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Background: Improved characterization of healthy muscle aging is needed to establish early biomarkers in age‐related diseases. Purpose: To quantify age‐related changes on multiple MRI and clinical variables evaluated in the same cohort and identify correlations among them. Study Type: Prospective. Population: 70 healthy subjects (30 men) from 20 to 81 years old. Field Strength/Sequence: 3T/water T2 (multiecho SE, multi‐TE STEAM), water T1 (GRE MR Fingerprinting), fat‐fraction (multiecho GRE, multi‐TE STEAM), carnosine (PRESS), multicomponent water T2 (ISIS‐CPMG SE train), and 31P pulse‐acquire spectroscopy. Assessment: Age‐ and sex‐related changes on:Imaging: fat‐fraction (FFMRI), water T1 (T1‐H2O), and T2 (T2‐H2O‐MRI) and their heterogeneities ΔT1‐H2O and ΔT2‐H2O‐MRI in the posterior compartment (PC) and anterior compartment (AC) of the leg.1H spectroscopy: Carnosine concentration, pH, water T2 components (T2‐H2O‐CPMG), fat‐fraction (FFMRS), and water T2 (T2‐H2O‐MRS) in the gastrocnemius medialis.31P spectroscopy: Phosphodiesters (PDE), phosphomonoesters, inorganic phosphates (Pi), and phosphocreatine (PCr) normalized to adenosine triphosphate (ATP) and pH in the calf.Clinical evaluation: Body‐mass index (BMI), gait speed (GS), plantar flexion strength, handgrip strength (HS), HS normalized to wrist circumference (HSnorm), physical activity assessment. Statistical Tests: Multilinear regressions with sex and age as fixed factors. Spearman correlations calculated between variables. Benjamini–Hochberg procedure for false positives reduction (5% rate). A P < 0.05 significance level was used. Results: Significant age‐related increases were found for BMI (ρAge = 0.04), HSnorm (ρAge = −0.01), PDE/ATP (ρAge = 2.8 × 10−3), Pi/ATP (ρAge = 2.0 × 10−3), Pi/PCr (ρAge = 0.3 × 10−3), T2‐H2O‐MRS (ρAge = 0.051 msec), FFMRS (ρAge = 0.036) the intermediate T2‐H2O‐CPMG component time (ρAge = 0.112 msec), and fraction (ρAge = −0.3 × 10−3); and in both compartments for FFMRI (ρAge = 0.06, PC; ρAge = 0.06, AC), T2‐H2O‐MRI (ρAge = 0.05, PC; ρAge = 0.05, AC; msec), ΔT2‐H2O‐MRI (ρAge = 0.02, PC; ρAge = 0.02, AC; msec), T1‐H2O (ρAge = 1.08, PC; ρAge = 1.06, AC; msec), and ΔT1‐H2O (ρAge = 0.22, PC; ρAge = 0.37, AC; msec). The best age predictors, accounting for sex‐related differences, were HSnorm (R2 = 0.52) and PDE/ATP (R2 = 0.44). In both leg compartments, the imaging measures and HSnorm were intercorrelated. In PC, T2‐H2O‐MRS and FFMRS also showed numerous correlations to the imaging measures. PDE/ATP correlated to T1‐H2O, T2‐H2O‐MRI, ΔT2‐H2O‐MRI, FFMRI, FFMRS, the intermediate T2‐H2O‐CPMG, BMI, Pi/PCr, and HSnorm. Data Conclusion: Our multiparametric MRI approach provided an integrative view of age‐related changes in the leg and revealed multiple correlations between these parameters and the normalized HS. Level of Evidence: 1 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

BACKGROUND: Clinical, histopathological, and imaging variables have been associated with prognosis in patients with glioblastoma (GBM). We aimed to develop a multiparametric radiogenomic model incorporating MRI texture features, demographic data, and histopathological tumor biomarkers to predict prognosis in patients with GBM. METHODS: In this retrospective study, patients were included if they had confirmed diagnosis of GBM with histopathological biomarkers and pre-operative MRI. Tumor segmentation was performed, and texture features were extracted to develop a predictive radiomic model of survival (

Neurofibromatosis (NF) type I is a neuroectodermal and mesodermal dysplasia caused by a mutation of the neurofibromin tumor suppressor gene. Phenotypic features of NF1 vary, and patients develop benign peripheral nerve sheath tumors and malignant neoplasms, such as malignant peripheral nerve sheath tumor, malignant melanoma, and astrocytoma. Multiparametric whole-body MR imaging (WBMRI) plays a critical role in disease surveillance. Multiparametric MRI, typically used in prostate imaging, is a general term for a technique that includes multiple sequences, i.e. anatomic, diffusion, and Dixon-based pre- and post-contrast imaging. This article discusses the value of multiparametric WBMRI and illustrates the spectrum of whole-body lesions of NF1 in a single imaging setting. Examples of lesions include those in the skin (tumors and axillary freckling), soft tissues (benign and malignant peripheral nerve sheath tumors, visceral plexiform, and diffuse lesions), bone and joints (nutrient nerve lesions, non-ossifying fibromas, intra-articular neurofibroma, etc.), spine (acute-angled scoliosis, dural ectasia, intraspinal tumors, etc.), and brain/skull (optic nerve glioma, choroid plexus xanthogranuloma, sphenoid wing dysplasia, cerebral hamartomas, etc.). After reading this article, the reader will gain knowledge of the variety of lesions encountered with NF1 and their WBMRI appearances. Timely identification of such lesions can aid in accurate diagnosis and appropriate patient management. [ABSTRACT FROM AUTHOR]

Background and objective: High-resolution micro-ultrasound (microUS) is an advanced imaging tool. Our objective was to determine whether systematic microUS use for transrectal biopsy (TRBx) improves the detection rate for clinically significant prostate cancer (csPCa) in comparison to transperineal biopsy (TPBx) performed with magnetic resonance imaging (MRI)/conventional transrectal ultrasound (TRUS) fusion software. Methods: We retrospectively analyzed data for men who underwent prostate biopsies, including those on active surveillance (AS). TRBx was performed under microUS guidance, while MRI/TRUS fusion was consistently used to guide TPBx. Patients were matched according to propensity score matching (PSM). The primary endpoint was comparison of the csPCa detection rate with the two approaches. Secondary endpoints included predictors of csPCa (International Society of Urological Pathology grade group ≥2, assessed via multivariable logistic regression) and complication rates. Key findings and limitations: Overall, 1423 patients were enrolled. After applying PSM we identified an analytical cohort of 1094 men, 582 in the TRBx group and 512 in the TPBx group. There was no significant difference in the csPCa detection rate between the TRBx (45%) and TPBx (51%) groups (p = 0.07). Complications occurred in nine of 1094 patients (1%). On adjusted multivariable analysis, TPBx had a similar csPCa detection rate to TRBx (adjusted odds ratio [aOR] 1.26;p = 0.09). Predictors of csPCa detection were a positive family history (aOR 1.68; 95% confidence interval [CI] 1.20–2.35; p = 0.002); age (aOR 1.04, 95% CI 1.02–1.06; p

Background: Studies have shown that deep‐learning radiomics (DLR) could help differentiate glioblastoma (GBM) from solitary brain metastasis (SBM), but whether integrating demographic‐MRI and DLR features can more accurately distinguish GBM from SBM remains uncertain. Purpose: To construct and validate a demographic‐MRI deep‐learning radiomics nomogram (DDLRN) integrating demographic‐MRI and DLR signatures to differentiate GBM from SBM preoperatively. Study Type: Retrospective. Population: Two hundred and thirty‐five patients with GBM (N = 115) or SBM (N = 120), randomly divided into a training cohort (90 GBM and 98 SBM) and a validation cohort (25 GBM and 22 SBM). Field Strength/Sequence: Axial T2‐weighted fast spin‐echo sequence (T2WI), T2‐weighted fluid‐attenuated inversion recovery sequence (T2‐FLAIR), and contrast‐enhanced T1‐weighted spin‐echo sequence (CE‐T1WI) using 1.5‐T and 3.0‐T scanners. Assessment: The demographic‐MRI signature was constructed with seven imaging features ("pool sign," "irregular ring sign," "regular ring sign," "intratumoral vessel sign," the ratio of the area of peritumoral edema to the enhanced tumor, the ratio of the lesion area on T2‐FLAIR to CE‐T1WI, and the tumor location) and demographic factors (age and sex). Based on multiparametric MRI, radiomics and deep‐learning (DL) models, DLR signature, and DDLRN were developed and validated. Statistical Tests: The Mann–Whitney U test, Pearson test, least absolute shrinkage and selection operator, and support vector machine algorithm were applied for feature selection and construction of radiomics and DL models. Results: DDLRN showed the best performance in differentiating GBM from SBM with area under the curves (AUCs) of 0.999 and 0.947 in the training and validation cohorts, respectively. Additionally, the DLR signature (AUC = 0.938) outperformed the radiomics and DL models, and the demographic‐MRI signature (AUC = 0.775) was comparable to the T2‐FLAIR radiomics and DL models in the validation cohort (AUC = 0.762 and 0.749, respectively). Data Conclusion: DDLRN integrating demographic‐MRI and DLR signatures showed excellent performance in differentiating GBM from SBM. Level of Evidence: 3 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

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Simple Summary: In our retrospective study at a tertiary centre, we reviewed the use of contrast-enhanced ultrasound (CEUS) and strain elastography (SE) as adjuncts to conventional greyscale and colour Doppler US (CDUS) for evaluating focal testicular abnormalities over a decade. This study highlights the potential of advanced ultrasound techniques to provide deeper insights into the characteristics of testicular abnormalities. In particular, we observed that contrast-enhanced ultrasound could detect vascular enhancement in all malignant cases, even those not identified by conventional CDUS, and more conclusively confirm benignity. While SE alone offered no distinctive advantage, incorporating a combination of CEUS and SE into the evaluation of focal testicular abnormalities improved diagnostic performance metrics over conventional CDUS. Our research underscores the enhanced performance achieved by utilising these advanced ultrasound techniques. The comprehensive diagnostic assessment provided by these techniques could facilitate a shift towards more conservative management of testicular lesions, supporting the preference for organ-preserving methods over more radical surgeries. Conventional ultrasonography (US), including greyscale imaging and colour Doppler US (CDUS), is pivotal for diagnosing scrotal pathologies, but it has limited specificity. Historically, solid focal testicular abnormalities often led to radical orchidectomy. This retrospective study evaluated the utilisation of contrast-enhanced ultrasound (CEUS) and strain elastography (SE) in investigating intratesticular focal abnormalities. A total of 124 cases were analysed. This study underscored the superior diagnostic capabilities of CEUS in detecting vascular enhancement in all malignant cases, even those with undetectable vascularity by CDUS. It also highlighted the potential of CEUS in identifying distinctive vascular patterns in benign vascular tumours. Definitive confirmation of benignity could be obtained when the absence of enhancement was demonstrated on CEUS. While SE alone offered no distinctive advantage in differentiating between benign and malignant pathologies, we demonstrated that incorporating a combination of CEUS and SE into the evaluation of focal testicular abnormalities could improve diagnostic performance metrics over conventional CDUS. Our findings underscore the role of advanced ultrasound techniques in enhancing the evaluation of focal testicular abnormalities in clinical practice and could aid a shift towards testis-sparing management strategies. [ABSTRACT FROM AUTHOR]

Purpose: There is not yet satisfactory performance data comparing multiparametric MRI (mpMRI) versus biparametric MRI (bpMRI) for detecting prostate cancer (PCa), particularly in high-risk populations. We compared both protocols for detecting overall PCa and clinically significant PCa (CS-PCa; defined as Grade Group ≥ 2) in a multiethnic urban population. Methods: We retrospectively reviewed electronic medical record data from men who underwent image-guided fusion prostate biopsy (FB) between 2016 and 2021 at our institution. Patient characteristics, Prostate Imaging Reporting and Data System (PI-RADS) scores, and FB outcomes were analyzed based on MRI protocol. Multivariate mixed-effects logistic regression models were used to examine associations of bpMRI versus mpMRI for detecting overall PCa and CS-PCa in targeted lesions, among all patients and stratified by race/ethnicity. Results: Overall, 566 men (44.0% Non-Hispanic Black [NHB]; 27.0% Hispanic) with 975 PI-RADS 3–5 lesions on MRI underwent FB. Of these, 312 (55%) men with 497 lesions underwent mpMRI and 254 (45%) men with 478 lesions underwent bpMRI. On multivariate analyses among all men, the odds of detecting overall PCa (OR = 1.18, 95% CI: 1.05–3.11, p = 0.031) and CS-PCa (OR = 2.15, 95% CI: 1.16–4.00, p = 0.014) on FB were higher for lesions identified on bpMRI than mpMRI. When stratified by race/ethnicity, the odds of detecting overall PCa (OR = 1.86; p = 0.15) and CS-PCa (OR = 2.20; p = 0.06) were not statistically different between lesions detected on bpMRI or mpMRI. Conclusion: BpMRI has similar diagnostic performance to mpMRI in detecting overall and CS-PCa within a racially/ethnically diverse population. BpMRI can be utilized for evaluating suspected CS-PCa among NHB and Hispanic men. [ABSTRACT FROM AUTHOR]

This paper presents the design and implementation of an efficient multiparametric recommender engine for low-power applications with incremental post-processor optimizations. The need for this work arises from the increasing demand for energy-efficient recommender systems that can provide accurate recommendations with low energy consumption and delay levels. To address this need, we propose a novel approach that combines the use of Fourier, Cosine, LSTM, GRU, Wavelet, and Gabor features for the representation of collected network datasets& samples. These features are processed using low-power recurrent neural networks (LP RNN) to reduce energy consumption and delay levels. To further improve the accuracy and efficiency of the recommender engine, we apply an augmented post-evaluation Q-learning process. Our proposed method is compared with existing models, and we demonstrate its superior performance in terms of accuracy, precision, recall, energy consumption, and delay levels. Experimental results on multiple datasets and samples show that our proposed approach achieves an accuracy of 98.9%, precision of 97.5%, and recall of 98.3% while consuming less energy and incurring lower delay compared to existing models. Overall, our proposed multiparametric recommender engine provides an efficient and effective solution for low-power applications that require accurate recommendations for data patterns. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) can detect disease recurrence after focal therapy for prostate cancer, but there is no robust guidance regarding its use. The TARGET consensus recommendations provide guidance on the acquisition, interpretation, and reporting of MRI after focal therapy, as well as minimum standards for study reporting. Magnetic resonance imaging (MRI) can detect recurrences after focal therapy for prostate cancer but there is no robust guidance regarding its use. Our objective was to produce consensus recommendations on MRI acquisition, interpretation, and reporting after focal therapy. A systematic review was performed in July 2022 to develop consensus statements. A two-round consensus exercise was then performed, with a consensus meeting in January 2023, during which 329 statements were scored by 23 panellists from Europe and North America spanning urology, radiology, and pathology with experience across eight focal therapy modalities. Using RAND Corporation/University of California-Los Angeles methodology, the Transatlantic Recommendations for Prostate Gland Evaluation with MRI after Focal Therapy (TARGET) were based on consensus for statements scored with agreement or disagreement. In total, 73 studies were included in the review. All 20 studies (100%) reporting suspicious imaging features cited focal contrast enhancement as suspicious for cancer recurrence. Of 31 studies reporting MRI assessment criteria, the Prostate Imaging-Reporting and Data System (PI-RADS) score was the scheme used most often (20 studies; 65%), followed by a 5-point Likert score (six studies; 19%). For the consensus exercise, consensus for statements scored with agreement or disagreement increased from 227 of 295 statements (76.9%) in round one to 270 of 329 statements (82.1%) in round two. Key recommendations include performing routine MRI at 12 mo using a multiparametric protocol compliant with PI-RADS version 2.1 standards. PI-RADS category scores for assessing recurrence within the ablation zone should be avoided. An alternative 5-point scoring system is presented that includes a major dynamic contrast enhancement (DCE) sequence and joint minor diffusion-weighted imaging and T2-weighted sequences. For the DCE sequence, focal nodular strong early enhancement was the most suspicious imaging finding. A structured minimum reporting data set and minimum reporting standards for studies detailing MRI data after focal therapy are presented. The TARGET consensus recommendations may improve MRI acquisition, interpretation, and reporting after focal therapy for prostate cancer and provide minimum standards for study reporting. Magnetic resonance imaging (MRI) scans can detect recurrent of prostate cancer after focal treatments, but there is a lack of guidance on MRI use for this purpose. We report new expert recommendations that may improve practice. [ABSTRACT FROM AUTHOR]

To investigate the predictive value of the pre-treatment diffusion parameters of diffusion-weighted magnetic resonance imaging (DW-MRI) using artificial intelligence (AI) for prostate-specific antigen (PSA) response in patients with low- and intermediate-risk prostate cancer (PCa) treated with stereotactic ablative radiotherapy (SABR). Retrospective evaluation was performed for 30 patients using pre-treatment multi-parametric MR image datasets between 2017 and 2021. MR-based mean- and minimum apparent diffusion coefficients (ADC mean , ADC min) were calculated for the intraprostatic dominant lesion. Therapeutic response was assessed using PSA levels. Predictive performance was assessed by the receiver operating characteristic (ROC) analysis. Statistics performed with a significance level of p ≤ 0.05. No biochemical relapse was detected after a median follow-up of twenty-three months (range: 3–50), with a median PSA of 0.01 ng/ml (range: 0.006–2.8) at the last examination. Significant differences were observed between the pre-treatment ADC mean , ADC min parameters, and the group averages of patients with low and high 1-year-PSA measurements (p < 0.0001, p < 0.0001). In prediction, the random forest (RF) model outperformed the decision tree (DT) and support vector machine (SVM) models by yielding area under the curves (AUC), with 0.722, 0.685, and 0.5, respectively. Our findings suggest that pre-treatment MR diffusion data may predict therapeutic response using the novel approach of machine learning in PCa patients treated with SABR. Clinicians shall measure and implement the evaluation of the suggested parameters (ADC min , ADC mean) to provide the most accurate therapy for the patient. [ABSTRACT FROM AUTHOR]

Background: MRI can provide information on kidney structure, perfusion, and oxygenation. Furthermore, it allows for the assessment of kidney sodium concentrations and handling, allowing multiparametric evaluation of kidney physiology. Multiparametric MRI is promising for establishing prognosis and monitoring treatment responses in kidney diseases, but its intraindividual variation during the day is unresolved. Purpose: To investigate the variation in multiparametric MRI measurements from the morning to the evening. Study Type: Prospective. Population: Ten healthy volunteers, aged 29 ± 5 without history of kidney disease. Field Strength/Sequence: 3 T/T1 mapping, blood‐oxygen level dependent imaging, arterial spin labeling perfusion imaging, diffusion weighted imaging, and sodium imaging. Assessment: A multiparametric MRI protocol, yielding T1, R2*, ADC, renal blood flow and renal sodium levels, was acquired in the morning, noon, and evening. The participants were fasting prior to the first examination. Urine biochemical analyses were performed to complement MRI data. The cortex and medulla were analyzed separately in a semi‐automatic fashion, and gradients of total sodium concentration (TSC) and R2* gradients were calculated from outer cortex to inner medulla. Statistical Test: Analyses of variance and mixed‐effects models to estimate differences from time of day. Coefficients of variation to assess variability within and between participants. A P‐value <0.05 was considered statistically significant. Results: The coefficients of variation varied from 5% to 18% for proton‐based parametric sequences, while it was 38% for TSC over a day. Data Conclusion: Multiparametric MRI is stable over the day. The coefficients of variation over a day were lower for proton multiparametric MRI, but higher for sodium MRI. Evidence Level: 2 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

With increasing spatial resolution, diffusion-weighted imaging (DWI) may be suitable for morphologic lesion characterization in breast MRI – an area that has traditionally been occupied by dynamic contrast-enhanced imaging (DCE). This investigation compared DWI with b values of 800 and 1600 s/mm2 to DCE for lesion morphology assessment in high-resolution breast MRI at 3 Tesla. Multiparametric breast MRI was performed in 91 patients with 93 histopathologically proven lesions (31 benign, 62 malignant). Two radiologists independently evaluated three datasets per patient (DWI b800 ; DWI b1600 ; DCE) and assessed lesion visibility and BIRADS morphology criteria. Diagnostic accuracy was compared among readers and datasets using Cochran's Q test and pairwise post-hoc McNemar tests. Bland-Altman analyses were conducted for lesion size comparisons. Discrimination of carcinomas was superior compared to benign findings in both DWI b800 and DWI b1600 (p < 0.001) with no b value-dependent difference. Similarly, assessability of mass lesions was better than of non-mass lesions, irrespective of b value (p < 0.001). Intra-reader reliability for the analysis of morphologic BIRADS criteria among DCE and DWI datasets was at least moderate (Fleiss κ ≥0.557), while at least substantial inter-reader agreement was ascertained over all assessed categories (κ ≥0.776). In pairwise Bland-Altman analyses, the measurement bias between DCE and DWI b800 was 0.7 mm, whereas the difference between DCE and DWI b1600 was 2.8 mm. DWI b1600 allowed for higher specificity than DCE (p = 0.007/0.062). DWI can be employed for reliable morphologic lesion characterization in high-resolution breast MRI. High b values increase diagnostic specificity, while lesion size assessment is more precise with standard 800 s/mm2 images. [ABSTRACT FROM AUTHOR]

Abstract Background Neoadjuvant chemotherapy (NAC) before radical cystectomy is standard of care in patients with muscle-invasive bladder cancer (MIBC). Response assessment after NAC is important but suboptimal using CT. We assessed MRI without vs. with intravenous contrast (biparametric [BP] vs. multiparametric [MP]) for identifying residual disease on cystectomy and explored its prognostic role. Methods Consecutive MIBC patients that underwent NAC, MRI, and cystectomy between January 2000–November 2022 were identified. Two radiologists reviewed BP-MRI (T2 + DWI) and MP-MRI (T2 + DWI + DCE) for residual tumor. Diagnostic performances were compared using receiver operating characteristic curve analysis. Kaplan-Meier curves and Cox proportional-hazards models were used to evaluate association with disease-free survival (DFS). Results 61 patients (36 men and 25 women; median age 65 years, interquartile range 59–72) were included. After NAC, no residual disease was detected on pathology in 19 (31.1%) patients. BP-MRI was more accurate than MP-MRI for detecting residual disease after NAC: area under the curve = 0.75 (95% confidence interval (CI), 0.62–0.85) vs. 0.58 (95% CI, 0.45–0.70; p = 0.043). Sensitivity were identical (65.1%; 95% CI, 49.1–79.0) but specificity was higher in BP-MRI compared with MP-MRI for determining residual disease: 77.8% (95% CI, 52.4–93.6) vs. 38.9% (95% CI, 17.3–64.3), respectively. Positive BP-MRI and residual disease on pathology were both associated with worse DFS: hazard ratio (HR) = 4.01 (95% CI, 1.70–9.46; p = 0.002) and HR = 5.13 (95% CI, 2.66–17.13; p = 0.008), respectively. Concordance between MRI and pathology results was significantly associated with DFS. Concordant positive (MRI+/pathology+) patients showed worse DFS than concordant negative (MRI-/pathology-) patients (HR = 8.75, 95% CI, 2.02–37.82; p = 0.004) and compared to the discordant group (MRI+/pathology- or MRI-/pathology+) with HR = 3.48 (95% CI, 1.39–8.71; p = 0.014). Conclusion BP-MRI was more accurate than MP-MRI for identifying residual disease after NAC. A negative BP-MRI was associated with better outcomes, providing complementary information to pathological assessment of cystectomy specimens.

Background: Preoperative identification of isocitrate dehydrogenase (IDH) mutation and 1p/19q codeletion status could help clinicians select the optimal therapy in patients with diffuse glioma. Although, the value of multimodal intersection was underutilized. Purpose: To evaluate the value of quantitative MRI biomarkers for the identification of IDH mutation and 1p/19q codeletion in adult patients with diffuse glioma. Study Type: Retrospective. Population: Two hundred sixteen adult diffuse gliomas with known genetic test results, divided into training (N = 130), test (N = 43), and validation (N = 43) groups. Sequence/Field Strength: Diffusion/perfusion‐weighted‐imaging sequences and multivoxel MR spectroscopy (MRS), all 3.0 T using three different scanners. Assessment: The apparent diffusion coefficient (ADC) and cerebral blood volume (CBV) of the core tumor were calculated to identify IDH‐mutant and 1p/19q‐codeleted statuses and to determine cut‐off values. ADC models were built based on the 30th percentile and lower, CBV models were built based on the 75th centile and higher (both in five centile steps). The optimal tumor region was defined and the metabolite concentrations of MRS voxels that overlapped with the ADC/CBV optimal region were calculated and added to the best‐performing diagnostic models. Statistical Tests: DeLong's test, diagnostic test, and decision curve analysis were performed. A P value <0.05 was considered to be statistically significant. Results: Almost all ADC models achieved good performance in identifying IDH mutation status, among which ADC_15th was the most valuable parameter (threshold = 1.186; Youden index = 0.734; AUC_train = 0.896). The differential power of CBV histogram metrics for predicting 1p/19q codeletion outperformed ADC histogram metrics, and the CBV_80th‐related model performed best (threshold = 1.435; Youden index = 0.458; AUC_train = 0.724). The AUCs of ADC_15th and CBV_80th models in the validation set were 0.857 and 0.733. These models tended to improve after incorporation of N‐acetylaspartate/total_creatine and glutamate‐plus‐glutamine/total_creatine, respectively. Data Conclusion: The intersection of ADC‐, CBV‐based histogram and MRS provide a reliable paradigm for identifying the key molecular markers in adult diffuse gliomas. Evidence Level: 3 Technical Efficacy: Stage 3 [ABSTRACT FROM AUTHOR]

Objective: To explore the value of multiparametric magnetic resonance imaging (MRI) radiomics in the preoperative prediction of isocitrate dehydrogenase (IDH) genotype for gliomas Methods: The preoperative routine MRI sequences of 114 patients with pathologically confirmed grade II-IV gliomas were retrospectively analysed. All patients were randomly divided into training cohort(n=79) and validation cohort (n=35) in the ratio of 7:3. After feature extraction, we eliminated covariance by calculating the linear correlation coefficients between features, and then identified the best features using the F-test. The Logistic regression was used to build the radiomics model and the clinical model, and to build the combined model. Assessment of these models by subject operating characteristic (ROC) curves, area under the curve (AUC), sensitivity and specificity. Results: The multiparametric radiomics model was built by eight selected radiomics features and yielded AUC values of 0.974 and 0.872 in the training and validation cohorts, which outperformed the conventional models. After incorporating the clinical model, the combined model outperformed the radiomics model, with AUCs of 0.963 and 0.892 for the training and validation cohorts. Conclusion: Radiomic models based on multiparametric MRI sequences could help to predict glioma IDH genotype before surgery. [ABSTRACT FROM AUTHOR]

Background: Multiparametric renal Magnetic Resonance Imaging (MRI) provides a non-invasive method to assess kidney structure and function, but longitudinal studies are limited. Methods: A total of 22 patients with CKD category G3-4 (estimated glomerular filtration rate (eGFR) 15–59 mL/min/1.73 m2) were recruited. Annual 3T multiparametric renal MRI scans were performed, comprising total kidney volume (TKV), longitudinal relaxation time (T1), apparent diffusion coefficient (ADC), Arterial Spin Labelling, and Blood Oxygen Level Dependent relaxation time (T2*), with 15 patients completing a Year 2 scan. CKD progression over 2 years was defined as eGFR_slope ≥ −5 mL/min/1.73 m2/year. Results: At baseline, T1 was higher (cortex p = 0.05, medulla p = 0.03) and cortex perfusion lower (p = 0.015) in participants with subsequent progression versus stable eGFR. A significant decrease in TKV and ADC and an increase in cortex T1 occurred in progressors at Year 1 and Year 2, with a significant decrease in perfusion in progressors only at Year 2. The only decline in the stable group was a reduction in TKV. There was no significant change in cortex or medulla T2* at Year 1 or Year 2 for progressors or stable participants. Conclusion: Lower renal cortex perfusion and higher T1 in the cortex and medulla may predict CKD progression, while renal cortex T1, TKV, and ADC may be useful to monitor progression. This study provides pilot data for future large-scale studies. [ABSTRACT FROM AUTHOR]

Multidimensional Magnetic Resonance Imaging (MRI) is a versatile tool for microstructure mapping. We use a diffusion weighted inversion recovery spin echo (DW-IR-SE) sequence with spiral readouts at ultra-strong gradients to acquire a rich diffusion–relaxation data set with sensitivity to myelin water. We reconstruct 1D and 2D spectra with a two-step convex optimization approach and investigate a variety of multidimensional MRI methods, including 1D multi-component relaxometry, 1D multi-component diffusometry, 2D relaxation correlation imaging, and 2D diffusion-relaxation correlation spectroscopic imaging (DR-CSI), in terms of their potential to quantify tissue microstructure, including the myelin water fraction (MWF). We observe a distinct spectral peak that we attribute to myelin water in multi-component T1 relaxometry, T1-T2 correlation, T1-D correlation, and T2-D correlation imaging. Due to lower achievable echo times compared to diffusometry, MWF maps from relaxometry have higher quality. Whilst 1D multi-component T1 data allows much faster myelin mapping, 2D approaches could offer unique insights into tissue microstructure and especially myelin diffusion. [ABSTRACT FROM AUTHOR]

ObjectiveTo investigate the performance of multiparametric magnetic resonance imaging (MRI)—based radiomics models in differentiating early stage of cervical cancer (Stage I-IIa vs. IIb-IV).MethodsOne hundred patients with cervical cancer who underwent preoperative MRI between June 2020 and March 2022 were retrospectively enrolled. Training (n = 70) and testing cohorts (n = 30) were assigned by stratified random sampling. The clinical and pathological features, including age, histological subtypes, tumor grades, and node status, were compared between the two cohorts by t-test or chi-square test. Radiomics features were extracted from each volume of interest (VOI) on T2-weighted images (T2WI) and apparent diffusion coefficient (ADC) maps. The data balance of the training cohort was resampled by synthesizing minority oversampling techniques. Subsequently, the adiomics signatures were constructed by the least absolute shrinkage and selection operator algorithm and minimum-redundancy maximum-relevance with 10-fold cross-validation. Logistic regression was applied to predict the cervical cancer stages (low [I-IIa]) and (high [IIb–IV] FIGO stages). The receiver operating characteristic curve (area under the curve [AUC]) and decision curve analysis were used to assess the performance of the radiomics model.ResultsThe characteristics of age, histological subtypes, tumor grades, and node status were not significantly different between the low [I-IIa] and high [IIb–IV] FIGO stages (p > 0.05 for both the training and test cohorts). Three models based on T2WI, ADC maps, and the combined were developed based on six radiomics features from T2WI and three radiomics features from ADC maps, with AUCs of 0.855 (95% confidence interval [CI], 0.777–0.934) and 0.823 (95% CI, 0.727–0.919), 0.861 (95% CI, 0.785–0.936) and 0.81 (95% CI, 0.701–0.918), 0.934 (95% CI, 0.884–0.984) and 0.902 (95% CI, 0.832–0.972) in the training and test cohorts.ConclusionThe radiomics models combined T2W and ADC maps had good predictive performance in differentiating the early stage from locally advanced cervical cancer.

ABSTRACT: Background: The diagnosis of myocarditis by cardiovascular magnetic resonance (CMR) requires the use of T2 and T1 weighted imaging, ideally incorporating parametric mapping. Current two-dimensional (2D) mapping sequences are acquired sequentially and involve multiple breath-holds resulting in prolonged scan times and anisotropic image resolution. We developed an isotropic free-breathing three-dimensional (3D) whole-heart sequence that allows simultaneous T1 and T2 mapping and validated it in patients with suspected myocarditis. Methods: Eighteen healthy volunteers and 28 patients with suspected myocarditis underwent conventional 2D T1 and T2 mapping with whole-heart coverage and 3D joint T1/T2 mapping on a 1.5T scanner. Acquisition time, image quality, and diagnostic performance were compared. Qualitative analysis was performed using a 4-point Likert scale. Bland-Altman plots were used to assess the quantitative agreement between 2D and 3D sequences. Results: The 3D T1/T2 sequence was acquired in 8 min 26 s under free breathing, whereas 2D T1 and T2 sequences were acquired with breath-holds in 11 min 44 s (p = 0.0001). All 2D images were diagnostic. For 3D images, 89% (25/28) of T1 and 96% (27/28) of T2 images were diagnostic with no significant difference in the proportion of diagnostic images for the 3D and 2D T1 (p = 0.2482) and T2 maps (p = 1.0000). Systematic bias in T1 was noted with biases of 102, 115, and 152 ms for basal-apical segments, with a larger bias for higher T1 values. Good agreement between T2 values for 3D and 2D techniques was found (bias of 1.8, 3.9, and 3.6 ms for basal-apical segments). The sensitivity and specificity of the 3D sequence for diagnosing acute myocarditis were 74% (95% confidence interval [CI] 49%–91%) and 83% (36%–100%), respectively, with a c-statistic (95% CI) of 0.85 (0.79–0.91) and no statistically significant difference between the 2D and 3D sequences for the detection of acute myocarditis for T1 (p = 0.2207) or T2 (p = 1.0000). Conclusion: Free-breathing whole-heart 3D joint T1/T2 mapping was comparable to 2D mapping sequences with respect to diagnostic performance, but with the added advantages of free breathing and shorter scan times. Further work is required to address the bias noted at high T1 values, but this did not significantly impact diagnostic accuracy.

Simple Summary: Bladder cancer is the sixth most common cancer in the United States. The prognosis is excellent for localized forms, but the survival rates drop significantly when cancer invades the smooth muscle of the bladder. Imaging is essential for the accurate staging, prognosis, and assessment of therapeutic efficacy in bladder cancer and has the potential to guide personalized treatment strategies. Computed tomography has traditionally been the standard modality, but magnetic resonance imaging (MRI) is the emerging technique of choice for its superior soft tissue contrast without exposure to ionizing radiation. Multiparametric (mp)MRI provides physiological data interrogating the biology of the tumor, as well as high-resolution anatomical images. Advanced MRI techniques have enabled new imaging-based clinical endpoints, including novel scoring systems for tumor staging. Artificial intelligence (AI) holds the potential for the automated discovery of clinically relevant patterns in mpMRI images of the bladder. This review focuses on the principles, applications, and performance of mpMRI for bladder imaging. Quantitative imaging biomarkers (QIBs) derived from mpMRI are increasingly used in oncological applications, including tumor staging, prognosis, and assessment of treatment response. To standardize mpMRI acquisition and interpretation, an expert panel developed the Vesical Imaging–Reporting and Data System (VI-RADS). Many studies confirm the standardization and high degree of inter-reader agreement to discriminate muscle invasiveness in bladder cancer, supporting VI-RADS implementation in routine clinical practice. The standard MRI sequences for VI-RADS scoring are anatomical imaging, including T2w images, and physiological imaging with diffusion-weighted MRI (DW-MRI) and dynamic contrast-enhanced MRI (DCE-MRI). Physiological QIBs derived from analysis of DW- and DCE-MRI data and radiomic image features extracted from mpMRI images play an important role in bladder cancer. The current development of AI tools for analyzing mpMRI data and their potential impact on bladder imaging are surveyed. AI architectures are often implemented based on convolutional neural networks (CNNs), focusing on narrow/specific tasks. The application of AI can substantially impact bladder imaging clinical workflows; for example, manual tumor segmentation, which demands high time commitment and has inter-reader variability, can be replaced by an autosegmentation tool. The use of mpMRI and AI is projected to drive the field toward the personalized management of bladder cancer patients. [ABSTRACT FROM AUTHOR]

The molecular heterogeneity of extracellular vesicles (EVs) and the co-isolation of physically similar particles, such as lipoproteins (LPs), confounds and limits the sensitivity of EV bulk biomarker characterization. Herein, we present a single-EV and particle (siEVP) protein and RNA assay (siEVPPRA) to simultaneously detectmRNAs, miRNAs, and proteins in subpopulations of EVs and LPs. The siEVPPRA immobilizes and sorts particles via positive immunoselection onto micropatterns and focuses biomolecular signals in situ. By detecting EVPs at a single-particle resolution, the siEVPPRA outperformed the sensitivities of bulk-analysis benchmark assays for RNA and protein. To assess the specificity of RNA detection in complex biofluids, EVs from various glioma cell lines were processed with small RNA sequencing, whereby two mRNAs and two miRNAs associated with glioblastoma multiforme (GBM) were chosen for cross-validation. Despite the presence of single-EV-LP co-isolates in serum, the siEVPPRA detected GBM-associated vesicular RNA profiles in GBM patient siEVPs. The siEVPPRA effectively examines intravesicular, intervesicular, and interparticle heterogeneity with diagnostic promise. [ABSTRACT FROM AUTHOR]

The effect of high contrast on the multiscale behaviour of elastic laminates is studied. Mathematical modelling in this area is of significant interest for a variety of modern applications, including but not limited to advanced sandwich structures and photovoltaic panels. As an example, the antiplane shear of a symmetric, three-layered plate is considered. The problem parameters expressing relative thickness, stiffness and density are assumed to be independent. The high contrast may generally support extra length and time scales corresponding to degenerated boundary layers and propagating long-wave low-frequency vibration modes. The main focus is on the relation between these two phenomena. The developed multiparametric approach demonstrates that those do not always appear simultaneously. The associated explicit estimates on contrast parameters are established. In addition, the recent asymptotic extension of the classical Saint-Venant's principle is adapted for calculating the contribution of the degenerate boundary layer or long-wave low-frequency propagation mode. The peculiarity of the limiting absorption principle in application to layered media is also addressed. [ABSTRACT FROM AUTHOR]

Optimizing the functional status of patients of any age is a major global public health goal. Rehabilitation is a process in which a person with disabilities is accompanied to achieve the best possible physical, functional, social, intellectual, and relational outcomes. The Intermediate Care Unit within the O.U. of Geriatrics and Gerontology of the San Martino Hospital in Genoa is focused on the treatment and motor reactivation of patients with geriatric pathologies. The objective of this study was to identify which factor, among the characteristics related to the patient and those identified by the geriatric evaluation, had the greatest impact on rehabilitation outcomes. Our findings revealed significant correlations between the Barthel Index delta, the 4AT Screening Test, and the number of drugs taken. This association highlights the potential benefits of medication management in enhancing the overall well-being and functional abilities of frail older adults, despite the literature suggesting that polypharmacotherapy is associated with a reduction in functional status and an increase in mortality. These findings underscore the significance of a multidimensional geriatric assessment. Refining and optimising these multidisciplinary approaches is the objective of a more effective geriatric rehabilitation strategy. [ABSTRACT FROM AUTHOR]

Magnetic resonance imaging (MRI) has shown a great potential in the evaluation and management of prostate cancer. In this study, we would like to evaluate the benefit of multiparametric MRI in the detection and localization of prostate cancer by comparing it with the gold standard of histopathology from radical prostatectomy. In this single-centre prospective study, 90 consecutive patients underwent radical prostatectomy from November 2016 to May 2018. All patients first underwent multiparametric (mp)-MRI, and all suspicious regions of interest were delineated and recorded on a 5-point scale as defined in prostate imaging reporting and data system version 2 (PI-RADS V2) score. All radical prostatectomy specimens, acquired after robotic radical prostatectomy with extended pelvic lymphadenectomy, were sent for histopathological examination (HPE). The mean age of the 90 patients was 65.3 years, and the mean serum prostate-specific antigen (PSA) was 16.9 ng/ml. The sensitivity and specificity of mp-MRI in the detection of the corresponding region of interest (ROI) on HPE were 67.4% and 89.3% respectively. Positive predictive value (PPV), negative predictive value (NPV), and accuracy of mp-MRI in the detection of corresponding ROI on HPE were 86.3%, 73.3%, and 78.3% respectively. The mp-MRI detected 96.8% solitary lesions and 61.7% multifocal lesions on the corresponding ROI on HPE. Multiparametric MRI has an excellent specificity and reasonable sensitivity for the diagnosis of prostate cancer. It is a good modality for the detection of solitary tumours, higher-grade tumours, detection of seminal vesicle invasion and extracapsular extension and helps in the decision-making process before radical prostatectomy, focal therapy or selecting an appropriate candidate for active surveillance. [ABSTRACT FROM AUTHOR]

Abstract Background Breast cancer is the most frequent cancer in women and remains the second leading cause of death in Western countries. It represents a heterogeneous group of diseases with diverse tumoral behaviour, treatment responsiveness and prognosis. While major progress in diagnosis and treatment has resulted in a decline in breast cancer-related mortality, some patients will relapse and prognosis in this cohort of patients remains poor. Treatment is determined according to tumor subtype; primarily hormone receptor status and HER2 expression. Menopausal status and site of disease relapse are also important considerations in treatment protocols. Main body Staging and repeated evaluation of patients with metastatic breast cancer are central to the accurate assessment of disease extent at diagnosis and during treatment; guiding ongoing clinical management. Advances have been made in the diagnostic and therapeutic fields, particularly with new targeted therapies. In parallel, oncological imaging has evolved exponentially with the development of functional and anatomical imaging techniques. Consistent, reproducible and validated methods of assessing response to therapy is critical in effectively managing patients with metastatic breast cancer. Conclusion Major progress has been made in oncological imaging over the last few decades. Accurate disease assessment at diagnosis and during treatment is important in the management of metastatic breast cancer. CT (and BS if appropriate) is generally widely available, relatively cheap and sufficient in many cases. However, several additional imaging modalities are emerging and can be used as adjuncts, particularly in pregnancy or other diagnostically challenging cases. Nevertheless, no single imaging technique is without limitation. The authors have evaluated the vast array of imaging techniques – individual, combined parametric and multimodal - that are available or that are emerging in the management of metastatic breast cancer. This includes WB DW-MRI, CCA, novel PET breast cancer-epitope specific radiotracers and radiogenomics.

Abstract Background Bosniak classification improves sensitivity and specificity for malignancy among cystic renal masses characterized with MRI. The quantitative parameters derived from diffusion-weighted imaging, and contrast enhancement, can be used in distinguishing between benign and malignant cystic renal masses. Methods This prospective observational study included 58 patients (39 male and 19 female) with complicated cystic renal mass initially diagnosed by US or CT. All patients underwent multiparametric MRI study (Pre- and Post-Gd-enhanced T1WI, T2WI and DWI) by using 3 Tesla MRI scanner. Each cystic renal lesion was assigned a category based on Bosniak classification. Demographic data were recorded. ADC ratio, dynamic enhancement parameters in both corticomedullary and nephrographic phases as well as absolute washout were calculated and compared using ROC curve analysis. Results The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the multiparametric MRI in categorization of cystic renal masses according to Bosniak classification version 2019 were 90.32%, 100%, 100%, 90% and 94.83%, respectively, which was higher compared to biparametric MRI and conventional MRI. Conclusions Multiparametric MRI can be utilized to confidently evaluate cystic renal masses, overcoming the traditional limitations of overlapping morphological imaging features. Quantitative parameters derived from multiparametric MRI allow better evaluation of complex cystic renal tumors to distinguish between benign and malignant complex cystic renal lesions.

Background: Healthy articular cartilage presents structural gradients defined by distinct zonal patterns through the thickness, which may be disrupted in the pathogenesis of several disorders. Analysis of textural patterns using quantitative MRI data may identify structural gradients of healthy or degenerating tissue that correlate with early osteoarthritis (OA). Purpose: To quantify spatial gradients and patterns in MRI data, and to probe new candidate biomarkers for early severity of OA. Study Type: Retrospective study. Subjects: Fourteen volunteers receiving total knee replacement surgery (eight males/two females/four unknown, average age ± standard deviation: 68.1 ± 9.6 years) and 10 patients from the OA Initiative (OAI) with radiographic OA onset (two males/eight females, average age ± standard deviation: 57.7 ± 9.4 years; initial Kellgren‐Lawrence [KL] grade: 0; final KL grade: 3 over the 10‐year study). Field Strength/Sequence: 3.0‐T and 14.1‐T, biomechanics‐based displacement‐encoded imaging, fast spin echo, multi‐slice multi‐echo T2 mapping. Assessment: We studied structure and strain in cartilage explants from volunteers receiving total knee replacement, or structure in cartilage of OAI patients with progressive OA. We calculated spatial gradients of quantitative MRI measures (eg, T2) normal to the cartilage surface to enhance zonal variations. We compared gradient values against histologically OA severity, conventional relaxometry, and/or KL grades. Statistical Tests: Multiparametric linear regression for evaluation of the relationship between residuals of the mixed effects models and histologically determined OA severity scoring, with a significance threshold at α = 0.05. Results: Gradients of individual relaxometry and biomechanics measures significantly correlated with OA severity, outperforming conventional relaxometry and strain metrics. In human explants, analysis of spatial gradients provided the strongest relationship to OA severity (R2 = 0.627). Spatial gradients of T2 from OAI data identified variations in radiographic (KL Grade 2) OA severity in single subjects, while conventional T2 alone did not. Data Conclusion: Spatial gradients of quantitative MRI data may improve the predictive power of noninvasive imaging for early‐stage degeneration. Evidence Level: 1 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

Resistance of high grade tumors to treatment involves cancer stem cell features, deregulated cell division, acceleration of genomic errors, and emergence of cellular variants that rely upon diverse signaling pathways. This heterogeneous tumor landscape limits the utility of the focal sampling provided by invasive biopsy when designing strategies for targeted therapies. In this roadmap review paper, we propose and develop methods for enabling mapping of cellular and molecular features in vivo to inform and optimize cancer treatment strategies in the brain. This approach leverages (1) the spatial and temporal advantages of in vivo imaging compared with surgical biopsy, (2) the rapid expansion of meaningful anatomical and functional magnetic resonance signals, (3) widespread access to cellular and molecular information enabled by next-generation sequencing, and (4) the enhanced accuracy and computational efficiency of deep learning techniques. As multiple cellular variants may be present within volumes below the resolution of imaging, we describe a mapping process to decode micro- and even nano-scale properties from the macro-scale data by simultaneously utilizing complimentary multiparametric image signals acquired in routine clinical practice. We outline design protocols for future research efforts that marry revolutionary bioinformation technologies, growing access to increased computational capability, and powerful statistical classification techniques to guide rational treatment selection. [ABSTRACT FROM AUTHOR]

The research has the objective of analyzing some characteristics of the family dynamics of the students of Agricultural Mechanical Engineering of the Chapingo Autonomous University, to strengthen their formative process through the tutorial action program. Tutoring as accompaniment manages individualized actions that result in the training of students from different areas of intervention. The research is descriptive, cross-sectional and quantitative. The sample consisted of 244 fourth, fifth, and sixth grade students of said career, with an average age of 20.27 years, intentionally selected through non-probabilistic sampling. The instrument used was the Turborienta multiparametric psychometric test that evaluated 160 factors and was applied online. Among the main findings, the following are indicated as strengths: family harmony, harmony with the father, harmony with the mother, parental protection of their child and relationship with siblings; while the areas of opportunity are: respect received from the father and mother, motivational support for the child and a tendency to argue. It is recommended the incorporation of various strategies to the tutorials in order to improve the family dynamics of these students. [ABSTRACT FROM AUTHOR]

Purpose of Review: This article aims to provide an updated overview of the indications for diagnostic breast magnetic resonance imaging (MRI), discusses the available and novel imaging exams proposed for breast cancer detection, and discusses considerations when performing breast MRI in the clinical setting. Recent Findings: Breast MRI is superior in identifying lesions in women with a very high risk of breast cancer or average risk with dense breasts. Moreover, the application of breast MRI has benefits in numerous other clinical cases as well; e.g., the assessment of the extent of disease, evaluation of response to neoadjuvant therapy (NAT), evaluation of lymph nodes and primary occult tumor, evaluation of lesions suspicious of Paget's disease, and suspicious discharge and breast implants. Summary: Breast cancer is the most frequently detected tumor among women around the globe and is often diagnosed as a result of abnormal findings on mammography. Although effective multimodal therapies significantly decline mortality rates, breast cancer remains one of the leading causes of cancer death. A proactive approach to identifying suspicious breast lesions at early stages can enhance the efficacy of anti-cancer treatments, improve patient recovery, and significantly improve long-term survival. However, the currently applied mammography to detect breast cancer has its limitations. High false-positive and false-negative rates are observed in women with dense breasts. Since approximately half of the screening population comprises women with dense breasts, mammography is often incorrectly used. The application of breast MRI should significantly impact the correct cases of breast abnormality detection in women. Radiomics provides valuable data obtained from breast MRI, further improving breast cancer diagnosis. Introducing these constantly evolving algorithms in clinical practice will lead to the right breast detection tool, optimized surveillance program, and individualized breast cancer treatment. [ABSTRACT FROM AUTHOR]

Background: Bosniak classification improves sensitivity and specificity for malignancy among cystic renal masses characterized with MRI. The quantitative parameters derived from diffusion-weighted imaging, and contrast enhancement, can be used in distinguishing between benign and malignant cystic renal masses. Methods: This prospective observational study included 58 patients (39 male and 19 female) with complicated cystic renal mass initially diagnosed by US or CT. All patients underwent multiparametric MRI study (Pre- and Post-Gd-enhanced T1WI, T2WI and DWI) by using 3 Tesla MRI scanner. Each cystic renal lesion was assigned a category based on Bosniak classification. Demographic data were recorded. ADC ratio, dynamic enhancement parameters in both corticomedullary and nephrographic phases as well as absolute washout were calculated and compared using ROC curve analysis. Results: The sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy of the multiparametric MRI in categorization of cystic renal masses according to Bosniak classification version 2019 were 90.32%, 100%, 100%, 90% and 94.83%, respectively, which was higher compared to biparametric MRI and conventional MRI. Conclusions: Multiparametric MRI can be utilized to confidently evaluate cystic renal masses, overcoming the traditional limitations of overlapping morphological imaging features. Quantitative parameters derived from multiparametric MRI allow better evaluation of complex cystic renal tumors to distinguish between benign and malignant complex cystic renal lesions. [ABSTRACT FROM AUTHOR]

Background: Improved characterization of healthy muscle aging is needed to establish early biomarkers in age-related diseases., Purpose: To quantify age-related changes on multiple MRI and clinical variables evaluated in the same cohort and identify correlations among them., Study Type: Prospective., Population: 70 healthy subjects (30 men) from 20 to 81 years old., Field Strength/sequence: 3T/water T 2 (multiecho SE, multi-TE STEAM), water T 1 (GRE MR Fingerprinting), fat-fraction (multiecho GRE, multi-TE STEAM), carnosine (PRESS), multicomponent water T 2 (ISIS-CPMG SE train), and 31 P pulse-acquire spectroscopy., Assessment: Age- and sex-related changes on: Imaging: fat-fraction (FF MRI ), water T 1 (T 1-H2O ), and T 2 (T 2-H2O-MRI ) and their heterogeneities ΔT 1-H2O and ΔT 2-H2O-MRI in the posterior compartment (PC) and anterior compartment (AC) of the leg. 1 H spectroscopy: Carnosine concentration, pH, water T 2 components (T 2-H2O-CPMG ), fat-fraction (FF MRS ), and water T 2 (T 2-H2O-MRS ) in the gastrocnemius medialis. 31 P spectroscopy: Phosphodiesters (PDE), phosphomonoesters, inorganic phosphates (Pi), and phosphocreatine (PCr) normalized to adenosine triphosphate (ATP) and pH in the calf. Clinical evaluation: Body-mass index (BMI), gait speed (GS), plantar flexion strength, handgrip strength (HS), HS normalized to wrist circumference (HS norm ), physical activity assessment., Statistical Tests: Multilinear regressions with sex and age as fixed factors. Spearman correlations calculated between variables. Benjamini-Hochberg procedure for false positives reduction (5% rate). A P < 0.05 significance level was used., Results: Significant age-related increases were found for BMI (ρ Age  = 0.04), HS norm (ρ Age  = -0.01), PDE/ATP (ρ Age  = 2.8 × 10 -3 ), Pi/ATP (ρ Age  = 2.0 × 10 -3 ), Pi/PCr (ρ Age  = 0.3 × 10 -3 ), T 2-H2O-MRS (ρ Age  = 0.051 msec), FF MRS (ρ Age  = 0.036) the intermediate T 2-H2O-CPMG component time (ρ Age  = 0.112 msec), and fraction (ρ Age  = -0.3 × 10 -3 ); and in both compartments for FF MRI (ρ Age  = 0.06, PC; ρ Age  = 0.06, AC), T 2-H2O-MRI (ρ Age  = 0.05, PC; ρ Age  = 0.05, AC; msec), ΔT 2-H2O-MRI (ρ Age  = 0.02, PC; ρ Age  = 0.02, AC; msec), T 1-H2O (ρ Age  = 1.08, PC; ρ Age  = 1.06, AC; msec), and ΔT 1-H2O (ρ Age  = 0.22, PC; ρ Age  = 0.37, AC; msec). The best age predictors, accounting for sex-related differences, were HS norm (R 2  = 0.52) and PDE/ATP (R 2  = 0.44). In both leg compartments, the imaging measures and HS norm were intercorrelated. In PC, T 2-H2O-MRS and FF MRS also showed numerous correlations to the imaging measures. PDE/ATP correlated to T 1-H2O, T 2-H2O-MRI , ΔT 2-H2O-MRI , FF MRI , FF MRS , the intermediate T 2-H2O-CPMG , BMI, Pi/PCr, and HS norm ., Data Conclusion: Our multiparametric MRI approach provided an integrative view of age-related changes in the leg and revealed multiple correlations between these parameters and the normalized HS., Level of Evidence: 1 TECHNICAL EFFICACY: Stage 3., (© 2024 International Society for Magnetic Resonance in Medicine.)

Background: The primary aim of this study was to evaluate the individual and combined efficacy of magnetic resonance imaging (MRI) parameters, which include MRI perfusion, MRI diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) in the grading of gliomas as low grade versus high grade. The pre-operative imaging-based grading of gliomas by multiparametric MRI was compared with the gold standard histopathological studies. Methods: A total of 22 patients referred to the radiology department for multiparametric MRI of the brain with presumptive diagnosis of glioma on computed tomography/MRI were included in the study. Conventional T1, T2 and fluid-attenuated inversion recovery images were obtained followed by perfusion MRI using gadopentetate dimeglumine (Magnevist) administration. This was followed by DWI and MRS. Results: Our statistical analysis demonstrated that a cut-off of apparent diffusion coefficient value of 954.085 (10–6 mm2/Sec) provides a sensitivity and specificity of 87.5% and 85.7%, respectively, in differentiating low-grade gliomas (LGGs) from high-grade gliomas (HGGs). A choline/creatine ratio cut-off value of 2 provides sensitivity and specificity of 100% and 92.9%, respectively, while a cut-off value of 1.45 of choline/N-acetylaspartate ratio provides both sensitivity and specificity of 100% in differentiating LGG from HGG. A cut-off of 1.9 for maximum relative cerebral blood volume (rCBV) value provides both sensitivity and specificity of 100% in differentiating LGGs from HGGs. Conclusions: We concluded that perfusion MRI (rCBV) was the best parameter among perfusion MRI, DWI and MRI spectroscopy in differentiating HGGs from LGGs. Combined multiparametric results showed a diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value of 86.4%, 82.4%, 100%, 100% and 62.5%, respectively, on comparison with gold standard histopathological grading.

Background: Prostate cancer is the most frequently diagnosed cancer among men in over one-half of the countries of the world. Multi-parametric MRI is currently recognized as the best imaging method for assessment of cancer prostate. Aim of the Work: comparing the diagnostic accuracy of mpMRI and bpMRI, according to PI-RADS V2.1 using the histopathological results as the standard of reference. Patients and Methods: 41 suspected prostate cancer patients were enrolled in our study based on elevated PSA levels or abnormal digital rectal examination, underwent prostate MRI. Images were interpreted first without DCE-MRI sequence then DCE-MRI was included, and scores were recorded, once for bpMRI and once for mpMRI. Results: ROC curve analysis revealed that the AUC for the bpMRI and mpMRI protocols in diagnosing cancer prostate were 0.953 and 0.950 respectively and the difference was not statistically significant (P-value=0.875). Sensitivity, specificity and accuracy were calculated to reveal that when using PI-RADS score of ≥ 3 as a cut-off, bpMRI and mpMRI had exactly the same sensitivity, specificity, accuracy, PPV and NPV (100, 62.5, 85% respectively). When increasing the cut-off point of PI-RADS score to ≥ 4, the sensitivity of bpMRI decreased from 100 to 80, specificity increased from 62.5 to 93.75 yet, accuracy remained the same (85.4%). Whereas the sensitivity of mpMRI remained 100, specificity increased from 62.5 to 68.75 and accuracy increased from 85.4% to 87.8%. Conclusion: bpMRI without DCE-MRI sequence did not lead to significant differences in diagnostic accuracy when using PI-RADS V2.1. [ABSTRACT FROM AUTHOR]

Background: Administration of opioids to suppress pain plays a major role in modern anesthesia. Measuring depth of hypnosis and neuromuscular recovery are already well established, and devices for pain monitoring are available. Nonetheless pain monitoring is rare in clinical practice. Recently, the pain monitoring device PMD200 (Medasense Biometrics™ , Israel) was introduced. It non-invasively measures heart rate, heart rate variability, skin resistance, resistance variability, temperature and movement to calculate a nociception level (NoL) index. The NoL index range starts at zero, which is equivalent to being painless, and goes up to a value of 100. The validity and reliability of NoL monitoring is the content of current studies. Objective: We tested the hypothesis if the use of the PMD200 significantly reduces opioid consumption during da Vinci prostatectomy. Material and methods: A total of 50 male patients were included in this randomized, single blinded study. Exclusion criteria were arrhythmia because the pain monitoring device requires a sinus rhythm for reliable results. Patients received a weight-adjusted sufentanil bolus (0.3 µg/kg ideal body weight) during induction of anesthesia. Additionally, they received 10 µg of sufentanil before skin incision. Both groups received total intravenous anesthesia with propofol and continuous muscle relaxation through cis-atracurium. In the control group (CONT; n = 26), a standardized sufentanil bolus of 10 µg were administered by common criteria (heart rate/blood pressure increase, lacrimation, gut feeling) at the anesthesiologistʼs discretion. In the intervention group (INT; n = 24), patients received the standardized sufentanil bolus when the NoL index was above 25 for 2 min, which corresponds to the manufacturerʼs recommendation. The NoL index and bolus administrations were recorded for every patient. In the control group, the display of the pain monitor showing the NoL index was not visible for the anesthesiologist. Postoperatively, pain/nausea scores and piritramide consumption were taken every 10 min for 1h in the recovery room. None of the patients had prior chronic pain with long-term use of painkillers. Statistics were done using Mann-Whitney U‑test, Kolmogorov-Smirnov test and Levene test. Results: Sufentanil bolus administrations, normalized for duration of surgery, were not significantly lower in the intervention group (p = 0.065). We noticed a significant difference in variation of opioid administrations (p = 0.033). Sufentanil boluses per hour in the INT were normally distributed (p = 0.2), whereas in CONT they were not (p = 0.003). Postoperative data like nausea, opioid consumption and pain scale showed no differences between groups. Conclusion: The use of PMD200 did not significantly reduce cumulative opioid consumption. Following on we must reject the initial hypothesis. The difference in sufentanil bolus variances may point to an individualized antinociceptive therapy when NoL monitoring is used. We suppose patients with high opioid demands are detected and patients with low opioid demands did not receive unnecessary opioids. This assumption is only true if the PMD200 measures the entity pain. Further studies with more participants during surgery with higher tissue damage could lead to more convincing data and conclusions. [ABSTRACT FROM AUTHOR]

Background Multiparametric magnetic resonance imaging (mp-MRI) of urinary bladder (UB) is a novel imaging to predict detrusor muscle invasion in Bladder cancer (BC). The Vesical Imaging–Reporting and Data System (VI-RADS) was introduced in 2018 to standardize the reporting of BC with mp-MRI and to diagnose muscle invasion. This study was performed to evaluate the role of mp-MRI using VI-RADS to predict muscle invasive BC. Methods This prospective study was carried from June 2020 to May 2021 in a tertiary care institute. Thirty-six patients with untreated BC underwent mp-MRI followed by transuretheral resection of the tumor (TURBT). Mp-MRI findings were evaluated by two radiologists and BC was categorized according to VI-RADS scoring system. Resected tumors along with separate biopsy from the base were reported by two pathologists. Histopathological findings were compared with VI-RADS score and the performance of VI-RADS for determining detrusor muscle invasion was analyzed. Results VI-RADS scores of 4 and 5 were assigned to 9 (25%) and 15 (41.7%) cases, respectively, while 4 (13.3%) cases had VI-RADS score 3 on mp-MRI. VI-RADS 1 and 2 lesions were observed in six (16.7%) and two (5.5%) cases, respectively. On histopathology, 23 cases (63.9%) had muscle-invasive cancer and 13 cases (36.1%) had non–muscle-invasive cancer. The sensitivity and diagnostic accuracy of mp-MRI in predicting muscle invasive BC was 95.6 and 80.6%, respectively. Conclusion Mp-MRI has high sensitivity and diagnostic accuracy in predicting muscle invasive BC and should be advocated for evaluation of BC prior to surgery.

To develop a radiomic nomogram based on multiparametric magnetic resonance imaging for the preoperative prediction of lymph node metastasis (LNM) in rectal cancer. This retrospective study included 318 patients with pathologically proven rectal adenocarcinoma from two hospitals. Radiomic features were extracted from T2-weighted imaging, diffusion-weighted imaging, and contrast-enhanced T1-weighted imaging scans of the training cohort, and the radsore model was then constructed. The combined model was obtained by integrating the Radscore and clinical models. The area under the receiver operating characteristic curve (AUC) was used to assess the diagnostic effectiveness of each model, and the best-performing model was used to develop the nomogram. The Radscore and clinical models exhibited similar diagnostic efficacy (DeLong's test, P > 0.05). The AUC of the combined model was significantly higher than those of the clinical and Radscore models in the training cohort (AUC: 0.837 vs. 0.763 and 0.787, P : 0.02120 and 0.02309) and the external validation cohort (AUC: 0.880 vs. 0.797 and 0.779, P : 0.02310 and 0.02471). However, the diagnostic performance of the three models was comparable in the internal validation cohort (P > 0.05). Thus, among the three models, the combined model exhibited the highest diagnostic efficiency. The calibration curve exhibited satisfactory consistency between the nomogram predictions and the actual results. DCA confirmed the considerable clinical usefulness of the nomogram. The radiomics nomogram can accurately and noninvasively predict LNM in rectal cancer before surgery, serving as a convenient visualization tool for informing treatment decisions, including the choice of surgical approach and the need for neoadjuvant therapy. [ABSTRACT FROM AUTHOR]

Background We sought to develop a novel non-contrast multiparametric MRI (mpMRI) protocol employing several complementary techniques in a single scan session for a comprehensive functional and structural evaluation of diabetic kidney disease (DKD). Methods In the cross-sectional part of this prospective observational study, 38 subjects ages 18‒79 years with type 2 diabetes and DKD [estimated glomerular filtration rate (eGFR) 15‒60 mL/min/1.73 m2] and 20 age- and gender-matched healthy volunteers (HVs) underwent mpMRI. Repeat mpMRI was performed on 23 DKD subjects and 10 HVs. By measured GFR (mGFR), 2 DKD subjects had GFR stage G2, 16 stage G3 and 20 stage G4/G5. A wide range of MRI biomarkers associated with kidney haemodynamics, oxygenation and macro/microstructure were evaluated. Their optimal sensitivity, specificity and repeatability to differentiate diabetic versus healthy kidneys and categorize various stages of disease as well as their correlation with mGFR/albuminuria was assessed. Results Several MRI biomarkers differentiated diabetic from healthy kidneys and distinct GFR stages (G3 versus G4/G5); mean arterial flow (MAF) was the strongest predictor (sensitivity 0.94 and 1.0, specificity 1.00 and 0.69; P  = .04 and.004, respectively). Parameters significantly correlating with mGFR were specific measures of kidney haemodynamics, oxygenation, microstructure and macrostructure, with MAF being the strongest univariate predictor (r  = 0.92; P  < .0001). Conclusions A comprehensive and repeatable non-contrast mpMRI protocol was developed that, as a single, non-invasive tool, allows functional and structural assessment of DKD, which has the potential to provide valuable insights into underlying pathophysiology, disease progression and analysis of efficacy/mode of action of therapeutic interventions in DKD. [ABSTRACT FROM AUTHOR]

Background: The primary aim of this study was to evaluate the individual and combined efficacy of magnetic resonance imaging (MRI) parameters, which include MRI perfusion, MRI diffusion-weighted imaging (DWI) and magnetic resonance spectroscopy (MRS) in the grading of gliomas as low grade versus high grade. The pre-operative imaging-based grading of gliomas by multiparametric MRI was compared with the gold standard histopathological studies. Methods: A total of 22 patients referred to the radiology department for multiparametric MRI of the brain with presumptive diagnosis of glioma on computed tomography/MRI were included in the study. Conventional T1, T2 and fluid-attenuated inversion recovery images were obtained followed by perfusion MRI using gadopentetate dimeglumine (Magnevist) administration. This was followed by DWI and MRS. Results: Our statistical analysis demonstrated that a cut-off of apparent diffusion coefficient value of 954.085 (10-6 mm2/Sec) provides a sensitivity and specificity of 87.5% and 85.7%, respectively, in differentiating low-grade gliomas (LGGs) from high-grade gliomas (HGGs). A choline/creatine ratio cut-off value of 2 provides sensitivity and specificity of 100% and 92.9%, respectively, while a cut-off value of 1.45 of choline/N-acetylaspartate ratio provides both sensitivity and specificity of 100% in differentiating LGG from HGG. A cut-off of 1.9 for maximum relative cerebral blood volume (rCBV) value provides both sensitivity and specificity of 100% in differentiating LGGs from HGGs. Conclusions: We concluded that perfusion MRI (rCBV) was the best parameter among perfusion MRI, DWI and MRI spectroscopy in differentiating HGGs from LGGs. Combined multiparametric results showed a diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value of 86.4%, 82.4%, 100%, 100% and 62.5%, respectively, on comparison with gold standard histopathological grading. [ABSTRACT FROM AUTHOR]

Abstract Background MRI provides several distinct quantitative parameters that may better differentiate renal cell carcinoma (RCC) subtypes. The purpose of the study is to evaluate the diagnostic accuracy of apparent diffusion coefficient (ADC), chemical shift signal intensity index (SII), and contrast enhancement in differentiation between different subtypes of renal cell carcinoma. Results There were 63 RCC as regard surgical histopathological analysis: 43 clear cell (ccRCC), 12 papillary (pRCC), and 8 chromophobe (cbRCC). The mean ADC ratio for ccRCC (0.75 ± 0.13) was significantly higher than that of pRCC (0.46 ± 0.12, P < 0.001) and cbRCC (0.41 ± 0.15, P < 0.001). The mean ADC value for ccRCC (1.56 ± 0.27 × 10−3 mm2/s) was significantly higher than that of pRCC (0.96 ± 0.25 × 10−3 mm2/s, P < 0.001) and cbRCC (0.89 ± 0.29 × 10−3 mm2/s, P < 0.001). The mean SII of pRCC (1.49 ± 0.04) was significantly higher than that of ccRCC (0.93 ± 0.01, P < 0.001) and cbRCC (1.01 ± 0.16, P < 0.001). The ccRCC absolute corticomedullary enhancement (196.7 ± 81.6) was significantly greater than that of cbRCC (177.8 ± 77.7, P < 0.001) and pRCC (164.3 ± 84.6, P < 0.001). Conclusion Our study demonstrated that multiparametric MRI is able to afford some quantitative features such as ADC ratio, SII, and absolute corticomedullary enhancement which can be used to accurately distinguish different subtypes of renal cell carcinoma.

Purpose: To develop a novel simultaneous co‐registered T1, T2, T2∗, T1ρ, and fat fraction abdominal MR fingerprinting (MRF) approach for fully comprehensive liver‐tissue characterization in a single breath‐hold scan. Methods: A gradient‐echo liver MRF sequence with low fixed flip angle, multi‐echo radial readout, and varying magnetization preparation pulses for multiparametric encoding is performed at 1.5 T. The T2∗ and fat fraction are estimated from a graph/cut water/fat separation method using a six‐peak fat model. Water/fat singular images obtained are then matched to an MRF dictionary, estimating water‐specific T1, T2, and T1ρ. The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional sequences. Results: For the phantom studies, linear fits show excellent coefficients of determination (r2 > 0.9) for every parametric map. For in vivo studies, the average values measured within regions of interest drawn on liver, spleen, muscle, and fat are statistically different from the reference scans (p < 0.05) for T1, T2, and T1⍴ but not for T2∗ and fat fraction, whereas correlation between MRF and reference scans is excellent for each parameter (r2 > 0.92 for every parameter). Conclusion: The proposed multi‐echo inversion‐recovery, T2, and T1⍴ prepared liver MRF sequence presented in this work allows for quantitative T1, T2, T2∗, T1⍴, and fat fraction liver‐tissue characterization in a single breath‐hold scan of 18 seconds. The approach showed good agreement and correlation with respect to reference clinical maps. [ABSTRACT FROM AUTHOR]

Background: Biparametric (bp) magnetic resonance imaging (MRI) could be an alternative MRI for the detection of the clinically significant prostate cancer (csPCa). Purpose: To compare the accuracies of prostate cancer detection and localization between prebiopsy bpMRI and postbiopsy multiparametric MRI (mpMRI) taken on different days, using radical prostatectomy specimens as the reference standards. Material and methods: Data of 41 total consecutive patients who underwent the following examinations and procedures between September 2015 and March 2017 were collected: (1) magnetic resonance– and/or ultrasonography-guided biopsy after bpMRI; (2) postbiopsy mpMRI; and (3) radical prostatectomy with csPCa. Two radiologists scored suspected lesions on bpMRI and mpMRI independently using Prostate Imaging Reporting and Data System version 2. The diagnostic accuracy of detecting csPCa and the Dice similarity coefficient were obtained. Apparent diffusion coefficient (ADC) ratios were also obtained for quantitative comparison between bpMRI and mpMRI. Results: Diagnostic accuracies on bpMRI and mpMRI were 0.83 and 0.82 for reader 1; 0.80 and 0.82 for reader 2. There are no significantly different values of diagnostic sensitivities or specificities between the readers or between MRI protocols. Intra-observer Dice similarity coefficient was significantly lower in reader 2, compared to that in reader 1 between the two MRI protocols. The range of mean ADC ratio was 0.281–0.635. There was no statistically significant difference in the ADC ratio between bpMRI and mpMRI. Conclusions: Diagnostic performance of bpMRI without dynamic contrast enhancement MRI is not significantly different from mpMRI with dynamic contrast enhancement MRI in the detection of csPCa.

Abstract Background Preoperative staging of urinary bladder carcinomas using TNM system is crucial in the management of bladder cancer which is determined mainly by stage and grade of tumor at diagnosis. We aim to evaluate the diagnostic accuracy of multiparametric MRI (mp-MRI) for assessment of the bladder cancer T stage and histologic grade. Results The overall T2-WI diagnostic accuracy for the T stage was 72.3%, increased to be 87.1% for contrast-enhanced images, and 92.6% for DWI, reaching the maximum accuracy 94.5% using the combined multi-parametric MRI technique. Diagnostic accuracies of mp-MRI in differentiating superficial from muscle-invasive (91%) and organ-confined from non-organ confined tumors (92%) were superior to DW-MRI (89% and 87%), DCE-MRI (84% and 83%), and T2W-MRI (74% and 71%), respectively. The agreement between MRI findings and histopathological staging was greater in mp-MRI (k = 0.91; excellent agreement) than in DW-MRI (k = 0.77; moderate agreement), DCE-MRI (k = 0.76; substantial agreement), and T2W-MRI (k = 0.53; fair agreement). Conclusion Mp-MRI provides useful information for evaluating the local T stages of bladder cancer and can predict the histological grades of urinary bladder cancers with high diagnostic accuracy.