Magnetic Resonance Imaging Prognostic Findings for Visual and Mortality Outcomes in Acute Invasive Fungal Rhinosinusitis.

PURPOSE: To identify initial, preintervention magnetic resonance imaging (MRI) findings that are predictive of visual and mortality outcomes in acute invasive fungal rhinosinusitis (AIFRS). DESIGN: Retrospective cohort study. PARTICIPANTS: Patients with histopathologically or microbiologically confirmed AIFRS cared for at a single, tertiary academic institution between January 2000 and February 2020. METHODS: A retrospective review of MRI scans and clinical records of patients with confirmed diagnosis of AIFRS was performed. For each radiologic characteristic, a modified Poisson regression with robust standard errors was used to estimate the risk ratio for blindness. A multivariate Cox proportional hazards model was used to study AIFRS-specific risk factors associated with mortality. MAIN OUTCOME MEASURE: Identification of initial, preintervention MRI findings associated with visual and mortality outcomes. RESULTS: The study comprised 78 patients (93 orbits, 63 with unilateral disease and 15 with bilateral disease) with AIFRS. The leading causes of immunosuppression were hematologic malignancy (38%) and diabetes mellitus (36%). Mucormycota constituted 56% of infections, and Ascomycota constituted 37%. The overall death rate resulting from infection was 38%. Risk factors for poor visual acuity outcomes on initial MRI included involvement of the orbital apex (relative risk [RR], 2.0; 95% confidence interval [CI], 1.1-3.8; P = 0.026) and cerebral arteries (RR, 1.8; 95% CI, 1.3-2.5; P < 0.001). Increased mortality was associated with involvement of the facial soft tissues (hazard ratio [HR], 4.9; 95% CI, 1.3-18.2; P = 0.017), nasolacrimal drainage apparatus (HR, 5.0; 95% CI, 1.5-16.1; P = 0.008), and intracranial space (HR, 3.5; 95% CI, 1.4-8.6; P = 0.006). Orbital soft tissue involvement was associated with decreased mortality (HR, 0.3; 95% CI, 0.1-0.6; P = 0.001). CONCLUSIONS: Extrasinonasal involvement in AIFRS typically signals advanced infection with the facial soft tissues most commonly affected. The initial, preintervention MRI is prognostic for a poor visual acuity outcome when orbital apex or cerebral arterial involvement, or both, are present. Facial soft tissues, nasolacrimal drainage apparatus, intracranial involvement, or a combination thereof is associated with increased mortality risk, whereas orbital soft tissue involvement is correlated with a reduced risk of mortality.

Development and web deployment of an automated neuroradiology MRI protocoling tool with natural language processing.

BACKGROUND: A systematic approach to MRI protocol assignment is essential for the efficient delivery of safe patient care. Advances in natural language processing (NLP) allow for the development of accurate automated protocol assignment. We aim to develop, evaluate, and deploy an NLP model that automates protocol assignment, given the clinician indication text. METHODS: We collected 7139 spine MRI protocols (routine or contrast) and 990 head MRI protocols (routine brain, contrast brain, or other) from a single institution. Protocols were split into training (n = 4997 for spine MRI; n = 839 for head MRI), validation (n = 1071 for spine MRI, fivefold cross-validation used for head MRI), and test (n = 1071 for spine MRI; n = 151 for head MRI) sets. fastText and XGBoost were used to develop 2 NLP models to classify spine and head MRI protocols, respectively. A Flask-based web app was developed to be deployed via Heroku. RESULTS: The spine MRI model had an accuracy of 83.38% and a receiver operator characteristic area under the curve (ROC-AUC) of 0.8873. The head MRI model had an accuracy of 85.43% with a routine brain protocol ROC-AUC of 0.9463 and contrast brain protocol ROC-AUC of 0.9284. Cancer, infectious, and inflammatory related keywords were associated with contrast administration. Structural anatomic abnormalities and stroke/altered mental status were indicative of routine spine and brain MRI, respectively. Error analysis revealed increasing the sample size may improve performance for head MRI protocols. A web version of the model is provided for demonstration and deployment. CONCLUSION: We developed and web-deployed two NLP models that accurately predict spine and head MRI protocol assignment, which could improve radiology workflow efficiency.

Implementing Virtual and Augmented Reality Tools for Radiology Education and Training, Communication, and Clinical Care.

Advances in virtual immersive and augmented reality technology, commercially available for the entertainment and gaming industry, hold potential for education and clinical use in medicine and the field of medical imaging. Radiology departments have begun exploring the use of these technologies to help with radiology education and clinical care. The purpose of this review article is to summarize how three institutions have explored using virtual and augmented reality for radiology.

Bridging the Gender Gap in the Society of IR: A Benchmark Study.

PURPOSE: To evaluate the evolving representation of women in the Society of Interventional Radiology (SIR). MATERIALS AND METHODS: A retrospective review of the available gender demographic data of various SIR subgroups between 2008 and 2017 was performed. The gender makeup of the following groups was analyzed: SIR membership, SIR Executive Council members and officers, Annual Meeting invited speakers, committee chairs, Journal of Vascular and Interventional Radiology (JVIR) first and senior authors, JVIR editorial board, IR Quarterly (IRQ) authors, and active interventional radiology (IR) residents and fellows. RESULTS: From 2008 to 2017, the percentage of female representation in SIR members doubled (from 6% to 13.1%). In the same period, female representation also significantly increased in Executive Council members (0% to 20%) and officers (0% to 50%), SIR Annual Meeting presenters (5.1% to 15.4%), and JVIR first authors (10% to 14.5%) and senior authors (7.1% to 11.9%). From 2012 to 2017, there were increases in female representation among SIR committee chairs (21% to 28%) and IRQ authors (4.5% to 27%). However, the percentage of female IR residents and fellows did not significantly change between 2008 and 2017 (11% vs 16.2%; P = .51). CONCLUSIONS: Women interventional radiologists are underrepresented within SIR, representing only 9.2% of active IR physicians. There has been a steady increase in female representation within most areas of SIR evaluated in this study. Although these trends are reassuring, efforts toward increasing recruitment and retention of women in IR need to improve in light of the infancy of IR as a residency program.

Paraneoplastic neurologic syndrome as a presentation of underlying breast malignancy.

While breast cancer most commonly presents as a screen-detected mammographic finding or a breast symptom, in very rare instances it may first present as a paraneoplastic neurologic syndrome (PNS; Surg Case Rep, 2015;1:59; Ann Neurol 2004;56:715). Fewer than 1% of breast cancer patients have PNS, and an even smaller percentage initially present with neurologic symptoms (J Neurol Neurosurg Psychiatry, 2004;75:ii43). We report a case series of three patients who presented with neurological disorders suspicious for PNS, and were subsequently found to have underlying breast cancer. We follow this with a discussion of key clinical features of management considerations in paraneoplastic syndromes secondary to breast malignancy.

Automatic Determination of the Need for Intravenous Contrast in Musculoskeletal MRI Examinations Using IBM Watson's Natural Language Processing Algorithm.

Magnetic resonance imaging (MRI) protocoling can be time- and resource-intensive, and protocols can often be suboptimal dependent upon the expertise or preferences of the protocoling radiologist. Providing a best-practice recommendation for an MRI protocol has the potential to improve efficiency and decrease the likelihood of a suboptimal or erroneous study. The goal of this study was to develop and validate a machine learning-based natural language classifier that can automatically assign the use of intravenous contrast for musculoskeletal MRI protocols based upon the free-text clinical indication of the study, thereby improving efficiency of the protocoling radiologist and potentially decreasing errors. We utilized a deep learning-based natural language classification system from IBM Watson, a question-answering supercomputer that gained fame after challenging the best human players on Jeopardy! in 2011. We compared this solution to a series of traditional machine learning-based natural language processing techniques that utilize a term-document frequency matrix. Each classifier was trained with 1240 MRI protocols plus their respective clinical indications and validated with a test set of 280. Ground truth of contrast assignment was obtained from the clinical record. For evaluation of inter-reader agreement, a blinded second reader radiologist analyzed all cases and determined contrast assignment based on only the free-text clinical indication. In the test set, Watson demonstrated overall accuracy of 83.2% when compared to the original protocol. This was similar to the overall accuracy of 80.2% achieved by an ensemble of eight traditional machine learning algorithms based on a term-document matrix. When compared to the second reader's contrast assignment, Watson achieved 88.6% agreement. When evaluating only the subset of cases where the original protocol and second reader were concordant (n = 251), agreement climbed further to 90.0%. The classifier was relatively robust to spelling and grammatical errors, which were frequent. Implementation of this automated MR contrast determination system as a clinical decision support tool may save considerable time and effort of the radiologist while potentially decreasing error rates, and require no change in order entry or workflow.

Torsion of a giant mesocolic lipoma in a child with Bannayan-Riley-Ruvalcaba syndrome.

A 6-year-old boy with Bannayan-Riley-Ruvalcaba syndrome (BRRS) presented to the emergency department with periumbilical abdominal pain for 12 h. A contrast-enhanced abdominal and pelvis CT examination revealed significant interval change in the size and appearance of a previously seen hypoattenuating right mesocolic fatty mass suggestive for lipoma, first observed 5 months prior. This lesion demonstrated new enhancing internal septations, a thickened capsule, interval development of adjacent mesenteric fat stranding and engorgement of the mesenteric vessels. Given the short follow-up interval and acute clinical presentation, imaging findings were suggestive for torsion. We present this case for the unusual imaging findings as well as to highlight the differential diagnosis for abdominal fat containing lesions by imaging in patients with BRRS and other hamartomatous syndromes.

Herpes zoster duplex bilateralis in an immunocompetent adolescent boy: a case report and literature review.

Simultaneous involvement of herpes zoster in multiple dermatomes is uncommon, and even more so in immunocompetent individuals. We report a case wherein a healthy adolescent boy presented with herpes zoster in two distinct dermatomes, raising concern for immunodeficiency, but he was found to be immunocompetent on further testing. A 14-year-old boy with no significant past medical history developed painless vesicular eruptions in two distinct distributions. Varicella zoster virus polymerase chain reaction was positive from unroofed vesicles in both regions. Initial laboratory studies disclosed abnormalities of unknown significance in natural killer (NK) cell percentage and function. The patient was treated with appropriate antiviral therapy. Repeat studies while healthy were not suggestive of an underlying NK cell defect. There are few case reports describing herpes zoster in two or more dermatomes in children. Previously described presentations most commonly occurred in the context of primary immunodeficiency, acquired immunodeficiency, or immunosuppressive medications. Because of the rarity of this presentation in immunocompetent patients, the authors recommend a thorough immune evaluation of all children presenting with isolated multidermatomal zoster.

Classification of traumatic injury to the dural venous sinus using CT venography.

BACKGROUND AND PURPOSE: Cerebral venous sinus thrombosis (CVST) is an underrecognized cause of morbidity in acute traumatic brain injury (TBI). Radiologic diagnosis is challenging in the setting of concurrent extra-axial injury and a lack of standardized diagnostic criteria. The prevalence of traumatic thrombosis versus compression is unknown. Treatment with anticoagulation is often determined by the appropriate classification of the type of traumatic venous injury. METHODS: We developed a two-part radiologic grading method for standardized assessment of traumatic CVST based on (1) the degree of flow limitation through the affected sinus and (2) the location of venous pathology (ie, external compression vs. intrinsic thrombosis) based on computed tomography venography. We applied this grading method to a retrospective cohort of TBI patients presenting to a Level 1 Trauma center. Chart review was performed to identify potential clinical correlates. A senior neuroradiologist graded the entire cohort and a random subsample was selected for blinded rating by two independent neuroradiologists. RESULTS: Seventy-six of 221 patients were identified for inclusion after excluding nontraumatic mechanisms. Seven unique grades were employed to characterize the full extent of venous injuries. The plurality of patients from the cohort (43/76 = 43.4%) suffered compressive injuries. Inter-rater reliability was moderate for the combined grade, kappa = 0.48, p<.05, and substantial for the flow limitation component, kappa = 0.69, p<.05. CONCLUSIONS: We introduce a standardized two-part classification system for traumatic venous sinus injury with moderate-substantial inter-rater reliability. Compressive injuries were more common than thrombotic injuries. Further prospective work is needed to validate the clinical significance of this classification system.

The University of California San Francisco Brain Metastases Stereotactic Radiosurgery (UCSF-BMSR) MRI Dataset.

Supplemental material is available for this article.

Colonic injuries and the damage control abdomen: does management strategy matter?

BACKGROUND: The optimal management of colon injury patients requiring damage control laparotomy (DCL) is controversial. The objective of this study was to assess the safety of colonic resection and anastomosis versus fecal diversion in trauma patients requiring DCL. METHODS: Patients with traumatic colon injuries undergoing DCL between 2000 and 2010 were identified by the database and chart review. Those who died within 48 h were excluded. Patients were divided into two groups: those undergoing one or more colonic anastomoses with or without distal colostomy (group 1) and those undergoing colostomy only or one or more colonic anastomoses with a protecting proximal ostomy (group 2). Variables were compared using Wilcoxon rank sum, χ2, or Fisher exact tests as appropriate. RESULTS: Sixty-one patients were included (group 1, n=28 and group 2, n=33). Fascial closure rates (group 1, 50% versus group 2, 61%; P=0.45), hospital length of stay (29 versus 23 d; P=0.89), and in-patient mortality (11% versus 12%; P=1.0) were similar between groups. There were a total of 11 anastomotic leaks, five of which were related to non-colonic enteric repairs. Colonic anastomosis leak rates were 16% overall (six of the 38 patients), 14% in group 1 (four of the 28 patients), and 20% in group 2 (two of the 10 patients). Compared with patients who did not leak, patients who leaked had a higher median age (37 versus 25 y; P=0.05), greater likelihood of not achieving facial closure before post-injury day 5 (18% versus 2%; P=0.003), and a longer hospital length of stay (46 versus 25 d; P=0.003). CONCLUSIONS: Outcomes after colonic injury in the setting of DCL were similar regardless of the surgical management strategy. Based on these findings, a strategy of diversion over anastomosis cannot be strongly recommended.

Three-dimensional U-Net Convolutional Neural Network for Detection and Segmentation of Intracranial Metastases.

PURPOSE: To develop and validate a neural network for automated detection and segmentation of intracranial metastases on brain MRI studies obtained for stereotactic radiosurgery treatment planning. MATERIALS AND METHODS: In this retrospective study, 413 patients (average age, 61 years ± 12 [standard deviation]; 238 women) with a total of 5202 intracranial metastases (median volume, 0.05 cm3; interquartile range, 0.02-0.18 cm3) undergoing stereotactic radiosurgery at one institution were included (January 2017 to February 2020). A total of 563 MRI examinations were performed among the patients, and studies were split into training (n = 413), validation (n = 50), and test (n = 100) datasets. A three-dimensional (3D) U-Net convolutional network was trained and validated on 413 T1 postcontrast or subtraction scans, and several loss functions were evaluated. After model validation, 100 discrete test patients, who underwent imaging after the training and validation patients, were used for final model evaluation. Performance for detection and segmentation of metastases was evaluated using Dice scores, false discovery rates, and false-negative rates, and a comparison with neuroradiologist interrater reliability was performed. RESULTS: The median Dice score for segmenting enhancing metastases in the test set was 0.75 (interquartile range, 0.63-0.84). There were strong correlations between manually segmented and predicted metastasis volumes (r = 0.98, P < .001) and between the number of manually segmented and predicted metastases (R = 0.95, P < .001). Higher Dice scores were strongly correlated with larger metastasis volumes on a logarithmically transformed scale (r = 0.71). Sensitivity across the whole test sample was 70.0% overall and 96.4% for metastases larger than 6 mm. There was an average of 0.46 false-positive results per scan, with the positive predictive value being 91.5%. In comparison, the median Dice score between two neuroradiologists was 0.85 (interquartile range, 0.80-0.89), with sensitivity across the test sample being 87.9% overall and 98.4% for metastases larger than 6 mm. CONCLUSION: A 3D U-Net-based convolutional neural network was able to segment brain metastases with high accuracy and perform detection at the level of human interrater reliability for metastases larger than 6 mm.Keywords: Adults, Brain/Brain Stem, CNS, Feature detection, MR-Imaging, Neural Networks, Neuro-Oncology, Quantification, Segmentation© RSNA, 2021.

Uncommon malignant renal tumors and atypical presentation of common ones: a guide for radiologists.

OBJECTIVE: While the typical imaging features of the more common RCC subtypes have previously been described, they can at times have unusual, but distinguishing features. Rarer renal tumors span a broad range of imaging features, but they may also have characteristic presentations. We review the key imaging features of atypical presentations of malignant renal tumors and uncommon malignant renal tumors. CONCLUSION: Renal tumors have many different presentation patterns, but knowledge of the distinguishing MR and CT features can help identify both atypical presentation of common malignancies and uncommon renal tumors.

Adjuvant immunotherapy for non-small cell lung cancer.

Non-small cell lung cancer (NSCLC) is the biggest cancer killer in the United States and worldwide. In 2011, there are estimated to be 221,130 new cases of lung cancer in the United States. Over a million people will die of lung cancer worldwide this year alone. When possible, surgery to remove the tumor is the best treatment strategy for patients with NSCLC. However, even with adjuvant (postoperative) chemotherapy and radiation, more than 40% of patients will develop recurrences locally or systemically and ultimately succumb to their disease. Thus, there is an urgent need for developing superior approaches to treat patients who undergo surgery for NSCLC to eliminate residual disease that is likely responsible for these recurrences. Our group and others have been interested in using immunotherapy to augment the efficacy of current treatment strategies. Immunotherapy is very effective against minimal disease burden and small deposits of tumor cells that are accessible by the circulating immune cells. Therefore, this strategy may be ideally suited as an adjunct to surgery to seek and destroy microscopic tumor deposits that remain after surgery. This review describes the mechanistic underpinnings of immunotherapy and how it is currently being used to target residual disease and prevent postoperative recurrences after pulmonary resection in NSCLC.