase in distortion levels with increasing echo time. 3D MRI sequences had lower distortion levels than 2D (median of 1.10 and 2.10 mm, respectively), and in DWI sequences, the echo-planar imaging read-out resulted in highest distortion levels. There is a large variation in the geometric distortion levels of clinical MRI sequences across Danish RT centers, and between anatomical sites. The large variation observed makes harmonization of MRI sequences across institutions and adoption of practices from well-performing anatomical sites, a relevant measure within RT. [ABSTRACT FROM AUTHOR]

Background Breast cancer (BC) is one of the main causes of cancer-related mortality among women. For clinical management to help patients survive longer and spend less time on treatment, early and precise cancer identification and differentiation of breast lesions are crucial. To investigate the accuracy of radiomic features (RF) extracted from dynamic contrast-enhanced Magnetic Resonance Imaging (DCE MRI) for differentiating invasive ductal carcinoma (IDC) from invasive lobular carcinoma (ILC). Methods This is a retrospective study. The IDC of 30 and ILC of 28 patients from Dukes breast cancer MRI data set of The Cancer Imaging Archive (TCIA), were included. The RF categories such as shape based, Gray level dependence matrix (GLDM), Gray level co-occurrence matrix (GLCM), First order, Gray level run length matrix (GLRLM), Gray level size zone matrix (GLSZM), NGTDM (Neighbouring gray tone difference matrix) were extracted from the DCE-MRI sequence using a 3D slicer. The maximum relevance and minimum redundancy (mRMR) was applied using Google Colab for identifying the top fifteen relevant radiomic features. The Mann-Whitney U test was performed to identify significant RF for differentiating IDC and ILC. Receiver Operating Characteristic (ROC) curve analysis was performed to ascertain the accuracy of RF in distinguishing between IDC and ILC. Results Ten DCE MRI-based RFs used in our study showed a significant difference (p

Accurate urethra contouring is critical in prostate SBRT. We compared urethra contouring on CT-urethrogram and T2-weighted MRI. The dice similarity coefficient, Jaccard index, Hausdorff distance and mean distance to agreement were evaluated. All four metrics indicate better agreement and less variability in urethra contouring on CT-urethrogram, compared to T2-weighted MRI.

BACKGROUND: Malignant Primary Brain Tumor (MPBT) and Metastatic Brain Tumor (MBT) are the most common types of brain tumors, which require different management approaches. Magnetic Resonance Imaging (MRI) is the most frequently used modality for assessing the presence of these tumors. The utilization of Deep Learning (DL) is expected to assist clinicians in classifying MPBT and MBT more effectively. OBJECTIVE: This study aims to examine the influence of MRI sequences on the classification performance of DL techniques for distinguishing between MPBT and MBT and analyze the results from a medical perspective. METHODS: Total 1,360 images performed from 4 different MRI sequences were collected and preprocessed. VGG19 and ResNet101 models were trained and evaluated using consistent parameters. The performance of the models was assessed using accuracy, sensitivity, and other precision metrics based on a confusion matrix analysis. RESULTS: The ResNet101 model achieves the highest accuracy of 83% for MPBT classification, correctly identifying 90 out of 102 images. The VGG19 model achieves an accuracy of 81% for MBT classification, accurately classifying 86 out of 102 images. T2 sequence shows the highest sensitivity for MPBT, while T1C and T1 sequences exhibit the highest sensitivity for MBT. CONCLUSIONS: DL models, particularly ResNet101 and VGG19, demonstrate promising performance in classifying MPBT and MBT based on MRI images. The choice of MRI sequence can impact the sensitivity of tumor detection. These findings contribute to the advancement of DL-based brain tumor classification and its potential in improving patient outcomes and healthcare efficiency. [ABSTRACT FROM AUTHOR]

Background: Gliomas are frequent tumors of brain parenchyma, which have histology similar to that of glial cells. Accurate glioma grading is required for determining clinical management. The background of this study is to investigate the accuracy of magnetic resonance imaging (MRI)‑based radiomic features extracted from multiple MRI sequences in differentiating low and high‑grade gliomas. Materials and Methods: This is a retrospective study. It includes two groups. Group A includes patients with confirmed histopathological diagnosis of low (23) and high‑grade (58) gliomas from 2012 to 2020 were included. The MRI images were acquired using a Signa HDxt 1.5 Tesla MRI (GE Healthcare, Milwaukee, USA). Group B includes an external test set consisting of low‑ (20) and high‑grade gliomas (20) obtained from The Cancer Genome Atlas (TCGA). The radiomic features were extracted from axial T2, apparent diffusion coefficient map, axial T2 fluid‑attenuated inversion recovery, and axial T1 post‑contrast sequences for both the groups. The Mann − Whitney U test was performed to assess the significant radiomic features useful for distinguishing the glioma grades for Group A. To determine the accuracy of radiomic features for differentiating gliomas, AUC was calculated from receiver operating characteristic curve analysis for both groups. Results: Our study noticed in Group A, fourteen MRI‑based radiomic features from four MRI sequences showed a significant difference (p < 0.001) in differentiating gliomas. In Group A, we noticed T1 post‑contrast radiomic features such as first‑order variance (FOV) (sensitivity − 94.56%, specificity – 97.51%, AUC – 0.969) and GLRLM long‑run gray‑level emphasis (sensitivity – 97.54%), specificity – 96.53%, AUC – 0.972) had the highest discriminative power for distinguishing the histological subtypes of gliomas. Our study noticed no statistical significant difference between ROC curves of significant radiomic features for both groups. In Group B, the T1 post‑contrast radiomic features such as FOV (AUC–0.933) and GLRLM long‑run gray‑level emphasis (AUC–0.981) had also shown high discriminative power for distinguishing the gliomas. Conclusion: Our study concludes that MRI‑based radiomic features extracted from multiple MRI sequences provide a non‑invasive diagnosis of low‑ and high‑grade gliomas and can be implemented in clinical settings for diagnosing the glioma grades. [ABSTRACT FROM AUTHOR]

Introduction Focal cortical dysplasia (FCD) is a most common cause of intractable focal epilepsy in children. Surgery is considered as a radical option for such patients with the prerequisite of lesion detection. Magnetic resonance imaging (MRI) plays a significant role in detection of FCDs in epilepsy patients; however, the detection of FCDs even in epilepsy dedicated MRI sequence shows relatively low positive rate. Last year, Middlebrooks et al introduced the novel three-dimensional Edge-Enhancing Gradient Echo (3D-EDGE) MRI sequence and using this sequence successfully identified five cases of FCDs which indicates its potential role in those epilepsy patients who may have FCDs. Case Presentation We present a 14-year-old, right-handed, male patient who has suffered from drug-resistant epilepsy over the past 3 years. It was unable to localize the lesion of the seizure, even using the series of epilepsy dedicated MRI sequences. Inspired by the previous report, the lesion of the seizure was successfully targeted by 3D-EDGE sequence. Combined with intraoperative navigation and precisely removed the lesion. He was uneventfully recovered with no signs of cerebral dysfunction and no seizure recurrence 8 months after surgery. Conclusion The 3D-EDGE sequences show a higher sensitivity for FCD detection in epilepsy patients compared with a series of epilepsy-dedicated MRI protocols. We confirmed that the study by Middlebrooks et al is of great clinical value. If the findings on routine MRI sequences or even epilepsy-dedicated MRI sequences were reported as negative, however, the semiology, video-electroencephalography, and fluorodeoxyglucose–positron emission tomography results suggest a local abnormality, and the results are concordant with each other, a 3D-EDGE sequence may be a good option. [ABSTRACT FROM AUTHOR]

Abstract Background MR imaging plays a significant role in detection and characterization of different brain diseases. The role of the post-contrast T1-weighted image magnetic resonance imaging (T1W MRI) sequence has been widely established in previous studies and clinical practice. In this study, we aim to share our experience as regards the added value of contrast-enhanced fluid-attenuated inversion recovery (CE-FLAIR) sequence in the diagnosis of various intracranial pathological conditions and evaluate its usefulness in comparison with post-contrast T1W images. Results Based on the final radiological diagnosis, the total cases were subdivided into three categories, and the majority of our cases were tumors (81.2%), followed by multiple sclerosis (11.8%), and the least was central nervous system infection (7.1%). CE-FLAIR showed superior enhancement in 35 cases (50.7) and equal enhancement in 25 cases (36.3%). However, it showed less enhancement than post-contrast T1W images in 9 cases (13%). Excellent inter-observer agreement (97.65%) was noted. Regarding lesion conspicuity, good delineation was found in the majority of cases (64.7%), fair delineation in 12.9%, and no delineation in 22.4%. A statistically significant difference was found in signal intensity of lesion between pre- and post-contrast FLAIR sequences. Contrast to background ratio was statistically significant in CE FLAIR images in comparison to CE T1 images. Conclusion CE-FLAIR imaging should be used as a routine or adjunctive sequence to CE-T1WI to enhance early detection and increase the diagnostic confidence in MRI examination of different brain pathological conditions.

Schizencephaly is one of the rare cortical malformations that classify in the group of neurological migration defects. The appearance of the anomaly is in the form of a cleft that passes through the brain parenchyma. In mild types, the cleft does not reach the lateral ventricle. Demonstrating the presence of polymicrogyria, optimal evaluation of the cortex and determining the cleft trace are essential in the radiological evaluation of schizencephaly. Because differential diagnosis should be made with heterotopias and focal cortical dysplasia. We present a case of a 21-yearold female patient with closed-lip schizencephaly accompanied by MRI findings. Polymicrogyria is best detected in sagittal T2 sequences, while the difference of white matter and grey matter are well observed in T1 and FLAIR sequences. The benefit of diffusion-weighted images in schizencephaly is unclear. The ADC values of the grey matter adjacent to the cleft are close to the lower limit of normal. Susceptibility weighted image (SWI) sequence has no place in the evaluation of schizencephaly. It can be beneficial for the exclusion of vascular malformations, hemorrhage and differential diagnosis.

Introduction Cochlear implant (CI) magnets and surgical techniques (e.g., positioning) have made an impact on the relationship between CI and magnetic resonance imaging (MRI) by solving the problem of pain and artifact. Recent investigations displayed the possibility to evaluate the CI electrode position by MRI in vivo. However, further improved perceptual quality is needed to allow an improved evaluation of the electrode. Aims The aim of this study was to assess a cochlear model for the examination of CI electrode pattern and MRI sequences in vitro. Materials and Methods We investigated CI electrodes in a fluid-filled three-dimensional artificial scala tympani model combined with a fluid package in a 3T MRI scanner. Different high-resolution T2 sequences (0.6–0.2 mm voxel size) were used for the visual electrode pattern evaluation for finding an optimized sequence. Results Artificial models can be used to evaluate MRI characteristics of CI electrodes. In our scanner configuration, a 0.3 mm voxel and 0.9 mm slice thickness sequence showed the best compromise between resolution and scanning time. Conclusion and Significance MRI model-based testing can be performed in vitro to evaluate CI electrodes' pattern and to optimize sequences. An MRI model is a tool for in vitro testing of MRI sequences and might help for future in vivo applications. [ABSTRACT FROM AUTHOR]

Background: MR imaging plays a significant role in detection and characterization of different brain diseases. The role of the post-contrast T1-weighted image magnetic resonance imaging (T1W MRI) sequence has been widely established in previous studies and clinical practice. In this study, we aim to share our experience as regards the added value of contrast-enhanced fluid-attenuated inversion recovery (CE-FLAIR) sequence in the diagnosis of various intracranial pathological conditions and evaluate its usefulness in comparison with post-contrast T1W images. Results: Based on the final radiological diagnosis, the total cases were subdivided into three categories, and the majority of our cases were tumors (81.2%), followed by multiple sclerosis (11.8%), and the least was central nervous system infection (7.1%). CE-FLAIR showed superior enhancement in 35 cases (50.7) and equal enhancement in 25 cases (36.3%). However, it showed less enhancement than post-contrast T1W images in 9 cases (13%). Excellent inter-observer agreement (97.65%) was noted. Regarding lesion conspicuity, good delineation was found in the majority of cases (64.7%), fair delineation in 12.9%, and no delineation in 22.4%. A statistically significant difference was found in signal intensity of lesion between pre- and post-contrast FLAIR sequences. Contrast to background ratio was statistically significant in CE FLAIR images in comparison to CE T1 images. Conclusion: CE-FLAIR imaging should be used as a routine or adjunctive sequence to CE-T1WI to enhance early detection and increase the diagnostic confidence in MRI examination of different brain pathological conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • MR microscopy with spin-echo (SE) and its DEFT variant (DE-SE) was compared. • The signal dependence on RF pulse flip angles and on diffusion was studied. • DE-SE was found considerably more sensitive to flip angle deviations than SE. • Diffusion signal attenuation in MR microscopy with DE-SE may be significant. • The water signal ratio between DE-SE and SE images was 10:1 with short TRs. Rapid MR imaging of slowly relaxing samples is often challenging. The most commonly used solutions are found in multi spin-echo (RARE) sequences or gradient-echo (GE) sequences, which allow faster imaging of such samples with multiple acquisitions of k -space lines per excitation or imaging with very short repetition times (TR s). Another solution is the use of a spin-echo (SE) sequence superimposed with a driven equilibrium Fourier transform (DEFT) method. Such a (DE-SE) imaging sequence has two refocusing RF pulses that produce two spin-echoes. In the first echo, the signal is acquired from the k -space line, and in the second echo, a 90° RF pulse is applied, typically 180° out of phase with respect to the excitation RF pulse. This last RF pulse allows almost complete magnetization reversal back to the longitudinal orientation with minimal magnetization loss. The DE-SE sequence and its RARE variant are widely used in clinical imaging, but its use in MR microscopy has some peculiarities related to the usually less perfect RF pulse flip angles and diffusion. In this study, their effects are first theoretically analyzed and later verified by experiments on test samples performed on a 9.4 T system for MR microscopy. Experiments on a water-filled tube for TE = 3.4 ms and TR = 25–200 ms showed that the DE-SE sequence produces about 10 times more signal than the SE sequence in this TR range. Finally, the performance of the DE-SE sequence compared to the SE sequence was demonstrated on a biological sample. The presented DE-SE sequence has been shown to be effective for rapid imaging of samples with long T 1 relaxation times in MR microscopy and can also be considered as a suitable method for rapid proton density weighed imaging of materials. [ABSTRACT FROM AUTHOR]

Schizencephaly is one of the rare cortical malformations that classify in the group of neurological migration defects. The appearance of the anomaly is in the form of a cleft that passes through the brain parenchyma. In mild types, the cleft does not reach the lateral ventricle. Demonstrating the presence of polymicrogyria, optimal evaluation of the cortex and determining the cleft trace are essential in the radiological evaluation of schizencephaly. Because differential diagnosis should be made with heterotopias and focal cortical dysplasia. We present a case of a 21-yearold female patient with closed-lip schizencephaly accompanied by MRI findings. Polymicrogyria is best detected in sagittal T2 sequences, while the difference of white matter and grey matter are well observed in T1 and FLAIR sequences. The benefit of diffusion-weighted images in schizencephaly is unclear. The ADC values of the grey matter adjacent to the cleft are close to the lower limit of normal. Susceptibility weighted image (SWI) sequence has no place in the evaluation of schizencephaly. It can be beneficial for the exclusion of vascular malformations, haemorrhage and differential diagnosis. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BC) is one of the main causes of cancer-related mortality among women. For clinical management to help patients survive longer and spend less time on treatment, early and precise cancer identification and differentiation of breast lesions are crucial. To investigate the accuracy of radiomic features (RF) extracted from dynamic contrast-enhanced Magnetic Resonance Imaging (DCE MRI) for differentiating invasive ductal carcinoma (IDC) from invasive lobular carcinoma (ILC)., Methods: This is a retrospective study. The IDC of 30 and ILC of 28 patients from Dukes breast cancer MRI data set of The Cancer Imaging Archive (TCIA), were included. The RF categories such as shape based, Gray level dependence matrix (GLDM), Gray level co-occurrence matrix (GLCM), First order, Gray level run length matrix (GLRLM), Gray level size zone matrix (GLSZM), NGTDM (Neighbouring gray tone difference matrix) were extracted from the DCE-MRI sequence using a 3D slicer. The maximum relevance and minimum redundancy (mRMR) was applied using Google Colab for identifying the top fifteen relevant radiomic features. The Mann-Whitney U test was performed to identify significant RF for differentiating IDC and ILC. Receiver Operating Characteristic (ROC) curve analysis was performed to ascertain the accuracy of RF in distinguishing between IDC and ILC., Results: Ten DCE MRI-based RFs used in our study showed a significant difference (p <0.001) between IDC and ILC. We noticed that DCE RF, such as Gray level run length matrix (GLRLM) gray level variance (sensitivity (SN) 97.21%, specificity (SP) 96.2%, area under curve (AUC) 0.998), Gray level co-occurrence matrix (GLCM) difference average (SN 95.72%, SP 96.34%, AUC 0.983), GLCM interquartile range (SN 95.24%, SP 97.31%, AUC 0.968), had the strongest ability to differentiate IDC and ILC., Conclusions: MRI-based RF derived from DCE sequences can be used in clinical settings to differentiate malignant lesions of the breast, such as IDC and ILC, without requiring intrusive procedures., Competing Interests: No competing interests were disclosed., (Copyright: © 2024 Maiti S et al.)

• Neural networks can segment contrast-enhancing brain metastases as well as their surrounding edemas with a reduced number of input sequences. • For the segmentation of contrast enhancing metastases, T1-CE alone provides sufficient segmentation quality. • For the segmentation of the edema, the combination of T1-CE and T2-FLAIR is crucial. • In our external test cohort, T1-CE is most important for detecting brain metastases, and additional sequences do not improve sensitivity. Many automatic approaches to brain tumor segmentation employ multiple magnetic resonance imaging (MRI) sequences. The goal of this project was to compare different combinations of input sequences to determine which MRI sequences are needed for effective automated brain metastasis (BM) segmentation. We analyzed preoperative imaging (T1-weighted sequence ± contrast-enhancement (T1/T1-CE), T2-weighted sequence (T2), and T2 fluid-attenuated inversion recovery (T2-FLAIR) sequence) from 339 patients with BMs from seven centers. A baseline 3D U-Net with all four sequences and six U-Nets with plausible sequence combinations (T1-CE, T1, T2-FLAIR, T1-CE + T2-FLAIR, T1-CE + T1 + T2-FLAIR, T1-CE + T1) were trained on 239 patients from two centers and subsequently tested on an external cohort of 100 patients from five centers. The model based on T1-CE alone achieved the best segmentation performance for BM segmentation with a median Dice similarity coefficient (DSC) of 0.96. Models trained without T1-CE performed worse (T1-only: DSC = 0.70 and T2-FLAIR-only: DSC = 0.73). For edema segmentation, models that included both T1-CE and T2-FLAIR performed best (DSC = 0.93), while the remaining four models without simultaneous inclusion of these both sequences reached a median DSC of 0.81–0.89. A T1-CE-only protocol suffices for the segmentation of BMs. The combination of T1-CE and T2-FLAIR is important for edema segmentation. Missing either T1-CE or T2-FLAIR decreases performance. These findings may improve imaging routines by omitting unnecessary sequences, thus allowing for faster procedures in daily clinical practice while enabling optimal neural network-based target definitions. [ABSTRACT FROM AUTHOR]

Atrial fibrillation (AF) is the most common cardiac arrhythmia. At present, cardiac ablation is the main treatment procedure for AF. To guide and plan this procedure, it is essential for clinicians to obtain patient-specific 3D geometrical models of the atria. For this, there is an interest in automatic image segmentation algorithms, such as deep learning (DL) methods, as opposed to manual segmentation, an error-prone and time-consuming method. However, to optimize DL algorithms, many annotated examples are required, increasing acquisition costs. The aim of this work is to develop automatic and high-performance computational models for left and right atrium (LA and RA) segmentation from a few labelled MRI volumetric images with a 3D Dual U-Net algorithm. For this, a supervised domain adaptation (SDA) method is introduced to infer knowledge from late gadolinium enhanced (LGE) MRI volumetric training samples (80 LA annotated samples) to a network trained with balanced steady-state free precession (bSSFP) MR images of limited number of annotations (19 RA and LA annotated samples). The resulting knowledge-transferred model SDA outperformed the same network trained from scratch in both RA (Dice equals 0.9160) and LA (Dice equals 0.8813) segmentation tasks.

Accurate urethra contouring is critical in prostate SBRT. We compared urethra contouring on CT-urethrogram and T2-weighted MRI. The dice similarity coefficient, Jaccard index, Hausdorff distance and mean distance to agreement were evaluated. All four metrics indicate better agreement and less variability in urethra contouring on CT-urethrogram, compared to T2-weighted MRI., Competing Interests: 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., (© 2023 The Authors.)

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Copyright of West China Journal of Stomatology is the property of Sichuan University, West China College of Stomatology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

18 F-FDG PET/MRI might be the diagnostic method of choice for Hodgkin lymphoma patients, as it combines significant metabolic information from PET with excellent soft-tissue contrast from MRI and avoids radiation exposure from CT. However, a major issue is longer examination times than for PET/CT, especially for younger children needing anesthesia. Thus, a targeted selection of suitable whole-body MRI sequences is important to optimize the PET/MRI workflow. Methods: The initial PET/MRI scans of 84 EuroNet-PHL-C2 study patients from 13 international PET centers were evaluated. In each available MRI sequence, 5 PET-positive lymph nodes were assessed. If extranodal involvement occurred, 2 splenic lesions, 2 skeletal lesions, and 2 lung lesions were also assessed. A detection rate was calculated dividing the number of visible, anatomically assignable, and measurable lesions in the respective MRI sequence by the total number of lesions. Results: Relaxation time-weighted (T2w) transverse sequences with fat saturation (fs) yielded the best result, with detection rates of 95% for nodal lesions, 62% for splenic lesions, 94% for skeletal lesions, and 83% for lung lesions, followed by T2w transverse sequences without fs (86%, 49%, 16%, and 59%, respectively) and longitudinal relaxation time-weighted contrast-enhanced transverse sequences with fs (74%, 35%, 57%, and 55%, respectively). Conclusion: T2w transverse sequences with fs yielded the highest detection rates and are well suited for accurate whole-body PET/MRI in lymphoma patients. There is no evidence to recommend the use of contrast agents., (© 2023 by the Society of Nuclear Medicine and Molecular Imaging.)

Magnetic resonance imaging (MRI) has become the gold standard for imaging neurological tissues including the spinal cord. The use of MRI for imaging in the acute management of patients with spinal cord injury has increased significantly. This paper used a vigorous literature review with Downs and Black scoring, followed by a Delphi vote on the main conclusions. MRI is strongly recommended for the prognostication of acute spinal cord injury. The sagittal T2 sequence was particularly found to be of value. Four prognostication patterns were found to be predictive of neurological outcome (normal, single-level edema, multi-level edema, and mixed hemorrhage and edema). It is recommended that MRI be used to direct clinical decision making. MRI has a role in clearance, the ruling out of injury, of the cervical spine in the obtunded patient only if there is abnormality of the neurological exam. Patients with cervical spinal cord injuries have an increased risk of vertebral artery injuries but the literature does not allow for recommendation of magnetic resonance angiography as part of the routine protocol. Finally, time repetition (TR) and time echo (TE) values used to evaluate patients with acute spinal cord injury vary significantly. All publications with MRI should specify the TR and TE values used. [ABSTRACT FROM AUTHOR]

Summary: Plain film radiography is the mainstay of orthopaedic investigation. Magnetic resonance imaging (MRI) is however now being utilised more frequently and reveals pathology that may have been overlooked with the plain film. This paper describes the basic science of MRI. It also describes the most frequently used sequences in orthopaedic MRI, MRI safety, and types of scanner, artefacts and the use of gadolinium. [Copyright &y& Elsevier]

Background: Hepatic lesions constitute a daily challenge to radiology in clinical settings, and non-invasive methods are valuable in the characterization of these liver tumours. We undertook our investigation to assess the lesion characterization potential of MRI by evaluating several unenhanced MR sequences and the dynamic gadolinium (Gd)-enhanced technique. Methods: A total of 116 focal liver lesions in 116 patients were included in our retrospective study, and histological verification was available for 107 lesions. Nine haemangiomas had a follow-up of 2 years. The 1.5-T MR system was used. T1- and T2-weighted sequences and dynamic Gd-enhanced studies were evaluated by two individual readers as separate sequences and also collectively. Lesions were classified into benign or malignant, and a specific diagnosis was proposed. The McNemar test was used in statistical analysis, and interobserver variation was measured using kappa statistics. Results: Lesion classification into benign and malignant tumours (by evaluating all images in concert) was assessed in 83% and 89% of cases by readers 1 and 2, respectively. From single sequences, best lesion classification was achieved with Gd-enhanced T1 by both readers. The difference in classification was statistically significant when all sequences were evaluated in comparison with any single sequence alone ( P = 0.02). Specific diagnosis was correctly determined using all sequences together in 60% and 71% of cases by readers 1 and 2, respectively. For individual sequences, correct diagnosis was most frequently proposed with a Gd-enhanced T1-weighted sequence by both readers (59% and 65% for readers 1 and 2, respectively). Conclusion: Multisequential MRI using Gd-enhanced imaging performs extremely well in liver lesion classification, and with moderate ability to determine a specific diagnosis. [ABSTRACT FROM AUTHOR]

This article provides a brief overview of magnetic resonance imaging (MRI) of the cervical spine for the clinician. A basic review of MRI physics is followed by a discussion of the most common imaging sequences. The indications for contrast are outlined along with contraindications. Finally, a review of cervical spine anatomy is correlated with annotated images. [Copyright &y& Elsevier]

Four factors can be used in MR of bone marrow: fat-water distribution, artifacts induced by bone trabeculae, diffusion, and uptake of contrast media. Fat-water is imaged using T1-weighted spin-echo, short tau inversion recovery (STIR), and fast STIR, in- and out-of-phase gradient echo, and fat pre-saturation sequences; bone trabeculae by gradient echo with long TE; diffusion by single-shot spin-echo. The injection of contrast media is a more easy and efficient way to improve the specificity. The value and limitations of those sequences are discussed in marrow replacements (metastases, lymphoma, leukemia) and in myeloid hyperplasia or depletion. [ABSTRACT FROM AUTHOR]

Atrial fibrillation (AF) is the most common cardiac arrhythmia. At present, cardiac ablation is the main treatment procedure for AF. To guide and plan this procedure, it is essential for clinicians to obtain patient-specific 3D geometrical models of the atria. For this, there is an interest in automatic image segmentation algorithms, such as deep learning (DL) methods, as opposed to manual segmentation, an error-prone and time-consuming method. However, to optimize DL algorithms, many annotated examples are required, increasing acquisition costs. The aim of this work is to develop automatic and high-performance computational models for left and right atrium (LA and RA) segmentation from a few labelled MRI volumetric images with a 3D Dual U-Net algorithm. For this, a supervised domain adaptation (SDA) method is introduced to infer knowledge from late gadolinium enhanced (LGE) MRI volumetric training samples (80 LA annotated samples) to a network trained with balanced steady-state free precession (bSSFP) MR images of limited number of annotations (19 RA and LA annotated samples). The resulting knowledge-transferred model SDA outperformed the same network trained from scratch in both RA (Dice equals 0.9160) and LA (Dice equals 0.8813) segmentation tasks. [ABSTRACT FROM AUTHOR]

Some knowledge of MR theory is required to be able to achieve high contrast between bone metastases and normal marrow. Three factors are used in MR to diagnose bone metastases; fat-water distribution, artifacts induced by bone trabeculae, and uptake of contrast medium. Using MR-histological correlations based on specimens of the lumbar spine, and studies of patients, we explain the advantages and limitations of sequences studying fat and water (spin-echo T1, STIR, in- and out-of-phase gradient echo, fat presaturation), bone trabeculae (gradient echo with long TE), and the injection of contrast medium. [ABSTRACT FROM AUTHOR]

The authors have used MRI for investigation of 41 patients with pancreatic tumours. MR examinations were performed with 0.5 T superconductive equipment. Short TR, short TE spin echo (SE) sequences were obtained with 8 averages and 256×256 matrix. T2-weighted sequences were also acquired. T1-weighted SE sequences provided more detail, with high intrinsic contrast between the tumour and the normal pancreas; small lesions (19 smaller than 3 cm in diameter) were always detected on these images. T2-weighted SE sequences were not useful for lesion detection, due to the lower intrinsic contrast and the number of artefacts. T2-weighted sequences proved helpful for lesion characterisation in two cases of cystoadenocarcinoma only. Staging of the tumour was possible with MRI, with good assessment of local spread, lymphoadenopathy, vascular involvement and hepatic metastases. MRI of the pancreas at medium field strength can be an alternative to CT in selected cases. [ABSTRACT FROM AUTHOR]

Objective and Patients: One hundred and forty-one patients with recent joint trauma, aged 12-71 years, were imaged on a 0.2-T dedicated MRI system and evaluated for bone bruises. The most beneficial sequences were compared.Design: The diagnosis of post-traumatic bone marrow abnormalities was established in 20 of 141 patients on the basis of decreased signal intensity on T1-weighted SE and GRE sequences and increased signal intensity on T2-weighted TSE and fat-suppressed IRGE sequences. Signal changes within the bone marrow were evaluated and statistically correlated with normal bone.Results: The highest signal alteration was found on T1-weighted SE and GRE sequences, followed by IRGE, which detected smaller differences in signal intensity. T2-weighted TSE imaging showed the least contrast. The areas with bone marrow changes were approximately equal in size on T1-weighted SE and T2-weighted TSE sequences. The same areas depicted on IRGE and GRE sequences proved to be significantly larger (P < 0.01).Conclusion: Using a 0.2-T dedicated system T1-weighted SE, T1-weighted GRE and IRGE sequences were most effective in detecting conspicuous bone marrow alteration, while the T2-weighted TSE sequence was inferior. GRE and IRGE imaging showed areas about 4 times larger depicting bone marrow changes. On suspicion of bone bruise, a protocol including GRE and IRGE pulse sequences could be most beneficial. [ABSTRACT FROM AUTHOR]

Background and Purpose: To develop an evidence-based, standardized structured reporting (SR) method for brain MRI examinations in neonatal hypoxic-ischemic encephalopathy (HIE) suitable both for clinical and research use., Methods: SR template development was based on comprehensive review of the pertinent literature with the basic sections and subdivisions of the template defined according to MRI sequences (both conventional and diffusion-weighted, MR-spectroscopy (MRS), and T2*-weighted imaging), and the items targeted on age-related imaging patterns of HIE. In order to evaluate the usability of the proposed SR template we compared data obtained from the brain MR image analysis of 87 term and 19 preterm neonates with the literature. The enrolled 106 infants were born between 2013 and 2015, went through therapeutic hypothermia according to the TOBY criteria due to moderate to severe asphyxia and had at least one brain MRI examination within the first two weeks of life. Ethical approval was obtained for this retrospective study. Descriptive statistical analysis was also performed on data exported from the structured reporting system as feasibility test., Results: The mean gestational age of the study population was 38.3±2.2 weeks; brain MRI was performed on 5.8±2.9 day of life, hence in 78% of our patients after the conclusion of therapeutic hypothermia. Our main imaging findings were concordant to the pertinent literature. Moreover, we identified a characteristic temporal evolution of diffusion changes. Interestingly 18% (n=19/106) of the clinically asphyxiated infants had isolated axial-extraaxial haemorrhage without any imaging sign of HIE., Conclusion: In this article our approach of reporting HIE cases with our novel SR template is described. The SR template was found suitable for reporting HIE cases, moreover it uncovered time and location dependent evolution of diffusion abnormalities (and pseudonormalization, as well), suggesting its usefulness in clinical research applications. The high number of isolated intracranial haemorrhages, and the changing diffusion pattern emphasizes the importance of early imaging in HIE.