Diagnostic MRI for deep pelvic endometriosis: towards a standardized protocol?

OBJECTIVES

To assess the diagnostic efficacy of an MRI protocol and patient preparation in detecting deep pelvic endometriosis (DPE).

MATERIAL AND METHODS

The cohort is from the ENDOVALIRM database, a multicentric national retrospective study involving women who underwent MRI followed by pelvic surgery for endometriosis (reference standard). Two senior radiologists independently analyzed MRI findings using the deep pelvic endometriosis index (dPEI) to determine lesion locations. The study evaluated the impact of bowel preparation, vaginal and rectal opacification, MRI unit type (1.5-T or 3-T), additional sequences (thin slice T2W or 3DT2W), and gadolinium injection on reader performance for diagnosing DPE locations. Fisher's exact test assessed differences in diagnostic accuracy based on patient preparation and MRI parameters.

RESULTS

The final cohort comprised 571 women with a mean age of 33.3 years (± 6.6 SD). MRI with bowel preparation outperformed MRI without bowel preparation in identifying torus/uterosacral ligament (USL) locations (p < 0.0001) and rectosigmoid nodules (p = 0.01). MRI without vaginal opacification diagnosed 94.1% (301/320) of torus/USL locations, surpassing MR with vaginal opacification, which diagnosed 85% (221/260) (p < 0.001). No significant differences related to bowel preparation or vaginal opacification were observed for other DPE locations. Rectal opacification did not affect diagnostic accuracy in the overall population, except in patients without bowel preparation, where performance improved (p = 0.04). There were no differences in diagnostic accuracy regarding MRI unit type (1.5-T/3-T), presence of additional sequences, or gadolinium injection for any endometriotic locations.

CONCLUSION

Bowel preparation prior to MRI examination is preferable to rectal or vaginal opacification for diagnosing deep endometriosis pelvic lesions.

CLINICAL RELEVANCE STATEMENT

Accurate diagnosis and staging of DPE are essential for effective treatment planning. Bowel preparation should be prioritized over rectal or vaginal opacification in MRI protocols. Optimizing MRI protocols for diagnostic performance with appropriate opacification techniques will help diagnose deep endometriosis more accurately.

KEY POINTS

Evaluating deep endometriosis in collapsible organs such as the vagina and rectum is difficult. Bowel preparation and an absence of vaginal opacification were found to be diagnostically beneficial. Bowel preparation should be prioritized over rectal or vaginal opacification in MRI protocols.

Magnetic resonance imaging of the knee for chronological age estimation-a systematic review

INTRODUCTION

Radiographs of the hand and teeth are frequently used for medical age assessment, as skeletal and dental maturation correlates with chronological age. These methods have been criticized for their lack of precision, and magnetic resonance imaging (MRI) of the knee has been proposed as a more accurate method. The aim of this systematic review is to explore the scientific and statistical evidence for medical age estimation based on skeletal maturation as assessed by MRI of the knee.

MATERIALS AND METHODS

A systematic review was conducted that included studies published before April 2021 on living individuals between 8 and 30 years old, with presumptively healthy knees for whom the ossification stages had been evaluated using MRI. The correlation between "mature knee" and chronological age and the risk of misclassifying a child as an adult and vice versa was calculated.

RESULTS

We found a considerable heterogeneity in the published studies -in terms of study population, MRI protocols, and grading systems used. There is a wide variation in the correlation between maturation stage and chronological age.

CONCLUSION

Data from published literature is deemed too heterogenous to support the use of MRI of the knee for chronological age determination. Further, it is not possible to assess the sensitivity, specificity, negative predictive value, or positive predictive value for the ability of MRI to determine whether a person is over or under 18 years old.

KEY POINTS

• There is an insufficient scientific basis for the use of magnetic resonance imaging of the knee in age determination by skeleton. • It is not possible to assess the predictive value of MRI of the knee to determine whether a person is over or under 18 years of age.

Improving the Age Estimation Efficiency by Calculation of the Area Ratio Index Using Semi-Automatic Segmentation of Knee MRI Images

The knee is an anatomical structure that can provide a great deal of data for research on age estimation. The aim of this study was to evaluate and apply a method for semi-automatic measurements of the area under the growth plate closure of the femur distal epiphysis and the growth plate closure itself on the 2D coronary slices using T2 weighted images (T2WI) generated on magnetic resonance (MRI) devices of different technical and technological characteristics. After the semi-automatic segmentation of the femur distal epiphysis under the growth plate closure and the growth plate closure itself, the areas of the measured closures were calculated using MATLAB version: 9.12. (R2022a), MathWorks Inc., Natick, MA, USA, for each individual coronal slice. The area ratio index (ARI) was calculated as the ratio between the area under the growth plate closure of the femur distal epiphysis and the growth plate closure itself. The study sample consisted of 27 female and 23 male Caucasian participants aged 10 to 26 years. A total of 339 T2WI images were used for ARI calculations. There was a positive correlation between chronological age and the average ARI measured by three independent observers (r = 0.8280, p < 0.001). Multiple regression analysis did not show any significant impact of the technical and technological characteristics of the MRI devices on ARI. The results of this study showed that ARI could serve as a useful tool for age estimation using knee MRI as well as for the further development of artificial intelligence (AI) applications.

Utilization of a cloud-based radiology analytics platform to monitor imaging volumes at a large tertiary center

Rationale and objective

In this study, we evaluate the ability of a novel cloud-based radiology analytics platform to continuously monitor imaging volumes at a large tertiary center following institutional protocol and policy changes.

Materials and methods

We evaluated response to environmental factors through the lens of the COVID-19 pandemic. Analysis involved 11 CT/18 MR imaging systems at a large tertiary center. A vendor neutral, cloud-based analytics tool (CBRAP) was used to retrospectively collect information via DICOM headers on imaging exams between Oct. 2019 to Aug. 2021. Exams were stratified by modality (CT or MRI) and organized by body region. Pre-pandemic scan volumes (Oct 2019-Feb. 2010) were compared with volumes during/after two waves of COVID-19 in Illinois (Mar. to May 2020 & Oct. to Dec. 2020) using a t-test or Mann-Whitney U test.

Results

The CBRAP was able to analyze 169,530 CT and 110,837 MR images, providing a detailed snapshot of baseline and post-pandemic CT and MR imaging across the radiology enterprise at our tertiary center. The CBRAP allowed for further subdivision in its reporting, showing monthly trends in average scan volumes specifically in the head, abdomen, spine, MSK, thorax, neck, GU system, or breast.

Conclusion

The CBRAP retrieved data for 300,000 + imaging exams across multiple modalities at a large tertiary center in a highly populated, urban environment. The ability to analyze large imaging volumes across multiple waves of COVID-19 and evaluate quality-improvement endeavors/imaging protocol changes displays the usefulness of the CBRAP as an advanced imaging analytics tool.

Normalization of breast MRIs using cycle-consistent generative adversarial networks

OBJECTIVES

Dynamic Contrast Enhanced-Magnetic Resonance Imaging (DCE-MRI) is widely used to complement ultrasound examinations and x-ray mammography for early detection and diagnosis of breast cancer. However, images generated by various MRI scanners (e.g., GE Healthcare, and Siemens) differ both in intensity and noise distribution, preventing algorithms trained on MRIs from one scanner to generalize to data from other scanners. In this work, we propose a method to solve this problem by normalizing images between various scanners.

METHODS

MRI normalization is challenging because it requires normalizing intensity values and mapping noise distributions between scanners. We utilize a cycle-consistent generative adversarial network to learn a bidirectional mapping and perform normalization between MRIs produced by GE Healthcare and Siemens scanners in an unpaired setting. Initial experiments demonstrate that the traditional CycleGAN architecture struggles to preserve the anatomical structures of the breast during normalization. Thus, we propose two technical innovations in order to preserve both the shape of the breast as well as the tissue structures within the breast. First, we incorporate mutual information loss during training in order to ensure anatomical consistency. Second, we propose a modified discriminator architecture that utilizes a smaller field-of-view to ensure the preservation of finer details in the breast tissue.

RESULTS

Quantitative and qualitative evaluations show that the second innovation consistently preserves the breast shape and tissue structures while also performing the proper intensity normalization and noise distribution mapping.

CONCLUSION

Our results demonstrate that the proposed model can successfully learn a bidirectional mapping and perform normalization between MRIs produced by different vendors, potentially enabling improved diagnosis and detection of breast cancer. All the data used in this study are publicly available at https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=70226903.

An International Standardized Magnetic Resonance Imaging Protocol for Diagnosis and Follow-up of Patients with Multiple Sclerosis: Advocacy, Dissemination, and Implementation Strategies

Standardized magnetic resonance imaging (MRI) protocols are important for the diagnosis and monitoring of patients with multiple sclerosis (MS). The Consortium of Multiple Sclerosis Centers (CMSC) convened an international panel of MRI experts to review and update the current guidelines. The objective was to update the standardized MRI protocol and clinical guidelines for diagnosis and follow-up of MS and develop strategies for advocacy, dissemination, and implementation. Conference attendees included neurologists, radiologists, technologists, and imaging scientists with expertise in MS. Representatives from the CMSC, Magnetic Resonance Imaging in MS (MAGNIMS), North American Imaging in Multiple Sclerosis Cooperative, US Department of Veteran Affairs, National Multiple Sclerosis Society, Multiple Sclerosis Association of America, MRI manufacturers, and commercial image analysis companies were present. Before the meeting, CMSC members were surveyed about standardized MRI protocols, gadolinium use, need for diffusion-weighted imaging, and the central vein sign. The panel worked to make the CMSC and MAGNIMS MRI protocols similar so that the updated guidelines could ultimately be accepted by international consensus. Advocacy efforts will promote the importance of standardized MS MRI protocols. Dissemination will include publications, meeting abstracts, educational programming, webinars, "meet the expert" teleconferences, and examination cards. Implementation will require comprehensive and coordinated efforts to make the protocol easy to access and use. The ultimate vision, and goal, is for the guidelines to be universally useful, usable, and used as the standard of care for patients with MS.