Body MRI Subspecialty Reinterpretations at a Tertiary Care Center: Discrepancy Rates and Error Types

Reinterpretation of Hepatopancreaticobiliary Imaging Exams: Assessment of Clinical Impact, Peer Learning, and Physician Satisfaction

OBJECTIVES

To assess the impact on clinical management, potential for peer learning, and referring physician satisfaction with subspecialist reinterpretations of hepatopancreaticobiliary (HPB) imaging examinations.

MATERIALS AND METHODS

HPB CTs and MRIs from outside hospitals were reinterpreted by two subspecialty radiologists between March 2021 and August 2022. Reinterpretation reports were mailed to radiologists that issued primary reports. The electronic record was reviewed to assess for changes in clinical management based on the reinterpretations (yes/no/unavailable). To assess the potential for peer learning, a survey using a 5-point Likert scale was sent to radiologists who issued primary reports. A separate survey was sent to referring physicians to assess satisfaction with reinterpretations.

RESULTS

Two hundred fifty imaging examinations (122 CT, 128 MRI) were reinterpreted at the request of 19 referring physicians. Ninety-six radiologists issued primary reports. RADPEER scores 1-3 were assigned to 131/250 (52%), 86/250 (34%), and 33/250 (13%) examinations, respectively. Of 213 reinterpretations with adequate records for assessment, 75/213 (35%) were associated with a change in management; of these, 71/75 (95%) were classified as RADPEER 2 or 3. Most radiologists agreed or strongly agreed with the following: prefer to receive reinterpretations (34/36, 94%); reinterpretations changed practice of reporting HPB imaging examinations (23/36, 64%); and reinterpretations offer opportunities for peer learning (34/36, 94%). Referring physicians agreed or strongly agreed (7/7, 100%) that reinterpretations are valuable and often change or clarify management of patients with complex HPB disease, and offer an opportunity for peer learning.

CONCLUSION

Radiologists and referring physicians strongly agree that HPB imaging reinterpretations help support peer learning and patient management, respectively.

Second-opinion interpretation of outside facility general ultrasound studies: rate of discrepancies and management change

BACKGROUND

Second-opinion reads on imaging studies are common for CT and MRI, but many institutions are hesitant to implement a workflow for second read of ultrasound studies performed at other facilities due to quality considerations.

OBJECTIVE

The purpose of this study was to assess discrepancy rates between initial and second-opinion general ultrasound reports METHODS: We reviewed all requests of second-opinion US studies referred to our tertiary care center between 02/01/2020 and 06/23/2022. We evaluated percentage of exams that were interpreted versus archived. Whenever the original report was available (n = 196 studies), we evaluated any discrepancy in findings, interpretation, and potential management change based on second report compared to the initial report as evaluated by consensus agreement of 3 subspecialized radiologists.

RESULTS

A total of 586 ultrasound studies for 533 patients were nominated for consult. After excluding 58 studies for technical reasons (e.g., duplicate nomination, images for procedure guidance, modality is not ultrasound) and 282 studies that were archived by the reading radiologist due to various objective (e.g., studies such as echocardiography not interpreted by the abdominal imagers or more recent study available obviating need for consultation) and subjective (e.g., suboptimal image quality, lack of cine clips) reasons, a total of 246 studies were reinterpreted and were further analyzed. Only 21/246 patients (8.5%) got repeat ultrasound of the same body part within 3 months of original study date. The original (first-read) report was available for 196/246 studies, with discrepancy present between the first and second reads in 74/196 (37.8%) studies, with potential management change in 51/196 (26.0%) studies.

CONCLUSION

Second-opinion interpretation of outside ultrasound examinations by subspecialized radiologists can result in recommended management change in 26% of studies indicating potential for added value to reinterpreting ultrasound studies despite the concerns for quality control.

Deep CTS: a Deep Neural Network for Identification MRI of Carpal Tunnel Syndrome

Carpal tunnel syndrome (CTS) is a common peripheral nerve disease in adults; it can cause pain, numbness, and even muscle atrophy and will adversely affect patients' daily life and work. There are no standard diagnostic criteria that go against the early diagnosis and treatment of patients. MRI as a novel imaging technique can show the patient's condition more objectively, and several characteristics of carpal tunnel syndrome have been found. However, various image sequences, heavy artifacts, small lesion characteristics, high volume of imagine reading, and high difficulty in MRI interpretation limit its application in clinical practice. With the development of automatic image segmentation technology, the algorithm has great potential in medical imaging. The challenge is that the segmentation target is too small, and there are two categories of images with the proximal border of the carpal tunnel as the boundary. To meet the challenge, we propose an end-to-end deep learning framework called Deep CTS to segment the carpal tunnel from the MR image. The Deep CTS consists of the shape classifier with a simple convolutional neural network and the carpal tunnel region segmentation with simplified U-Net. With the specialized structure for the carpal tunnel, Deep CTS can segment the carpal tunnel region efficiently and improve the intersection over union of results. The experimental results demonstrated that the performance of the proposed deep learning framework is better than other segmentation networks for small objects. We trained the model with 333 images, tested it with 82 images, and achieved 0.63 accuracy of intersection over union and 0.17 s segmentation efficiency, which indicate great promise for the clinical application of this algorithm.

Current and future imaging modalities in gastric cancer

Gastric adenocarcinoma treatment can include endoscopic mucosal resection, surgery, chemotherapy, radiation, and palliative measures depending on staging. Both invasive and noninvasive staging techniques have been used to dictate the best treatment pathway. Here, we review the current imaging modalities used in gastric cancer as well as novel techniques to accurately stage and screen these patients.

Radiologist errors by modality, anatomic region, and pathology for 1.6 million exams: what we have learned

PURPOSE

To evaluate the feasibility of adding pathology to recent radiologist error characterization schemes of modality and anatomic region and the potential of this data to more specifically inform peer review and peer learning.

METHODS

Quality assurance data originating from 349 radiologists in a national teleradiology practice were collected for 2019. Interpretive errors were simply categorized as major or minor. Reporting or communication errors were classified as administrative errors. Interpretive errors were then divided by modality, anatomic region and placed into one of 64 pathologic categories.

RESULTS

Out of 1,628,464 studies, the discrepancy rate was 0.5% (8181/1,634,201). The 8181 total errors consisted of 2992 major errors (0.18%) and 5189 minor errors (0.32%). Precisely, 3.1% (257/8181) of total errors were administrative. Of major interpretive errors, 75.5% occurred on CT, with CT abdomen and pelvis accounting for 40.4%. The most common pathologic discrepancy for all exams was in the category of mass, nodule, or adenopathy (1583/8181), the majority of which were minor (1315/1583). The most common pathologic discrepancy for the 2937 major interpretive errors was fracture or dislocation (27%; 793/2937), followed by bleed (10.7%; 315/2937).

CONCLUSION

The addition of error-related pathology to peer review is both feasible and practical and provides a more detailed guide to targeted individual and practice-wide peer learning quality improvement efforts. Future research is needed to determine if there are measurable improvements in detection or interpretation of specific pathologies following error feedback and educational interventions.