Magnetic Resonance Imaging Approach Research Articles

Sex differences in gray matter, white matter, and regional brain perfusion in young, healthy adults.

Cerebrovascular and neurological diseases exhibit sex-specific patterns in prevalence, severity, and regional specificity, some of which are associated with altered cerebral blood flow (CBF). Females often exhibit higher resting CBF, but understanding the impact of sex per se on CBF is hampered by study variability in age, comorbidities, medications, and control for menstrual cycle or hormone therapies. A majority of studies report whole brain CBF without differentiating between gray and white matter or without assessing regional CBF. Thus fundamental sex differences in regional or whole brain CBF remain unclarified. While controlling for the above confounders, we tested the hypothesis that females will exhibit higher total gray and white matter perfusion as well as regional gray matter perfusion. Adults 18-30 yr old (females = 22 and males = 26) were studied using arterial spin labeling (ASL) magnetic resonance imaging (MRI) scans followed by computational anatomy toolbox (CAT12) analysis in statistical parametric mapping (SPM12) to quantify CBF relative to brain volume. Females displayed 40% higher perfusion globally (females = 62 ± 9 and males = 45 ± 10 mL/100 g/min, P < 0.001), gray matter (females = 75 ± 11 and males = 54 ± 12 mL/100 g/min, P < 0.001), and white matter (females = 44 ± 6 and males = 32 ± 7 mL/100 g/min, P < 0.001). Females exhibited greater perfusion than males in 67 of the 68 regions tested, ranging from 14% to 66% higher. A second MRI approach (4-dimensional flow) focused on large arteries confirmed the sex difference in global CBF. These data indicate strikingly higher basal CBF in females at global, gray, and white matter levels and across dozens of brain regions and offer new clarity into fundamental sex differences in global and regional CBF regulation before aging or pathology.NEW & NOTEWORTHY MRI used to measure cerebral blood flow (CBF) in gray matter, white matter, and 68 regions in healthy men and women. This study demonstrated that CBF is 40% higher in women, the highest sex difference reported, when controlling for numerous important clinical confounders like age, smoking, menstrual cycle, comorbidities, and medications.

Prediction of early recurrence of adult-type diffuse gliomas following radiotherapy using multi-modal magnetic resonance images.

Adult-type diffuse gliomas are among the central nervous system's most aggressive malignant primary neoplasms. Despite advancements in systemic therapies and technological improvements in radiation oncology treatment delivery, the survival outcome for these patients remains poor. Fast and accurate assessment of tumor response to oncologic treatments is crucial, as it can enable the early detection of recurrent or refractory gliomas, thereby allowing timely intervention with life-prolonging salvage therapies. Radiomics is a developing field with great potential to improve medical image interpretation. This study aims to apply a radiomics-based predictive model for classifying response to radiotherapy within the first 3 months post-treatment. Ninety-five patients were selected from the Burdenko Glioblastoma Progression Dataset. Tumor regions were delineated in the axial plane on contrast-enhanced T1(CE T1W) and T2 fluid-attenuated inversion recovery (T2_FLAIR) magnetic resonance imaging (MRI). Hand-crafted radiomic (HCR) features, including first- and second-order features, were extracted using PyRadiomics (3.7.6) in Python (3.10). Then, recursive feature elimination with a random forest (RF) classifier was applied for feature dimensionality reduction. RF and support vector machine (SVM) classifiers were built to predict treatment outcomes using the selected features. Leave-one-out cross-validation was employed to tune hyperparameters and evaluate the models. For each segmented target, 186 HCR features were extracted from the MRI sequence. Using the top-ranked radiomic features from a combination of CE T1W and T2_FLAIR, an optimized classifier achieved the highest averaged area under the curve (AUC) of 0.829±0.075 using the RF classifier. The HCR features of CE T1W produced the worst outcomes among all models (0.603±0.024 and 0.615±0.075 for RF and SVM classifiers, respectively). We developed and evaluated a radiomics-based predictive model for early tumor response to radiotherapy, demonstrating excellent performance supported by high AUC values. This model, harnessing radiomic features from multi-modal MRI, showed superior predictive performance compared to single-modal MRI approaches. These results underscore the potential of radiomics in clinical decision support for this disease process.

Quantitative MRI approach in the preoperative evaluation of a rare large-mass abdominal GIST tumor

Gastrointestinal stromal tumors (GISTs) are rare cancers originating from the gastrointestinal tract's interstitial cells of Cajal. This study explores the utility of quantitative Magnetic Resonance Imaging (MRI), particularly volumetric lesion segmentation, in the preoperative evaluation of large-mass abdominal GISTs. MRI offers high-resolution imaging without ionizing radiation, which is crucial for oncology patients requiring repeated scans. Advanced semi-automatic segmentation techniques were employed in this study from different MRI sequences to enhance precision in tumor boundary delineation and volumetric analysis, and aid personalized surgical planning. In addition, this study demonstrates that using different clinical imaging protocols and comparing volumetric data from CT and various MRI sequences yields consistent results with minimal volumetric error. Finally, integrating MRI data into real-time surgical navigation systems underscored the synergy between radiology, surgical oncology, and computer science, improving tumor margin assessment and reducing recurrence risk. This approach highlights a pivotal shift towards technology-enhanced healthcare, promising better patient outcomes.

Ultrasound Versus Magnetic Resonance Imaging as First-Line Imaging Strategies for Rotator Cuff Pathologies: A Comprehensive Analysis of Clinical Practices, Economic Efficiency, and Future Perspectives.

Rotator cuff injuries are a prevalent cause of atraumatic chronic shoulder pain, imposing a significant healthcare burden. This articlereviews the clinical presentation, diagnostic imaging modalities, practice variations, and economic efficiency considerations in the evaluation of rotator cuff pathologies. Ultrasound (US) and magnetic resonance imaging (MRI) are the primary imaging methods for diagnosing rotator cuff injuries. US provides real-time visualization but has limited tissue penetration, while MRI offers detailed anatomical information but is not a dynamic process. Studies show that MRI is superior to US with higher sensitivity and specificity. MRI is the gold standard, particularly for surgical planning, but US remains relevant when MRI is not feasible. Both require standardized protocols for evaluating tear dimensions and muscle atrophy. With the operator-dependent nature of US, MRI offers a more comprehensive assessment of rotator cuff tears and predictive insights for clinical outcomes. Practice variations exist in the management of rotator cuff pathologies, with some countries favoring US as the primary imaging modality and others relying more on MRI. These variations are influenced by factors like resource availability and healthcare system nuances. In Australia, current guidelines lean towardconservative management, potentially leading to delayed diagnoses and increased costs. The United States often favors MRI, while Canada advocates for US as the initial choice. Economic considerations play a significant role in selecting imaging modalities. While US is cost-effective, it may necessitate subsequent MRI examinations, contributing to inefficiencies in the diagnostic process. Studies suggest that a combined approach of US and MRI is less efficient and cost-effective than MRI alone. However, the use of both modalities rather than MRI aloneis common in clinical practice, adding to healthcare expenses. In conclusion, the choice of imaging modality for rotator cuff pathologies should consider factors such as diagnostic efficacy, cost-effectiveness, and resource availability. Radiologists play a pivotal role in guiding this selection and ensuring comprehensive evaluations. Future considerations should include the revision of management guidelines and the potential inclusion of shoulder pathologies in healthcare coverage to optimize patient care and healthcare expenditure.

An Illustrated Scoping Review of the Magnetic Resonance Imaging Characteristics of Canine and Feline Brain Tumors.

Magnetic resonance imaging (MRI) is used pervasively in veterinary practice for the antemortem diagnosis of intracranial tumors. Here, we provide an illustrated summary of the published MRI features of primary and secondary intracranial tumors of dogs and cats, following PRISMA scoping review guidelines. The PubMed and Web of Science databases were searched for relevant records, and input from stakeholders was solicited to select data for extraction. Sixty-seven studies of moderate to low-level evidence quality describing the MRI features of pathologically confirmed canine and feline brain tumors met inclusion criteria. Considerable variability in data inclusion and reporting, as well as low case numbers, prohibited comparative data analyses. Available data support a holistic MRI approach incorporating lesion number, location within the brain, shape, intrinsic signal appearances on multiparametric sequences, patterns of contrast enhancement, and associated secondary changes in the brain to prioritize differential imaging diagnoses, and often allows for accurate presumptive diagnosis of common intracranial tumors. Quantitative MRI techniques show promise for improving discrimination of neoplastic from non-neoplastic brain lesions, as well as differentiating brain tumor types and grades, but sample size limitations will likely remain a significant practical obstacle to the design of robustly powered radiomic studies. For many brain tumor variants, particularly in cats, there remains a need for standardized studies that correlate clinicopathologic and neuroimaging data.

Machine Learning-Based Prediction of Glioma IDH Gene Mutation Status Using Physio-Metabolic MRI of Oxygen Metabolism and Neovascularization (A Bicenter Study).

The mutational status of the isocitrate dehydrogenase (IDH) gene plays a key role in the treatment of glioma patients because it is known to affect energy metabolism pathways relevant to glioma. Physio-metabolic magnetic resonance imaging (MRI) enables the non-invasive analysis of oxygen metabolism and tissue hypoxia as well as associated neovascularization and microvascular architecture. However, evaluating such complex neuroimaging data requires computational support. Traditional machine learning algorithms and simple deep learning models were trained with radiomic features from clinical MRI (cMRI) or physio-metabolic MRI data. A total of 215 patients (first center: 166 participants + 16 participants for independent internal testing of the algorithms versus second site: 33 participants for independent external testing) were enrolled using two different physio-metabolic MRI protocols. The algorithms trained with physio-metabolic data demonstrated the best classification performance in independent internal testing: precision, 91.7%; accuracy, 87.5%; area under the receiver operating curve (AUROC), 0.979. In external testing, traditional machine learning models trained with cMRI data exhibited the best IDH classification results: precision, 84.9%; accuracy, 81.8%; and AUROC, 0.879. The poor performance for the physio-metabolic MRI approach appears to be explainable by site-dependent differences in data acquisition methodologies. The physio-metabolic MRI approach potentially supports reliable classification of IDH gene status in the presurgical stage of glioma patients. However, non-standardized protocols limit the level of evidence and underlie the need for a reproducible framework of data acquisition techniques.

Whole-brain mapping of increased manganese levels in welders and its association with exposure and motor function

Although manganese (Mn) is a trace metal essential for humans, chronic exposure to Mn can cause accumulation of this metal ion in the brain leading to an increased risk of neurological and neurobehavioral health effects. This is a concern for welders exposed to Mn through welding fumes. While brain Mn accumulation in occupational settings has mostly been reported in the basal ganglia, several imaging studies also revealed elevated Mn in other brain areas. Since Mn functions as a magnetic resonance imaging (MRI) T1 contrast agent, we developed a whole-brain MRI approach to map in vivo Mn deposition differences in the brains of non-exposed factory controls and exposed welders. This is a cross-sectional analysis of 23 non-exposed factory controls and 36 exposed full-time welders from the same truck manufacturer. We collected high-resolution 3D MRIs of brain anatomy and R1 relaxation maps to identify regional differences using voxel-based quantification (VBQ) and statistical parametric mapping. Furthermore, we investigated the associations between excess Mn deposition and neuropsychological and motor test performance. Our results indicate that: (1) Using whole-brain MRI relaxometry methods we can generate excess Mn deposition maps in vivo, (2) excess Mn accumulation due to occupational exposure occurs beyond the basal ganglia in cortical areas associated with motor and cognitive functions, (3) Mn likely diffuses along white matter tracts in the brain, and (4) Mn deposition in specific brain regions is associated with exposure (cerebellum and frontal cortex) and motor metrics (cerebellum and hippocampus).

7 T Lesion-Attenuated Magnetization-Prepared Gradient Echo Acquisition for Detection of Posterior Fossa Demyelinating Lesions in Multiple Sclerosis.

Detection of infratentorial demyelinating lesions in multiple sclerosis (MS) presents a challenge in magnetic resonance imaging (MRI), a difficulty that is further heightened in 7 T MRI. This study aimed to assess the efficacy of a novel MRI approach, lesion-attenuated magnetization-prepared gradient echo acquisition (LAMA), for detecting demyelinating lesions within the posterior fossa and upper cervical spine on 7 T MRI and contrast its performance with conventional double-inversion recovery (DIR) and T2-weighted turbo spin echo sequences. We conducted a retrospective cross-sectional study in 42 patients with a confirmed diagnosis of MS. All patients had 7 T MRI that incorporated LAMA, 3D DIR, and 2D T2-weighted turbo spin echo sequences. Three readers assessed lesion count in the brainstem, cerebellum, and upper cervical spinal cord using both DIR and T2-weighted images in one session. In a separate session, LAMA was analyzed alone. Contrast-to-noise ratio was also compared between LAMA and the conventional sequences. Lesion counts between methods were assessed using nonparametric Wilcoxon signed rank test. Interrater agreement in lesion detection was estimated by intraclass correlation coefficients. LAMA identified a significantly greater number of lesions than DIR + T2 (mean 6.4 vs 3.0; P < 0.001). LAMA also exhibited better interrater agreement (intraclass correlation coefficient [95% confidence interval], 0.75 [0.41-0.88] vs 0.61 [0.35-0.78]). The contrast-to-noise ratio for LAMA (3.7 ± 0.9) significantly exceeded that of DIR (1.94 ± 0.7) and T2 (1.2 ± 0.7) (all P 's < 0.001). In cases with no lesions detected using DIR + T2, at least 1 lesion was identified in 83.3% with LAMA. Across all analyzed brain regions, LAMA consistently detected more lesions than DIR + T2. LAMA significantly improves the detection of infratentorial demyelinating lesions in MS patients compared with traditional methods. Integrating LAMA with standard magnetization-prepared 2 rapid acquisition gradient echo acquisition provides a valuable tool for accurately characterizing the extent of MS disease.

A Multi-Modality Magnetic Resonance Imaging Model for Predicting Traumatic Brain Injury Outcomes

Traumatic Brain Injury (TBI) is a heterogenous injury and a leading cause of long-term deficits and mortality in the United States. In order to improve TBI outcomes, an effective prognostication tool is necessary. Standard imaging modalities, computerized tomography (CT) and magnetic resonance imaging (MRI), have a limited ability to predict TBI outcomes. Currently, advanced MRI techniques are being studied for their efficacy. The aim of this study is to determine whether a multimodality MRI approach is superior to a single modality MRI approach in determining clinical outcomes of TBI. A secondary data analysis was conducted on TBI data obtained from 31 rat brains; 3-day MRI data in the Ipsilateral Perilesion Cortex and 28-day Behavioral Test data (Novel Object Recognition, Barnes Maze, and Open Field Test Total Distance and Total Act Time) were analyzed. A Best Subset Analysis was conducted for each of the behavioral tests. Three out of four behavioral tests show improved adjusted R2 values for models containing more than one imaging modality. A Multiple Linear Regression Analysis was then conducted on the MRIs from the highest predictive model determined by Best Subset Analysis. This analysis shows that a multimodality MRI approach can explain 25.2% of the variability in behavioral outcomes in the Novel Object Recognition Test with a P value of 0.012. Thus, the study demonstrates that a multi-modality MRI approach has a potential for effectively diagnosing and predicting TBI outcomes.

Advanced MRI Approaches for Evaluating Common Lower Extremity Injuries in Basketball Players: Current and Emerging Techniques.

Magnetic resonance imaging (MRI) can provide accurate and non-invasive diagnoses of lower extremity injuries in athletes. Sport-related injuries commonly occur in and around the knee and can affect the articular cartilage, patellar tendon, hamstring muscles, and bone. Sports medicine physicians utilize MRI to evaluate and diagnose injury, track recovery, estimate return to sport timelines, and assess the risk of recurrent injury. This article reviews the current literature and describes novel developments of quantitative MRI tools that can further advance our understanding of sports injury diagnosis, prevention, and treatment while minimizing injury risk and rehabilitation time. Innovative approaches for enhancing the early diagnosis and treatment of musculoskeletal injuries in basketball players span a spectrum of techniques. These encompass the utilization of T2, T1ρ, and T2* quantitative MRI, along with dGEMRIC and Na-MRI to assess articular cartilage injuries, 3D-Ultrashort echo time MRI for patellar tendon injuries, diffusion tensor imaging for acute myotendinous injuries, and sagittal short tau inversion recovery and axial long-axis T1-weighted, and 3D Cube sequences for bone stress imaging. Future studies should further refine and validate these MR-based quantitative techniques while exploring the lifelong cumulative impact of basketball on players' knees. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 2.

Non-invasive assessment of normal and impaired iron homeostasis in the brain

Strict iron regulation is essential for normal brain function. The iron homeostasis, determined by the milieu of available iron compounds, is impaired in aging, neurodegenerative diseases and cancer. However, non-invasive assessment of different molecular iron environments implicating brain tissue’s iron homeostasis remains a challenge. We present a magnetic resonance imaging (MRI) technology sensitive to the iron homeostasis of the living brain (the r1-r2* relaxivity). In vitro, our MRI approach reveals the distinct paramagnetic properties of ferritin, transferrin and ferrous iron ions. In the in vivo human brain, we validate our approach against ex vivo iron compounds quantification and gene expression. Our approach varies with the iron mobilization capacity across brain regions and in aging. It reveals brain tumors’ iron homeostasis, and enhances the distinction between tumor tissue and non-pathological tissue without contrast agents. Therefore, our approach may allow for non-invasive research and diagnosis of iron homeostasis in living human brains.

T1 contrast versus fluid-attenuated inversion recovery contrast technique for evaluation of cerebral tuberculosis

Objectives: T2-weighted (T2W) fluid-attenuated inversion recovery (FLAIR), a traditional magnetic resonance imaging (MRI) technique, is regarded as one of the most effective methods for examining brain disorders. The identification of brain pathologies can be significantly aided by T2 FLAIR and T1 post-contrast imaging. However, lesion enhancement is occasionally inconspicuous on T1-weighted image. Hence, for the evaluation of brain disorders, a MRI approach known as FLAIR contrast would combine the benefits of T2W FLAIR with contrast-enhancement on a single picture. Material and Methods: After obtaining clearance from the Institution’s Ethics Committee, contrast-enhanced MRI (CE-MRI) brain of 20 patients was taken for the study. CE-MRI was performed using 1.5 Tesla Intera PHILIPS with intravenous administration of gadolinium at approximately 0.1 mL/kg/body at a rate of 10 mL/15 s. Results: This study showed a better appreciation of lesion conspicuity when compared to prior T1 contrast images. However, there was no significant difference in the number of lesions, lesion extension, and degree of contrast-enhancement on comparison with T1 contrast images. Conclusion: T1 FLAIR contrast shows a better appreciation of lesion conspicuity when compared to T1 contrast images. Post-contrast FLAIR imaging is a valuable adjunct to post-contrast T1W imaging and effectively delineates cerebral tubercular pathologies. However, T1 FLAIR cannot be used as a replacement for conventional T1 fat saturated post-contrast imaging.

Recent Advances in Habenula Imaging Technology: A Comprehensive Review.

The habenula (Hb) is involved in many natural human behaviors, and the relevance of its alterations in size and neural activity to several psychiatric disorders and addictive behaviors has been presumed and investigated in recent years using magnetic resonance imaging (MRI). Although the Hb is small, an increasing number of studies have overcome the difficulties in MRI. Conventional structural-based imaging also has great defects in observing the Hb contrast with adjacent structures. In addition, more and more attention should be paid to the Hb's functional, structural, and quantitative imaging studies. Several advanced MRI methods have recently been employed in clinical studies to explore the Hb and its involvement in psychiatric diseases. This review summarizes the anatomy and function of the human Hb; moreover, it focuses on exploring the human Hb with noninvasive MRI approaches, highlighting strategies to overcome the poor contrast with adjacent structures and the need for multiparametric MRI to develop imaging markers for diagnosis and treatment follow-up. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Multiparametric Magnetic Resonance Investigations on Acute and Long-Term Kidney Injury.

Acute kidney injury (AKI) is a frequent complication of critical illness and carries a significant risk of short- and long-term mortality. The prediction of the progression of AKI to long-term injury has been difficult for renal disease treatment. Radiologists are keen for the early detection of transition from AKI to long-term kidney injury, which would help in the preventive measures. The lack of established methods for early detection of long-term kidney injury underscores the pressing needs of advanced imaging technology that reveals microscopic tissue alterations during the progression of AKI. Fueled by recent advances in data acquisition and post-processing methods of magnetic resonance imaging (MRI), multiparametric MRI is showing great potential as a diagnostic tool for many kidney diseases. Multiparametric MRI studies offer a precious opportunity for real-time noninvasive monitoring of pathological development and progression of AKI to long-term injury. It provides insight into renal vasculature and function (arterial spin labeling, intravoxel incoherent motion), tissue oxygenation (blood oxygen level-dependent), tissue injury and fibrosis (diffusion tensor imaging, diffusion kurtosis imaging, T1 and T2 mapping, quantitative susceptibility mapping). The multiparametric MRI approach is highly promising but the longitudinal investigation on the transition of AKI to irreversible long-term impairment is largely ignored. Further optimization and implementation of renal MR methods in clinical practice will enhance our comprehension of not only AKI but chronic kidney diseases. Novel imaging biomarkers for microscopic renal tissue alterations could be discovered and benefit the preventative interventions. This review explores recent MRI applications on acute and long-term kidney injury while addressing lingering challenges, with emphasis on the potential value of the development of multiparametric MRI for renal imaging on clinical systems. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 2.

MP44-14 PREBIOPSY MRI APPROACH FOR PROSTATE CANCER DIAGNOSIS IS ASSOCIATED WITH LOWER RISK OF BIOCHEMICAL RECURRENCE AFTER TREATMENT

You have accessJournal of UrologyCME1 Apr 2023MP44-14 PREBIOPSY MRI APPROACH FOR PROSTATE CANCER DIAGNOSIS IS ASSOCIATED WITH LOWER RISK OF BIOCHEMICAL RECURRENCE AFTER TREATMENT Fernando Blank, Neha Debnath, Shima Tayebi, Amy Cherry, Juliana Tobler, Sadhna Verma, and Abhinav Sidana Fernando BlankFernando Blank More articles by this author , Neha DebnathNeha Debnath More articles by this author , Shima TayebiShima Tayebi More articles by this author , Amy CherryAmy Cherry More articles by this author , Juliana ToblerJuliana Tobler More articles by this author , Sadhna VermaSadhna Verma More articles by this author , and Abhinav SidanaAbhinav Sidana More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003290.14AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: To determine the impact of prebiopsy prostate magnetic resonance imaging (MRI) followed by a targeted biopsy (TBx) approach for initial diagnosis on oncological outcomes after prostate cancer (PCa) treatment. METHODS: We performed a retrospective review of all patients who underwent prostate biopsy followed by radiation therapy (RT) or radical prostatectomy (RP) as their first treatment at our center from 2014-2020. Patients were separated into two cohorts based on the diagnostic approach: prebiopsy prostate MRI during initial evaluation and those who did not receive MRI. Patients with positive MRI findings underwent a combination of TBx and systematic biopsy (SBx) to confirm diagnosis while those without MRI underwent SBx only. Patients with prostate specific antigen (PSA) >20 were excluded. Kaplan-Meier curve analysis was used to compare biochemical recurrence (BCR, defined as PSA>0.2ng/ml after RP or a rise of 2ng/ml after RT) between cohorts. Cox proportional hazard analysis was done to determine the predictors of the BCR. RESULTS: 366 patients (174 diagnosed by SBx only, and 192 diagnosed by prebiopsy MRI and TBx) with a median follow-up of 40 months were included in the study. 245 men (67%) had RP as their first treatment. Median age and PSA were 64.7 and 7.9 respectively in the SBx cohort and 65.0 and 8.3 respectively in TBx cohort. There was a significant difference in BCR rate between the TBx (7.98%) versus SBx (19.28%, p<0.05 by log rank). After adjusting for age, race, PSA, biopsy path, DRE, and family history, prebiopy MRI and TBx approach for diagnosis was found to be an independent negative predictor (p=0.001); with patients diagnosed with the above approach 71% less likely to have BCR during the study period. CONCLUSIONS: Our study shows that patients undergoing prebiopsy MRI followed by TBx have lower rates of BCR compared to men diagnosed without prebiopsy MRI. To our knowledge, this study is the first to show the positive impact of prebiopsy MRI on oncological outcomes, likely due to its role in risk stratification, treatment selection and surgical staging and planning. Further longitudinal studies are needed to discern the true long-term benefits of prebiopsy MRI on oncological outcomes. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e617 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Fernando Blank More articles by this author Neha Debnath More articles by this author Shima Tayebi More articles by this author Amy Cherry More articles by this author Juliana Tobler More articles by this author Sadhna Verma More articles by this author Abhinav Sidana More articles by this author Expand All Advertisement PDF downloadLoading ...

Deep Learning Approach for MRI in the Classification of Anterior Talofibular Ligament Injuries.

Diagnosing anterior talofibular ligament (ATFL) injuries differs among radiologists. Further assessment of ATFL tears is valuable for clinical decision-making. To establish a deep learning method for classifying ATFL injuries based on magnetic resonance imaging (MRI). Retrospective. One thousand seventy-three patients from a single center with ankle MRI within 1 month of reference standard arthroscopy (in-group dataset), were divided into training, validation, and test sets in a ratio of 8:1:1. Additionally, 167 patients from another center were used as an independent out-group dataset. Fat-saturation proton density-weighted fast spin-echo sequence at 1.5/3.0 T. Patients were divided into normal, strain and degeneration, partial tear and complete tear groups (groups 0-3). The complete tear group was divided into five sub-groups by location and the potential avulsion fracture (groups 3.1-3.5). All images were input into AlexNet, VGG11, Small-Sample-Attention Net (SSA-Net), and SSA-Net + Weight Loss for classification. The results were compared with four radiologists with 5-30 years of experience. Model performance was evaluated by the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and so on. McNemar's test was used to compare performance among the different models, and between the radiologists and models. The intraclass correlation coefficient (ICC) was used to assess the reliability of the radiologists. P < 0.05 was considered statistically significant. The average AUC of AlexNet, VGG11, SAA-Net, and SSA-Net + Weight Loss was 0.95, 0.99, 0.99, 0.99 in groups 0-3 and 0.96, 0.99, 0.99, 0.99 in groups 3.1-3.5. The effect of SSA-Net + Weight Loss was similar to SSA-Net but better than AlexNet and VGG11. In the out-group test set, the AUC of SSA-Net + Weight Loss ranged from 0.89 to 0.99. The ICC of radiologists was 0.97-1.00. The effect of SSA-Net + Weight Loss was better than each radiologist in the in-group and out-group test sets. Deep learning has potential to be used for classifying ATFL injuries. SSA-Net + Weight Loss has a better diagnostic effect than radiologists with different experience levels. 4 TECHNICAL EFFICACY: Stage 2.

MRI of the ileal pouch.

Ileal pouch surgery is the surgical gold standard treatment for patients with ulcerative colitis (UC) and familial adenomatous polyposis (FAP). However, ileal pouch surgery is a technically challenging procedure and is associated with high morbidity. Clinical presentations of pouch complications are often nonspecific but imaging can identify many of these complications and is essential in clinical management. This paper will focus on magnetic resonance imaging (MRI) of the ileal pouch, including recommended MRI protocol and approach to imaging interpretation with an emphasis on those ileal pouch complications particularly well evaluated with MRI.

Environmental Impact of Prostate Magnetic Resonance Imaging and Transrectal Ultrasound Guided Prostate Biopsy

BackgroundReducing low-value clinical care is an important strategy to mitigate environmental pollution caused by health care. ObjectiveTo estimate the environmental impacts associated with prostate magnetic resonance imaging (MRI) and prostate biopsy. Design, setting, and participantsWe performed a cradle-to-grave life cycle assessment of prostate biopsy. Data included materials and energy inventory, patient and staff travel contributed by prostate MRI, transrectal ultrasound guided prostate biopsy, and pathology analysis. We compared environmental emissions across five clinical scenarios: multiparametric MRI (mpMRI) of the prostate with targeted and systematic biopsies (baseline), mpMRI with targeted biopsy cores only, systematic biopsy without MRI, mpMRI with systematic biopsy, and biparametric MRI (bpMRI) with targeted and systematic biopsies. We estimated the environmental impacts associated with reducing the overall number and varying the approach of a prostate biopsy by using MRI as a triage strategy or by omitting MRI. The study involved academic medical centers in the USA, outpatient urology clinics, health care facilities, medical staff, and patients. Outcome measurements and statistical analysisGreenhouse gas emissions (CO2 equivalents, CO2e), and equivalents of coal and gasoline burned were measured. Results and limitationsIn the USA, a single transrectal prostate biopsy procedure including prostate MRI, and targeted and systematic biopsies emits an estimated 80.7 kg CO2e. An approach of MRI targeted cores alone without a systematic biopsy generated 76.2 kg CO2e, a systematic 12-core biopsy without mpMRI generated 36.2 kg CO2e, and bpMRI with targeted and systematic biopsies generated 70.5 kg CO2e; mpMRI alone contributed 42.7 kg CO2e (54.3% of baseline scenario). Energy was the largest contributor, with an estimated 38.1 kg CO2e, followed by staff travel (20.7 kg CO2e) and supply production (11.4 kg CO2e). Performing 100 000 fewer unnecessary biopsies would avoid 8.1 million kg CO2e, the equivalent of 4.1 million liters of gasoline consumed. Per 100 000 patients, the use of prostate MRI to triage prostate biopsy and guide targeted biopsy cores would save the equivalent of 1.4 million kg of CO2 emissions, the equivalent of 700 000 l of gasoline consumed. This analysis was limited to prostate MRI and biopsy, and does not account for downstream clinical management. ConclusionsA prostate biopsy contributes a calculable environmental footprint. Modifying or reducing the number of biopsies performed through existing evidence-based approaches would decrease health care pollution from the procedure. Patient summaryWe estimated that prostate magnetic resonance imaging (MRI) with a prostate biopsy procedure emits the equivalent of 80.7 kg of carbon dioxide. Performing fewer unnecessary prostate biopsies or using prostate MRI as a tool to decide which patients should have a prostate biopsy would reduce procedural greenhouse gas emissions and health care pollution.

Updates on Quantitative MRI of Diffuse Liver Disease: A Narrative Review.

Diffuse liver diseases are highly prevalent conditions around the world, including pathological liver changes that occur when hepatocytes are damaged and liver function declines, often leading to a chronic condition. In the last years, Magnetic Resonance Imaging (MRI) is reaching an important role in the study of diffuse liver diseases moving from qualitative to quantitative assessment of liver parenchyma. In fact, this can allow noninvasive accurate and standardized assessment of diffuse liver diseases and can represent a concrete alternative to biopsy which represents the current reference standard. MRI approach already tested for other pathologies include diffusion-weighted imaging (DWI) and radiomics, able to quantify different aspects of diffuse liver disease. New emerging MRI quantitative methods include MR elastography (MRE) for the quantification of the hepatic stiffness in cirrhotic patients, dedicated gradient multiecho sequences for the assessment of hepatic fat storage, and iron overload. Thus, the aim of this review is to give an overview of the technical principles and clinical application of new quantitative MRI techniques for the evaluation of diffuse liver disease.

Dextran-enhanced CEST MRI reveals the size effect of BBB dysfunction associated with neuroinflammation

INTRODUCTION: The blood-brain barrier (BBB) is compromised in multiple central nervous system (CNS) disorders associated with neuroinflammation, including multiple sclerosis (MS). Currently available magnetic resonance imaging (MRI) methods, however, are only able to measure BBB leakage in the lower molecular size range with the use of small molecular tracers, i.e., gadolinium (Gd) agents (&lt;1 kDa)1,2 and water (18 Da).3,4 The goal of this study is to adopt a dextran-based chemical exchange saturation transfer (CEST) MRI approach for assessing BBB leakage in the larger size range and studying the size characteristics of BBB dysfunction.&#x0D; METHODS: All animal experiments will be approved by the Animal Care and Use Committee of Johns Hopkins University. EAE MS mouse model: C57Bl/6 mice (F/6-10w), were injected s.c. with myelin peptide (MOG35-55, 200 μL, 0.5 mg/mL) emulsified in incomplete Freund's adjuvant supplemented with M. tuberculosis H37Ra (5 mg/mL) and i.p. with 300 ng of pertussis toxin on days 0 and 2. Mice were observed daily for signs of paralysis using a 0-5 rating system. Fluorescent imaging. EAE mice (n=3) were injected with the combination of fixable Dex40-TRITC and Dex3-FITC (i.v.) at the dose of 80 mg/kg, and sacrificed at 30 min after injection (without perfusion) to collect brains. Fluorescence microscopy was then performed on tissue sections. MRI: all in vivo MRI was acquired using a Biospec 11.7 T horizontal MRI scanner (Bruker, Ettlingen, Germany). According to our previously reported protocol,5 CEST MRI was performed before and after the i.v. injection of 200 µL dex40 saline solution (750 mg/kg b.w), using parameters: B1=1.8 µT, Tsat=3 s, Δω=-3 to +3 ppm with a step size of 0.2 ppm. MTRasym=(S-Δω–S+Δω)/S0 was computed after the B0 correction using the WASSR method. ΔMTRasym (1 ppm) at each time point was calculated by MTRasym (t)- MTRasym (pre).&#x0D; RESULTS: 1. The size-dependent BBB disruption in MS can be detected by fluorescent dextran-tracers of different sizes: Immunofluorescent results show dextrans of smaller sizes (e.g., 3 kDa) penetrated the brain parenchyma deeper than larger sizes (e.g., 40 kDa). Our study proves the feasibility to use dextrans as a group of tracers with different sizes for probing the size effect of BBB dysfunction. 2. Dex-enhanced CEST MRI: As shown in Figure 1, mice with high clinical disability scores have BBB impairment in the mouse brain, confirmed with Gd-enhanced MRI (Figure 1B). Dex-enhanced MRI results (Figure 1C) showed substantial contrast enhancement in the corresponding brain regions. Interestingly, while the size of Dex (40 kDa) is larger than the size of Gd-DOTA (559 Da), the area showing enhanced Dex-CEST signal is slightly larger than that of Gd-enhancement, suggesting that, besides size, other particle properties such as shape and surface properties of a given agent/particle may also contribute to the permeation across BBB.&#x0D; CONCLUSIONS: We have established a dextran-based imaging protocol for assessing the biodistribution of dextrans in the brains of EAE mice. We will continue studying the size effect of dextrans and determining the optimal dextran size for accurately mentoring the disease progression.