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Rationale and Objectives: The expansion of large language models to process images offers new avenues for application in radiology. This study aims to assess the multimodal capabilities of contemporary large language models, which allow analysis of image inputs in addition to textual data, on radiology board-style examination questions with images., Materials and Methods: 280 questions were retrospectively selected from the AuntMinnie public test bank. The test questions were converted into three formats of prompts; (1) Multimodal, (2) Image-only, and (3) Text-only input. Three models, GPT-4V, Gemini 1.5 Pro, and Claude 3.5 Sonnet, were evaluated using these prompts. The Cochran Q test and pairwise McNemar test were used to compare performances between prompt formats and models., Results: No difference was found for the performance in terms of % correct answers between the text, image, and multimodal prompt formats for GPT-4V (54%, 52%, and 57%, respectively; p = .31) and Gemini 1.5 Pro (53%, 54%, and 57%, respectively; p = .53). For Claude 3.5 Sonnet, the image input (48%) significantly underperformed compared to the text input (63%, p < .001) and the multimodal input (66%, p < .001), but no difference was found between the text and multimodal inputs (p = .29). Claude significantly outperformed GPT and Gemini in the text and multimodal formats (p < .01)., Conclusion: Vision-capable large language models cannot effectively use images to increase performance on radiology board-style examination questions. When using textual data alone, Claude 3.5 Sonnet outperforms GPT-4V and Gemini 1.5 Pro, highlighting the advancements in the field and its potential for use in further research., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)

In this case report, we describe a diagnosis of papillary renal cell carcinoma in a 76-year-old male patient who was incidentally found to have a left adrenal mass during routine aneurysm surveillance. Computed tomography demonstrated a left adrenal mass and left renal structure which was concerning for renal cell carcinoma. He underwent left adrenalectomy and initial histopathology demonstrated papillary renal cell carcinoma. He subsequently underwent left radical nephrectomy with lymph node dissection. Histopathological analysis of the removed left renal and nodal specimens revealed papillary renal cell carcinoma with lymph node metastasis. However, re-review of the adrenal pathology slides determined the specimen as represented by primary kidney tumor and not adrenal metastasis. This report reviews the presentation and radiological findings of synchronous papillary renal cell carcinoma and differential diagnosis for indeterminate adrenal mass on computed tomography., (© 2024 The Authors. Published by Elsevier Inc. on behalf of University of Washington.)

Background The burgeoning interest in ChatGPT as a potentially useful tool in medicine highlights the necessity for systematic evaluation of its capabilities and limitations. Purpose To evaluate the accuracy, reliability, and repeatability of differential diagnoses produced by ChatGPT from transcribed radiologic findings. Materials and Methods Cases selected from a radiology textbook series spanning a variety of imaging modalities, subspecialties, and anatomic pathologies were converted into standardized prompts that were entered into ChatGPT (GPT-3.5 and GPT-4 algorithms; April 3 to June 1, 2023). Responses were analyzed for accuracy via comparison with the final diagnosis and top 3 differential diagnosis provided in the textbook, which served as the ground truth. Reliability, defined based on the frequency of algorithmic hallucination, was assessed through the identification of factually incorrect statements and fabricated references. Comparisons were made between the algorithms using the McNemar test and a generalized estimating equation model framework. Test-retest repeatability was measured by obtaining 10 independent responses from both algorithms for 10 cases in each subspecialty, and calculating the average pairwise percent agreement and Krippendorff α. Results A total of 339 cases were collected across multiple radiologic subspecialties. The overall accuracy of GPT-3.5 and GPT-4 for final diagnosis was 53.7% (182 of 339) and 66.1% (224 of 339; P < .001), respectively. The mean differential score (ie, proportion of top 3 diagnoses that matched the original literature differential diagnosis) for GPT-3.5 and GPT-4 was 0.50 and 0.54 ( P = .06), respectively. Of the references provided in GPT-3.5 and GPT-4 responses, 39.9% (401 of 1006) and 14.3% (161 of 1124; P < .001), respectively, were fabricated. GPT-3.5 and GPT-4 generated false statements in 16.2% (55 of 339) and 4.7% (16 of 339; P < .001) of cases, respectively. The range of average pairwise percent agreement across subspecialties for the final diagnosis and top 3 differential diagnosis was 59%-98% and 23%-49%, respectively. Conclusion ChatGPT achieved the best results when the most up-to-date model (GPT-4) was used and when it was prompted for a single diagnosis. Hallucination frequency was lower with GPT-4 than with GPT-3.5, but repeatability was an issue for both models. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Chang in this issue.

Phosphaturic mesenchymal tumor (PMT) is a rare tumor causing bone complications and myopathy. Histologically, PMT displays a mix of spindled cells, osteoclast-like giant cells, basophilic matrix, and flocculent or "grungy" calcification. Here we describe a case of PMT in the right hip and proximal femur, initially suspected to be multiple myeloma, presenting with osteolytic lesions and elevated alkaline phosphatase. Tests for malignancy were negative, but a subsequent biopsy confirmed PMT. The patient underwent hip biopsy, femur resection, and hemiarthroplasty, with follow-up MRI recommended., (© 2024 The Authors. Published by Elsevier Inc. on behalf of University of Washington.)

The shift from film to PACS in reading rooms, coupled with escalating case volumes, exposes radiologists to the issues of the modern computer workstation including computer work posture and work-related musculoskeletal disorders (WMSD). Common WMSDs affecting the neck and upper extremities include cervical myofascial pain, shoulder tendonitis, lateral epicondylitis, carpal tunnel syndrome, and cubital tunnel syndrome. This review examines each pathology along with its pathogenesis, clinical features, physical exam findings, and potential risk factors. Furthermore, a comprehensive 11-part physical therapy regimen that is both prophylactic and therapeutic is illustrated and described in detail. One of the objectives of this review is to advocate for the inclusion of a physical therapy regimen in the working routine of diagnostic radiologists to prevent WMSDs. A brief daily commitment to this regimen can help radiologists remain healthy and productive in order to deliver optimal patient care throughout their careers., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Prostate cancer accounts for 29% of malignant diagnoses among men in the United States and is the second leading cause of death from cancer. Effective screening methods and improved treatment have decreased the mortality rate significantly. This decreased mortality rate, however, does not apply to all histologic variants. Adenosquamous carcinoma of the prostate is an extremely aggressive neoplasm with no current known curative therapy. It is often diagnosed after chemotherapy, radiation, or androgen deprivation therapy for traditional prostatic adenocarcinomas. Primary carcinomas of the prostate with squamous features include, but are not limited to, pure squamous cell carcinoma and adenocarcinoma mixed with squamous cell carcinoma (SCC). Important distinguishable clinical features of adenosquamous carcinoma include normal prostate-specific antigen (PSA) levels, even with advanced disease and osteolytic versus osteoblastic metastatic lesions in adenocarcinoma. Additional entities to consider in the differential diagnosis are squamous metaplasia of the prostate, secondary involvement of pure SCC, and urothelial carcinoma with squamous differentiation. Here, we present a de novo case of adenosquamous carcinoma in a 48-year-old man who rapidly developed extensive metastatic disease.

Purpose: Early characterization of small (T1a, <4 cm) renal masses is imperative for patient care and treatment planning. Renal biopsy is a sensitive and specific procedure that can accurately differentiate small renal masses as malignant or benign. However, it is an invasive procedure with a nonnegligible complication rate and is not performed routinely at most institutions. In this study, we sought to apply the Retroperitoneal Vascularity Assessment and Scoring in Carcinoma (Re-VASC) scoring system to T1a renal masses and analyzed whether it could differentiate these masses as benign or malignant. Methods: We obtained Institutional Review Board approval to retrospectively examine the records of all patients who presented to our single, urban academic referral center for surgical treatment of renal cell carcinoma (RCC). For the malignant group, patients with a diagnosis of T1a RCC from pathologic evaluation were included. Additionally, patients with a histopathological diagnosis of a T1a nonmalignant renal mass (fat poor-angiomyolipoma or oncocytoma) were included in our benign group. Results: This study includes 57 benign and 69 malignant T1a renal tumors. Average size for benign and malignant masses were 2.47 and 2.63, respectively ( p  = 0.267). Analysis demonstrated no significant difference between both groups in terms of sex, laterality, or size. The average Re-VASC score of benign and malignant masses was 0.175 and malignant masses was 0.784, respectively ( p  < 0.001). Additionally, the Re-VASC score was independently associated with malignancy with an odds ratio of 2.223 ( p  = 0.0109). Conclusion: The Re-VASC scoring system exhibits significantly greater values for malignant T1a renal masses when compared to benign masses. As a result, it shows promise as an adjunctive tool to renal biopsy for clinical decision-making. Further assessment of Re-VASC's true efficacy as a diagnostic marker will include prospective evaluation of a larger multicenter population.

Background: Undifferentiated carcinomas of the pancreas with osteoclast-like giant cells (UCPOGC) are rare pancreatic neoplasms that account for less than 1% of all pancreatic malignancies. This case report of a 54-year-old male with metastatic UCPOGC adds to the existing literature and further ascertains the clinical and imaging features, treatment options, and prognosis of this rare entity., Case Presentation: We present the detailed clinical course of a 54-year-old Asian male patient with UCPOGC, with focus on the relevant clinical features and imaging findings that are characteristic of this disease entity., Conclusions: UCPOGC is an extremely rare pancreatic tumor with a unique histopathology and clinical course. It is often difficult to distinguish UCPOGCs from other pancreatic tumors, such as traditional pancreatic ductal adenocarcinomas (PDAC), on imaging, and it therefore remains a pathological diagnosis. Surgery is generally regarded as the first-line treatment option, and the roles of chemotherapy and radiation are unclear. Due to the exceeding rarity of this tumor, large-scale clinical studies are not feasible. Therefore, it is important to share individual insights and experiences to improve our understanding and care for patients with this devastating disease., (© 2023. The Author(s).)

Hepatosplenomegaly is commonly diagnosed by radiologists based on single dimension measurements and heuristic cut-offs. Volumetric measurements may be more accurate for diagnosing organ enlargement. Artificial intelligence techniques may be able to automatically calculate liver and spleen volume and facilitate more accurate diagnosis. After IRB approval, 2 convolutional neural networks (CNN) were developed to automatically segment the liver and spleen on a training dataset comprised of 500 single-phase, contrast-enhanced CT abdomen and pelvis examinations. A separate dataset of ten thousand sequential examinations at a single institution was segmented with these CNNs. Performance was evaluated on a 1% subset and compared with manual segmentations using Sorensen-Dice coefficients and Pearson correlation coefficients. Radiologist reports were reviewed for diagnosis of hepatomegaly and splenomegaly and compared with calculated volumes. Abnormal enlargement was defined as greater than 2 standard deviations above the mean. Median Dice coefficients for liver and spleen segmentation were 0.988 and 0.981, respectively. Pearson correlation coefficients of CNN-derived estimates of organ volume against the gold-standard manual annotation were 0.999 for the liver and spleen (P < 0.001). Average liver volume was 1556.8 ± 498.7 cc and average spleen volume was 194.6 ± 123.0 cc. There were significant differences in average liver and spleen volumes between male and female patients. Thus, the volume thresholds for ground-truth determination of hepatomegaly and splenomegaly were determined separately for each sex. Radiologist classification of hepatomegaly was 65% sensitive, 91% specific, with a positive predictive value (PPV) of 23% and an negative predictive value (NPV) of 98%. Radiologist classification of splenomegaly was 68% sensitive, 97% specific, with a positive predictive value (PPV) of 50% and a negative predictive value (NPV) of 99%. Convolutional neural networks can accurately segment the liver and spleen and may be helpful to improve radiologist accuracy in the diagnosis of hepatomegaly and splenomegaly., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Radiology reports often contain recommendations for follow-up imaging, Provider adherence to these radiology recommendations can be incomplete, which may result in patient harm, lost revenue, or litigation. This study sought to perform a revenue assessment of a hybrid natural language processing (NLP) and human follow-up system. Reports generated from January 2020 to April 2021 that were indexed as overdue from follow-up recommendations by mPower Follow-Up Recommendation Algorithm (Nuance Communications Inc., Burlington, MA), were assessed for follow up and revenue. Follow-up exams completed because of the hybrid system were tabulated and given revenue amounts based on Medicare national reimbursement rates. These rates were then summated. A total of n =3011 patients were flagged via the mPower algorithm as having not received a timely follow-up indicated for procedure. Of these, n = 427 required the quality nurse to contact their healthcare provider to place orders. The follow-up imaging of these patients accounted for $62,937.66 of revenue. This revenue was calculated as higher than personnel cost (based on national average quality and safety nurse salary and time allotted on follow-ups). Our results indicate that a hybrid human-artificial intelligence follow-up system can be profitable, while potentially adding to patient safety. Our revenue figure likely significantly underestimates the true revenue obtained at our institution. This was due to the use of Medicare national reimbursement rates to calculate revenue, for the purposes of generalizability., (Copyright © 2023 Elsevier Inc. All rights reserved.)

Purpose: Renal cell carcinoma (RCC) is the most common type of kidney cancer worldwide. Although radiologists assess enhancement patterns of renal tumors to predict tumor pathology report, to our knowledge, no formal scoring system has been created and validated to assess the level of neovascularity in RCC, despite its critical role in cancer metastases. In this study, we characterized and analyzed the level of angiogenesis in tumor-burdened kidneys and their benign counterparts. We then created and validated a scoring scale for neovascularity that can help predict tumor staging for RCC. Methods: After Institutional Review Board approval, the charts of patients who had undergone operation for RCC between January 13, 2014 and February 4, 2020 were retrospectively reviewed for inclusion in this study. Inclusion criteria were a diagnosis of RCC, simple/radical nephrectomy, preoperative contrast-enhanced CT scans, and complete pathology reports. Neovascularity was scored on a scale of 0-4 where 0 = no neovascularity detected, 1 = a single vessel <3 mm wide, 2 = a single vessel ≥3 mm wide, 3 = multiple vessels <3 mm wide, and 4 = multiple vessels ≥3 mm wide. Results: A total of 227 patients were included in this study. Most of the tumor pathology reports were clear cell carcinoma, regardless of tumor staging. The average neovascularity score was 1.07 for pT1x tumors, 2.83 for pT2x tumors, and 3.04 for pT3x tumors. There was a significant difference in neovascularity score between pT1x and pT2x tumors ( p  = 0.0046), pT1x and pT3x tumors ( p  < 0.0001), and benign kidneys and kidneys with RCC ( p  < 0.0001). Conclusion: Our novel vascular scoring system for RCC demonstrates significant correlation with RCC pathological tumor staging. This scoring system may be utilized as part of a comprehensive radiological assessment of renal tumors, potentially improving tumor characterization and clinical decision making.

Purpose: The coronavirus disease 2019 (COVID-19) pandemic has led to substantial disruptions in healthcare staffing and operations. Stay-at-home (SAH) orders and limitations in social gathering implemented in spring 2020 were followed by initial decreases in healthcare and imaging utilization. This study aims to evaluate the impact of subsequent easing of SAH on trauma volumes, demand for, and turnaround times for trauma computed tomography (CT) exams, hypothesizing that after initial decreases, trauma volumes have increased as COVID safety measures have been reduced., Methods: Patient characteristics, CT imaging volumes, and turnaround time were analyzed for all adult activated emergency department trauma patients requiring CT imaging at a single Level-I trauma center (1/2018-2/2022) located in the sixth most populous county in the USA. Based on COVID safety measures in place in the state of California, three time periods were compared: baseline (PRE, 1/1/2018-3/19/2020), COVID safety measures (COVID, 3/20/2020-1/25/2021), and POST (1/26/2021-2/28/2022)., Results: There were 16,984 trauma patients across the study (PRE = 8289, COVID = 3139, POST = 5556). The average daily trauma patient volumes increased significantly in the POST period compared to the PRE and COVID periods (13.9 vs. 10.3 vs. 10.1, p < 0.001), with increases in both blunt (p < 0.001) and penetrating (p = 0.002) trauma. The average daily number of trauma CT examinations performed increased significantly in the POST period compared to the PRE and COVID periods (56.7 vs. 48.3 vs. 47.6, p < 0.001), with significant increases in average turnaround time (47 min vs. 31 and 37, p < 0.001)., Conclusion: After initial decreases in trauma radiology volumes following stay-at-home orders, subsequent easing of safety measures has coincided with increases in trauma imaging volumes above pre-pandemic levels and longer exam turnaround times., (© 2022. The Author(s).)

Purpose: To create an algorithm able to accurately detect IVC filters on radiographs without human assistance, capable of being used to screen radiographs to identify patients needing IVC filter retrieval., Methods: A primary dataset of 5225 images, 30% of which included IVC filters, was assembled and annotated. 85% of the data was used to train a Cascade R-CNN (Region Based Convolutional Neural Network) object detection network incorporating a pre-trained ResNet-50 backbone. The remaining 15% of the data, independently annotated by three radiologists, was used as a test set to assess performance. The algorithm was also assessed on an independently constructed 1424-image dataset, drawn from a different institution than the primary dataset., Results: On the primary test set, the algorithm achieved a sensitivity of 96.2% (95% CI 92.7-98.1%) and a specificity of 98.9% (95% CI 97.4-99.5%). Results were similar on the external test set: sensitivity 97.9% (95% CI 96.2-98.9%), specificity 99.6 (95% CI 98.9-99.9%)., Conclusion: Fully automated detection of IVC filters on radiographs with high sensitivity and excellent specificity required for an automated screening system can be achieved using object detection neural networks. Further work will develop a system for identifying patients for IVC filter retrieval based on this algorithm., (© 2022. The Author(s).)

The prognosis for patients with penile squamous cell carcinoma metastatic to regional lymph nodes or distant sites remains poor with limited treatment options, especially after the failure of first-line chemotherapy. Clinical trials evaluating the use of checkpoint inhibitor therapy, or the use of checkpoint inhibitor therapy with stereotactic body radiation therapy for the treatment of metastatic penile squamous cell carcinoma, are currently unavailable. In this case report, we present a patient with relapsed advanced penile squamous cell carcinoma and an unknown (human papilloma virus) HPV status and borderline programmed death-ligand 1 (PD-L)1 status who was treated with pembrolizumab and stereotactic body radiation therapy. This patient achieved a complete durable treatment response despite having genomic features of an immunologically "cold" tumor. This case highlights the importance of investigating more into the treatment of these tumors that lack genomic features that classically have been observed to be susceptible to treatment with immunotherapy or immunotherapy augmented with stereotactic body radiation therapy in solid tumors, particularly in metastatic penile squamous cell carcinoma.

Introduction: Enfortumab vedotin is an antibody-drug conjugate used in patients with pretreated advanced urothelial carcinoma. Patients with human immunodeficiency virus were excluded from clinical trials conducted with this agent. Efficacy and safety of enfortumab vedotin has not been established in this patient population., Case Report: A patient with a long-standing diagnosis of human immunodeficiency virus and an undetectable viral load on antiretroviral therapy was diagnosed with metastatic upper tract urothelial carcinoma. Following disease progression on platinum-based chemotherapy and pembrolizumab, he was initiated on therapy with enfortumab vedotin., Management & Outcome: The patient developed significant toxicity shortly after initiation of enfortumab vedotin. His treatment was subsequently changed to docetaxel chemotherapy and he developed similar significant toxicity. Upon changing his antiretroviral therapy regimen, he was rechallenged with enfortumab vedotin and was able to tolerate it without dose-limiting toxicity, ultimately achieving a partial treatment response., Discussion: This case describes use of enfortumab vedotin in a patient with human immunodeficiency virus, which has not previously been reported. It also underscores the importance of careful medication reconciliation in patients receiving enfortumab vedotin and antiretroviral therapy.

Background: Endometriomas are a type of ovarian cyst composed of degenerated blood products from hemorrhage of ectopic endometrial tissue. Endometriomas can rupture, causing hemoperitoneum, and present with signs and symptoms similar to other, more common abdominal emergencies. Therefore, they are not often diagnosed preoperatively. Ultrasound and cross-sectional imaging can assist in diagnosis of endometriomas. We present a case of ruptured endometrioma causing massive hemoperitoneum that was initially suspected to represent malignancy with carcinomatosis., Case Presentation: A 32-year-old Hispanic woman presented with sharp abdominal pain and 15-pound unintentional weight loss over 6 months. Laboratory work was significant for a negative pregnancy test and elevated cancer antigen-125. Computed tomography of the abdomen and pelvis demonstrated a 13-cm complex cystic mass in the left adnexa with moderate hyperdense ascites and omental nodularity. Ultrasound demonstrated a large left adnexal complex cystic structure with internal echoes, and chest computed tomography showed no signs of intrathoracic neoplastic or infectious processes. Her presentation was concerning for malignancy with carcinomatosis. Fluid from a paracentesis was sent for culture and cytology. Diagnostic laparoscopy revealed that the left ovary had been completely replaced by an endometrioma, which had a small ruptured area superiorly. Brown deposits of endometriosis were present on the cyst, omentum, and various peritoneal linings. Tissue samples of the endometrium, myometrium, cervix, ovaries, fallopian tubes, peritoneum, omentum, and paracolic spaces were taken and showed no hyperplastic, dysplastic, or malignant cells on pathology., Conclusions: Ruptured endometrioma and ruptured hemorrhagic cyst should be included in the differential diagnosis when a premenopausal female presents with hemoperitoneum in combination with complex adnexal cystic masses in the absence of trauma. Cancer antigen-125 and cancer antigen 19-9 can be falsely elevated in the setting of ruptured endometrioma., (© 2022. The Author(s).)

This is a case report of a ureteral obstruction from inguinal hernia entrapment with an ipsilateral cryptorchid testis in a 45-year-old male with an ectopic pelvic kidney. Ureteral herniation is unusual and to our knowledge has not been described in the setting of a patient with an ectopic pelvic kidney and undescended testis. The patient initially presented at an outside hospital with mild right lower quadrant abdominal pain and scrotal fullness, and initial computed tomography (CT) imaging demonstrated a pelvic right kidney with an indirect right inguinal hernia containing an entrapped ureter resulting in severe hydronephrosis. The CT also revealed an undescended testis on the patient's right side. A nephrostomy tube was then placed in the right kidney under interventional radiological (IR) guidance and subsequent CT urography showed resolution of hydronephrosis. Surgical hernia repair was followed up on a later date. The discussion addresses the unique pathological features of this case while highlighting the relevant complications of a ureteral herniation., Topics: Pelvic kidney, renal ectopia, ureteral obstruction, cryptorchidism, undescended testis., (© 2022 Feil, et al.)

Background: Ganglioneuromas are a benign tumor originating from neural crest cells. As one of the neuroblastic tumors, ganglioneuromas are most common in children, with a mean age at presentation of 7 years. Ganglioneuromas are typically singular in nature, but rarely can present with lymph node involvement and distant metastasis. We present a rare case of a retroperitoneal ganglioneuroma found in a human immunodeficiency virus positive adult, which was complicated by lymph node involvement. This case is notable not only in regard to the age of the patient, but also because of his human immunodeficiency virus positive status and the extension of tumor to lymph nodes., Case Presentation: A 27-year-old Latino male with history of human immunodeficiency virus presented with a 6-month history of left upper quadrant and epigastric abdominal pain with associated nausea and vomiting. The patient had a computed tomography scan showing a retroperitoneal mass encasing the aorta, celiac axis, and superior mesenteric artery. Core needle biopsy revealed ganglioneuroma. Owing to obstructive symptoms, resection of the mass along with partial gastric resection, partial pancreatic resection, and splenectomy was performed by a multidisciplinary group of surgeons. Pathology results revealed metastatic spread of ganglioneuroma to surrounding lymph nodes., Conclusions: Ganglioneuromas are most common in children and very rarely occur in adults. However, it is still important to consider this entity in the differential for patients presenting with suspicious symptoms. While rare, it is essential to consider metastasis in this generally benign disease., (© 2021. The Author(s).)

Background: Pneumatosis cystoides intestinalis is a rare and usually benign condition in which multiple thin-walled cysts develop in the submucosa or subserosa of the gastrointestinal tract. While usually asymptomatic, severe cases can result in pneumoperitoneum, which can be managed surgically or medically depending on circumstances. We present a case of a patient with pneumatosis cystoides intestinalis, which presented as pneumoperitoneum following trauma. To our knowledge, there are no other published cases in which a trauma patient with pneumoperitoneum was found to have radiologic evidence of pneumatosis cystoides intestinalis., Case Presentation: We present the case of a 37-year-old Hispanic male admitted to the hospital after being involved in a motorcycle accident. Computed tomography imaging of the abdomen and pelvis with oral and intravenous contrast demonstrated trace pneumoperitoneum, possibly originating from the splenic flexure of the colon without evidence of extravasation of oral contrast. Laparoscopy with conversion to exploratory laparotomy revealed bowel abnormalities at the distal transverse colon and splenic flexure, which were identified as pneumatosis cystoides intestinalis by pathology. There was no evidence of bowel perforation. A panel of abdominal radiologists attended the computed tomography interpretation to note that incidental atraumatic or traumatic rupture of the cysts could have caused the pneumoperitoneum. The patient had an uncomplicated postoperative course and was transferred to another facility per insurance request., Conclusions: When presenting in the context of trauma, pneumatosis cystoides intestinalis can lead to difficult management decisions. To our knowledge, there are no existing evidence-based guidelines for the scenario of concurrent pneumatosis cystoides intestinalis, blunt abdominal trauma, and pneumoperitoneum in a patient with a benign abdominal exam. This patient's pneumoperitoneum was likely caused by rupture of preexisting cysts rather than frank bowel perforation. Patients who are asymptomatic, lack signs of clinically worrisome disease, and have a low pretest probability will likely not benefit from surgery and can be medically managed. Thorough discussion between surgeons and radiologists can be helpful when evaluating the clinical significance of a patient's pneumatosis cystoides intestinalis and aid in the decision to perform surgery., (© 2021. The Author(s).)

Background: Patients diagnosed with locally advanced pancreatic cancer are usually not eligible for surgical resection because of significant vascular involvement. Stereotactic body radiation therapy and chemotherapy are the treatments recommended by the National Comprehensive Cancer Network criteria. For patients who do not respond to or tolerate stereotactic body radiation therapy and/or chemotherapy, a new option is irreversible electroporation. Irreversible electroporation is a nonthermal minimally invasive ablation technique that uses electrical pulses to induce apoptosis of tumor cells without damage to the extracellular matrix, thus preserving ducts and vessels. Irreversible electroporation requires very precise needle placement, which has limited its ubiquitous use. Intraprocedural cone-beam computed tomography with navigation can be fused with previous imaging to provide real-time tumor navigation capabilities during the procedure to allow for more accurate needle placement and treatment. Here, we present a patient who underwent percutaneous irreversible electroporation with intraprocedural cone-beam computed tomography fusion guidance to treat his pancreatic cancer., Case Presentation: The patient, an 88-year-old White male, initially presented with abdominal pain, and was ultimately diagnosed with locally advanced pancreatic cancer. He has an excellent performance status and no other comorbidities. He was started on chemotherapy and radiation therapy, with good response. However, continued vascular involvement of the tumors precluded him from safe surgical resection. The patient underwent irreversible electroporation with intraprocedural cone-beam computed tomography fusion navigation. The primary lesion demonstrates no residual tumor, and the soft tissue involvement of the adjacent vasculature has stabilized., Conclusions: Although not curative on its own, irreversible electroporation holds promise as a treatment option for patients with locally advanced pancreatic cancer to increase downsizing to curative surgery or increase quality of life. Cone-beam computed tomography navigation can improve irreversible electroporation by providing guidance during needle guidance. Image fusion with previous advanced imaging can improve lesion visualization and targeting, thereby improving the effectiveness of irreversible electroporation., (© 2021. The Author(s).)

Background: Renal-cell carcinoma is the most common kidney cancer and the 13th most common cause of cancer death worldwide. Partial nephrectomy and percutaneous ablation, increasingly utilized to treat small renal masses and preserve renal parenchyma, require precise preoperative imaging interpretation. We sought to develop and evaluate a convolutional neural network (CNN), a type of deep learning (DL) artificial intelligence (AI), to act as a surgical planning aid by determining renal tumor and kidney volumes through segmentation on single-phase CT. Materials and Methods: After Institutional Review Board approval, the CT images of 319 patients were retrospectively analyzed. Two distinct CNNs were developed for (1) bounding cube localization of the right and left hemiabdomen and (2) segmentation of the renal parenchyma and tumor within each bounding cube. Training was performed on a randomly selected cohort of 269 patients. CNN performance was evaluated on a separate cohort of 50 patients using Sorensen-Dice coefficients (which measures the spatial overlap between the manually segmented and neural network-derived segmentations) and Pearson correlation coefficients. Experiments were run on a graphics processing unit-optimized workstation with a single NVIDIA GeForce GTX Titan X (12GB, Maxwell Architecture). Results: Median Dice coefficients for kidney and tumor segmentation were 0.970 and 0.816, respectively; Pearson correlation coefficients between CNN-generated and human-annotated estimates for kidney and tumor volume were 0.998 and 0.993 ( p  < 0.001), respectively. End-to-end trained CNNs were able to perform renal parenchyma and tumor segmentation on a new test case in an average of 5.6 seconds. Conclusions: Initial experience with automated DL AI demonstrates that it is capable of rapidly and accurately segmenting kidneys and renal tumors on single-phase contrast-enhanced CT scans and calculating tumor and renal volumes.

Minimally invasive alternatives to traditional prostate surgery are increasingly utilized to treat benign prostatic hyperplasia and localized prostate cancer in select patients. Advantages of these treatments over prostatectomy include lower risk of complication, shorter length of hospital stay, and a more favorable safety profile. Multiparametric magnetic resonance imaging (mpMRI) has become a widely accepted imaging modality for evaluation of the prostate gland and provides both anatomical and functional information. As prostate mpMRI and minimally invasive prostate procedure volumes increase, it is important for radiologists to be familiar with normal post-procedure imaging findings and potential complications. This paper reviews the indications, procedural concepts, common post-procedure imaging findings, and potential complications of prostatic artery embolization, prostatic urethral lift, irreversible electroporation, photodynamic therapy, high-intensity focused ultrasound, focal cryotherapy, and focal laser ablation., (© 2021. This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.)

Purpose: Computerized tomographic urography is the diagnostic tool of choice for evaluating hematuria. In keeping with the ALARA (As Low As Reasonably Achievable) principle, we evaluated a triple bolus computerized tomography protocol designed to reduce radiation exposure., Materials and Methods: Patients with macroscopic or microscopic hematuria were prospectively randomized to conventional computerized tomography (100) or triple bolus computerized tomography (100). The triple bolus computerized tomography protocol entails 2 scans: pre-contrast scan followed by 3 contrast injections at 40 seconds, 60 seconds and 20 minutes prior to the second scan to capture all 3 phases. The conventional computerized tomography protocol requires 4 scans: pre-contrast scan, and 3 post-contrast scans at the corticomedullary, nephrographic and excretory phases. Radiation exposure and the detection of urological pathology were recorded based on radiology reports., Results: There were no differences in patient demographics or body mass index between the 2 groups. Triple bolus computerized tomography exposed patients to 33% less radiation (1,715 vs 1,145 mGy*cm for conventional vs triple bolus computerized tomography; p <0.001). For macroscopic hematuria, the pathology detection rates were 70% for triple bolus and 73% for conventional computerized tomography (p=0.72). For microscopic hematuria, the detection rates were 59% for triple bolus and 50% for conventional computerized tomography (p=0.68). In both groups, the rates of detection of urolithiasis, renal cysts, urological masses, bladder pathology and prostate pathology were no different between triple bolus and conventional computerized tomography., Conclusions: In both the settings of macroscopic and microscopic hematuria evaluation, triple bolus computerized tomography significantly reduces radiation exposure while providing equivalent detection of genitourinary pathology compared to conventional computerized tomography. The ability to detect upper tract filling defects was not specifically tested.

Background: Jejunal lymphatic malformations are congenital lesions that are seldom diagnosed in adults and rarely seen on imaging., Case Presentation: A 61-year-old Caucasian woman was initially diagnosed and treated for mucinous ovarian carcinoma. After an exploratory laparotomy with left salpingo-oophorectomy, a computed tomography scan of the abdomen and pelvis demonstrated suspicious fluid-containing lesions involving a segment of jejunum and adjacent mesentery. Resection of the lesion during subsequent debulking surgery revealed that the lesion seen on imaging was a jejunal lymphatic malformation and not a cancerous implant., Conclusions: Abdominal lymphatic malformations are difficult to diagnose solely on imaging but should remain on the differential in adult cancer patients with persistent cystic abdominal lesions despite chemotherapy and must be differentiated from metastatic implants.

Purpose To develop a deep learning model to delineate the transition zone (TZ) and peripheral zone (PZ) of the prostate on MR images. Materials and Methods This retrospective study was composed of patients who underwent a multiparametric prostate MRI and an MRI/transrectal US fusion biopsy between January 2013 and May 2016. A board-certified abdominal radiologist manually segmented the prostate, TZ, and PZ on the entire data set. Included accessions were split into 60% training, 20% validation, and 20% test data sets for model development. Three convolutional neural networks with a U-Net architecture were trained for automatic recognition of the prostate organ, TZ, and PZ. Model performance for segmentation was assessed using Dice scores and Pearson correlation coefficients. Results A total of 242 patients were included (242 MR images; 6292 total images). Models for prostate organ segmentation, TZ segmentation, and PZ segmentation were trained and validated. Using the test data set, for prostate organ segmentation, the mean Dice score was 0.940 (interquartile range, 0.930-0.961), and the Pearson correlation coefficient for volume was 0.981 (95% CI: 0.966, 0.989). For TZ segmentation, the mean Dice score was 0.910 (interquartile range, 0.894-0.938), and the Pearson correlation coefficient for volume was 0.992 (95% CI: 0.985, 0.995). For PZ segmentation, the mean Dice score was 0.774 (interquartile range, 0.727-0.832), and the Pearson correlation coefficient for volume was 0.927 (95% CI: 0.870, 0.957). Conclusion Deep learning with an architecture composed of three U-Nets can accurately segment the prostate, TZ, and PZ. Keywords: MRI, Genital/Reproductive, Prostate, Neural Networks Supplemental material is available for this article. © RSNA, 2021.

Objective: Prostate cancer is the most commonly diagnosed cancer in men in the United States with more than 200,000 new cases in 2018. Multiparametric MRI (mpMRI) is increasingly used for prostate cancer evaluation. Prostate organ segmentation is an essential step of surgical planning for prostate fusion biopsies. Deep learning convolutional neural networks (CNNs) are the predominant method of machine learning for medical image recognition. In this study, we describe a deep learning approach, a subset of artificial intelligence, for automatic localization and segmentation of prostates from mpMRI., Materials and Methods: This retrospective study included patients who underwent prostate MRI and ultrasound-MRI fusion transrectal biopsy between September 2014 and December 2016. Axial T2-weighted images were manually segmented by two abdominal radiologists, which served as ground truth. These manually segmented images were used for training on a customized hybrid 3D-2D U-Net CNN architecture in a fivefold cross-validation paradigm for neural network training and validation. The Dice score, a measure of overlap between manually segmented and automatically derived segmentations, and Pearson linear correlation coefficient of prostate volume were used for statistical evaluation., Results: The CNN was trained on 299 MRI examinations (total number of MR images = 7774) of 287 patients. The customized hybrid 3D-2D U-Net had a mean Dice score of 0.898 (range, 0.890-0.908) and a Pearson correlation coefficient for prostate volume of 0.974., Conclusion: A deep learning CNN can automatically segment the prostate organ from clinical MR images. Further studies should examine developing pattern recognition for lesion localization and quantification.

Purpose: The coronavirus disease 2019 (COVID-19) pandemic has led to significant disruptions in the healthcare system including surges of infected patients exceeding local capacity, closures of primary care offices, and delays of non-emergent medical care. Government-initiated measures to decrease healthcare utilization (i.e., "flattening the curve") have included shelter-in-place mandates and social distancing, which have taken effect across most of the USA. We evaluate the immediate impact of the Public Health Messaging and shelter-in-place mandates on Emergency Department (ED) demand for radiology services., Methods: We analyzed ED radiology volumes from the five University of California health systems during a 2-week time period following the shelter-in-place mandate and compared those volumes with March 2019 and early April 2019 volumes., Results: ED radiology volumes declined from the 2019 baseline by 32 to 40% (p < 0.001) across the five health systems with a total decrease in volumes across all 5 systems by 35% (p < 0.001). Stratifying by subspecialty, the smallest declines were seen in non-trauma thoracic imaging, which decreased 18% (p value < 0.001), while all other non-trauma studies decreased by 48% (p < 0.001)., Conclusion: Total ED radiology demand may be a marker for public adherence to shelter-in-place mandates, though ED chest radiology demand may increase with an increase in COVID-19 cases.

Objectives: To assess the utility of multiparametric MRI in detecting clinically significant prostate cancer (csPCa) by comparing PI-RADSv2 scores with International Society of Urological Pathology (ISUP) pathologic grading criteria., Methods: Data from 137 patients were retrospectively analyzed. PI-RADSv2 scores were compared with pathologic grade using ISUP criteria. Pathologic grades were divided into clinically significant (groups 3-5) and clinically insignificant lesions (groups 1-2). Chi-squared analysis was performed for to assess correlation., Results: Sensitivity and specificity of PI-RADSv2 score 3-5 lesions for detecting csPCa was 100% and 18.5%, respectively. Negative predictive value (NPV) is 100% for these lesions. When considering only PI-RADSv2 score 4-5 lesions, sensitivity decreases to 90% and specificity increases to 67.5%, with a NPV of 98.5%. When only PI-RADSv2 score 5 lesions are considered, sensitivity decreases to 50% and specificity increases to 90%, with a NPV of 95%., Conclusions: Multiparametric MRI has excellent sensitivity for detecting csPCa. Specificity is poor for PI-RADSv2 score 3 lesions but improves significantly for PI-RADSv2 score 4 and 5 lesions. Overall, mpMRI is an excellent screening tool for csPCa, as designated by the recently validated ISUP criteria., Advances in Knowledge: Multiple limitations of the longstanding Gleason pathologic scoring system have led to the development of new ISUP pathologic criteria, which is more focused on the clinical significance of lesions. There are currently insufficient studies evaluating and validating the ISUP criteria with PIRADS v2 evaluation of the prostate., (Copyright © 2019 Elsevier Inc. All rights reserved.)

A 19-year-old G1 at 37 weeks presented with acute non-ruptured appendicitis. Her advanced gestational age and surgical anatomy presented a complex surgical scenario. She was treated with intravenous antibiotics and induction of labour, which resulted in resolution of the appendicitis and an uncomplicated vaginal delivery at early term. This case is an example that appendicitis occurring in early-term pregnancy can be successfully managed with intravenous antibiotics, but this is a complex clinical scenario with a limited evidence base to make management decisions. Future studies of medical management of appendicitis in pregnancy, specifically in later gestation, are needed to provide additional information to guide clinicians., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Background Prostate MRI is used widely in clinical care for guiding tissue sampling, active surveillance, and staging. The Prostate Imaging Reporting and Data System (PI-RADS) helps provide a standardized probabilistic approach for identifying clinically significant prostate cancer. Despite widespread use, the variability in performance of prostate MRI across practices remains unknown. Purpose To estimate the positive predictive value (PPV) of PI-RADS for the detection of high-grade prostate cancer across imaging centers. Materials and Methods This retrospective cross-sectional study was compliant with the HIPAA. Twenty-six centers with members in the Society of Abdominal Radiology Prostate Cancer Disease-focused Panel submitted data from men with suspected or biopsy-proven untreated prostate cancer. MRI scans were obtained between January 2015 and April 2018. This was followed with targeted biopsy. Only men with at least one MRI lesion assigned a PI-RADS score of 2-5 were included. Outcome was prostate cancer with Gleason score (GS) greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2). A mixed-model logistic regression with institution and individuals as random effects was used to estimate overall PPVs. The variability of observed PPV of PI-RADS across imaging centers was described by using the median and interquartile range. Results The authors evaluated 3449 men (mean age, 65 years ± 8 [standard deviation]) with 5082 lesions. Biopsy results showed 1698 cancers with GS greater than or equal to 3+4 (International Society of Urological Pathology grade group ≥2) in 2082 men. Across all centers, the estimated PPV was 35% (95% confidence interval [CI]: 27%, 43%) for a PI-RADS score greater than or equal to 3 and 49% (95% CI: 40%, 58%) for a PI-RADS score greater than or equal to 4. The interquartile ranges of PPV at these same PI-RADS score thresholds were 27%-44% and 27%-48%, respectively. Conclusion The positive predictive value of the Prostate Imaging and Reporting Data System was low and varied widely across centers. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Milot in this issue.

Prostate carcinoma is one of the most prevalent cancers worldwide. Multiparametric magnetic resonance imaging (mpMRI) is a non-invasive tool that can improve prostate lesion detection, classification, and volume quantification. Machine learning (ML), a branch of artificial intelligence, can rapidly and accurately analyze mpMRI images. ML could provide better standardization and consistency in identifying prostate lesions and enhance prostate carcinoma management. This review summarizes ML applications to prostate mpMRI and focuses on prostate organ segmentation, lesion detection and segmentation, and lesion characterization. A literature search was conducted to find studies that have applied ML methods to prostate mpMRI. To date, prostate organ segmentation and volume approximation have been well executed using various ML techniques. Prostate lesion detection and segmentation are much more challenging tasks for ML and were attempted in several studies. They largely remain unsolved problems due to data scarcity and the limitations of current ML algorithms. By contrast, prostate lesion characterization has been successfully completed in several studies because of better data availability. Overall, ML is well situated to become a tool that enhances radiologists' accuracy and speed.

Purpose: Use of magnetic resonance imaging (MRI)/transrectal ultrasound fusion biopsies to determine the accuracy of multiparametric MRI (mpMRI), using Prostate Imaging-Reporting and Data System version 2 (PI-RADSv2), for detecting clinically significant prostate cancer in the overall gland and specifically the peripheral zone (PZ) and transitional zone (TZ)., Methods: A retrospective analysis of patients who underwent fusion biopsy identified 137 men with 231 prostate lesions was approved by the Institutional Review Board. Subjects initially classified under PI-RADSv1 criteria were regraded using PI-RADSv2 by a radiologist blinded to PI-RADSv1 score and biopsy results. Spearman correlation, chi-squared, and logistic regression analysis were performed., Results: There was positive correlation between PI-RADSv2 and Gleason scores (P < 0.001). In the PZ, mpMRI demonstrated 100% sensitivity, 100% negative predictive value, and 35.9% positive predictive value, compared to 100%, 100%, and 27.1%, respectively, for TZ lesions. When predicting clinically significant prostate cancer, the PI-RADSv2 area under the curve for TZ lesions was 0.844 (95% CI: 0.753-0.935, P < 0.001) and 0.769 (95% CI: 0.684-0.854, P < 0.001) for PZ lesions. Combining PI-RADSv2 with additional risk factors (body mass index, prostate-specific antigen density, digital rectal examination) improved the area under curve., Conclusions: PI-RADSv2 achieves excellent sensitivity and negative predictive value for both PZ and TZ lesions., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Objective: The aim of this study is to evaluate the utility of quantitative apparent diffusion coefficient (ADC) measurements and normalized ADC ratios in multiparametric MRI for the diagnosis of clinically significant peripheral zone (PZ) prostate cancer particularly among equivocally suspicious prostate lesions., Methods: A retrospective analysis of 95 patients with PZ lesions by PI-RADSv2 criteria, and who underwent subsequent MRI-US fusion biopsy, was approved by an institutional review board. Two radiologists independently measured ADC values in regions of interest (ROIs) of PZ lesions and calculated normalized ADC ratio based on ROIs in the bladder lumen. Diagnostic performance was evaluated using ROC. Inter observer variability was assessed using intraclass correlation coefficient (ICC)., Results: Mean ADC and normalized ADC ratios for clinically significant and non-clinically significant lesions were 0.763 × 10-3 mm 2  s -1 , 29.8%; and 1.135 × 10-3 mm 2  s -1 , 47.2% (p < 0.001), respectively. Area under the ROC curve (AUC) was 0.880 [95% CI (0.816-0.944) and 0.885 (95% CI (0.814-0.955)] for ADC and ADC ratio, respectively. Optimal AUC threshold for ADC was 0.843 × 10-3 mm 2  s -1 (Sn 70.5%, Sp 88.2%) and for normalized ADC was 33.1% (Sn 75.0%, Sp 95.7%). intraclass correlation coefficient was high at 0.889., Conclusion: Quantitative ADC measurement in PZ prostate lesions demonstrates excellent diagnostic performance in differentiating clinically significant from non-clinically significant prostate cancer with high inter observer correlation. Advances In knowledge: Quantitative ADC is presented as an additional method to evaluate lesions in mpMRI of the prostate. This technique may be incorporated in new and existing methods to improve detection and discrimination of clinically significant prostate cancer.

The terms composite and collision tumors have been used interchangeably throughout radiological literature. Both composite and collision tumors involve two morphologically and immunohistochemically distinct neoplasms coexisting within a single organ. However, collision tumors lack the histological cellular intermingling seen in composite tumors. Composite tumors often arise from a common driver mutation that induces a divergent histology from a common neoplastic source while collision tumors may arise from coincidental neoplastic change. The purpose of this review is to provide an overview of abdominal composite and collision tumors by discussing hallmark radiographic and pathological presentations of rare hepatic, renal, and adrenal case studies. A better understanding of the presentation of each lesion is imperative for proper recognition, diagnosis, and management of these unique tumor presentations.

Arteriovenous fistulae and grafts for hemodialysis access are a lifeline in patients with end-stage renal disease. A significant cause of morbidity and mortality in this population is dialysis access dysfunction. Duplex ultrasound imaging is an excellent modality to evaluate arteriovenous fistulae and grafts, the 2 main types of long-term hemodialysis access. This review provides a detailed Doppler ultrasound protocol for evaluation of fistulae or grafts to familiarize imagers with their normal appearance, highlighting common dialysis access complications., (Copyright © 2016 Elsevier Inc. All rights reserved.)