Risk of malignancy in T1-hyperintense Bosniak version 2019 class II and IIF cystic renal masses.

BACKGROUND: Bosniak classification version 2019 includes cystic masses in class II and IIF based partly on their hyperintense appearance at T1-weighted MRI. The prevalence of malignancy in non-enhancing heterogeneously T1-hyperintense masses is unknown, nor whether the pattern of T1 hyperintensity affects malignancy likelihood. PURPOSE: To determine the malignancy proportion among six patterns of T1 hyperintensity within non-enhancing cystic renal masses. METHODS: This retrospective, single-institution study included 72 Bosniak class II and IIF, non-enhancing, T1-hyperintense cystic renal masses. Diagnosis was confirmed by histopathology or by follow-up imaging demonstrating 5-year size and morphologic stability, decreased in size by ≥ 30%, resolution, or Bosniak down-classification. Six patterns of T1 hyperintensity were pre-defined: homogeneous (pattern A), fluid-fluid level (pattern B), peripherally markedly T1-hyperintense (pattern C), containing a T1-hyperintense non-enhancing nodule (pattern D), peripherally T1-hypointense (pattern E), and heterogeneously T1-hyperintense without a distinct pattern (pattern F). Three readers independently assigned each mass to a pattern. Individual and mean malignancy proportion were determined. Mann-Whitney test and Fischer's exact test compared the likelihood of malignancy between patterns. Inter-reader agreement was analyzed with Gwet's agreement coefficient (AC). RESULTS: Among 72 masses, the mean number of masses assigned was 11 (15%) to pattern A, 21 (29%) to pattern B, 6 (8%) to pattern C, 7 (10%) to pattern D, 5 (7%) to pattern E, and 22 (31%) to pattern F. Five of 72 masses (7%) were malignant; none was assigned pattern A, B, or D. Mean malignancy proportion was 5% (0/9, 1/6, and 0/4) for pattern C, 13% (0/4, 1/3, and 1/7) for pattern E, and 18% (5/20, 3/21, and 4/25) for pattern F. Malignant masses were more likely assigned to pattern E or F (p = 0.003-0.039). Inter-reader agreement was substantial (Gwet's AC: 0.68). CONCLUSION: Bosniak version 2019 class IIF masses that are non-enhancing and heterogeneously T1-hyperintense with a fluid-fluid level are likely benign. Those that are non-enhancing and heterogeneously T1-hyperintense without a distinct pattern have a malignancy proportion up to 25% (5/20).

External Validation of a Five-Tiered CT Algorithm for the Diagnosis of Clear Cell Renal Cell Carcinoma: A Retrospective Five-Reader Study.

BACKGROUND. In 2022, a five-tiered CT algorithm was proposed for predicting whether a small (cT1a) solid renal mass represents clear cell renal cell carcinoma (ccRCC). OBJECTIVE. The purpose of this external validation study was to evaluate the proposed CT algorithm for diagnosis of ccRCC among small solid renal masses. METHODS. This retrospective study included 93 patients (median age, 62 years; 42 women, 51 men) with 97 small solid renal masses that were seen on corticomedullary phase contrast-enhanced CT performed between January 2012 and July 2022 and subsequently underwent surgical resection. Five readers (three attending radiologists, two clinical fellows) independently evaluated masses for the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score; these scores were used to derive the CT score by use of the previously proposed CT algorithm. The CT score's sensitivity, specificity, and PPV for ccRCC were calculated at threshold of 4 or greater, and the NPV for ccRCC was calculated at a threshold of 3 or greater (consistent with thresholds in studies of the MRI-based clear cell likelihood score and the CT algorithm's initial study). The CT score's sensitivity and specificity for papillary RCC were calculated at a threshold of 2 or less. Interreader agreement was assessed using the Gwet agreement coefficient (AC1). RESULTS. Overall, 61 of 97 masses (63%) were malignant and 43 of 97 (44%) were ccRCC. Across readers, CT score had sensitivity ranging from 47% to 95% (pooled sensitivity, 74% [95% CI, 68-80%]), specificity ranging from 19% to 83% (pooled specificity, 59% [95% CI, 52-67%]), PPV ranging from 48% to 76% (pooled PPV, 59% [95% CI, 49-71%]), and NPV ranging from 83% to 100% (pooled NPV, 90% [95% CI, 84-95%]), for ccRCC. A CT score of 2 or less had sensitivity ranging from 44% to 100% and specificity ranging from 77% to 98% for papillary RCC (representing nine of 97 masses). Interreader agreement was substantial for attenuation score (AC1 = 0.70), poor for heterogeneity score (AC1 = 0.17), fair for five-tiered CT score (AC1 = 0.32), and fair for dichotomous CT score at a threshold of 4 or greater (AC1 = 0.24 [95% CI, 0.14-0.33]). CONCLUSION. The five-tiered CT algorithm for evaluation of small solid renal masses was tested in an external sample and showed high NPV for ccRCC. CLINICAL IMPACT. The CT algorithm may be used for risk stratification and patient selection for active surveillance by identifying patients unlikely to have ccRCC.

Deep learning of chest X-rays can predict mechanical ventilation outcome in ICU-admitted COVID-19 patients.

The COVID-19 pandemic repeatedly overwhelms healthcare systems capacity and forced the development and implementation of triage guidelines in ICU for scarce resources (e.g. mechanical ventilation). These guidelines were often based on known risk factors for COVID-19. It is proposed that image data, specifically bedside computed X-ray (CXR), provide additional predictive information on mortality following mechanical ventilation that can be incorporated in the guidelines. Deep transfer learning was used to extract convolutional features from a systematically collected, multi-institutional dataset of COVID-19 ICU patients. A model predicting outcome of mechanical ventilation (remission or mortality) was trained on the extracted features and compared to a model based on known, aggregated risk factors. The model reached a 0.702 area under the curve (95% CI 0.707-0.694) at predicting mechanical ventilation outcome from pre-intubation CXRs, higher than the risk factor model. Combining imaging data and risk factors increased model performance to 0.743 AUC (95% CI 0.746-0.732). Additionally, a post-hoc analysis showed an increase performance on high-quality than low-quality CXRs, suggesting that using only high-quality images would result in an even stronger model.

Tracking and predicting COVID-19 radiological trajectory on chest X-rays using deep learning.

Radiological findings on chest X-ray (CXR) have shown to be essential for the proper management of COVID-19 patients as the maximum severity over the course of the disease is closely linked to the outcome. As such, evaluation of future severity from current CXR would be highly desirable. We trained a repurposed deep learning algorithm on the CheXnet open dataset (224,316 chest X-ray images of 65,240 unique patients) to extract features that mapped to radiological labels. We collected CXRs of COVID-19-positive patients from an open-source dataset (COVID-19 image data collection) and from a multi-institutional local ICU dataset. The data was grouped into pairs of sequential CXRs and were categorized into three categories: 'Worse', 'Stable', or 'Improved' on the basis of radiological evolution ascertained from images and reports. Classical machine-learning algorithms were trained on the deep learning extracted features to perform immediate severity evaluation and prediction of future radiological trajectory. Receiver operating characteristic analyses and Mann-Whitney tests were performed. Deep learning predictions between "Worse" and "Improved" outcome categories and for severity stratification were significantly different for three radiological signs and one diagnostic ('Consolidation', 'Lung Lesion', 'Pleural effusion' and 'Pneumonia'; all P < 0.05). Features from the first CXR of each pair could correctly predict the outcome category between 'Worse' and 'Improved' cases with a 0.81 (0.74-0.83 95% CI) AUC in the open-access dataset and with a 0.66 (0.67-0.64 95% CI) AUC in the ICU dataset. Features extracted from the CXR could predict disease severity with a 52.3% accuracy in a 4-way classification. Severity evaluation trained on the COVID-19 image data collection had good out-of-distribution generalization when testing on the local dataset, with 81.6% of intubated ICU patients being classified as critically ill, and the predicted severity was correlated with the clinical outcome with a 0.639 AUC. CXR deep learning features show promise for classifying disease severity and trajectory. Once validated in studies incorporating clinical data and with larger sample sizes, this information may be considered to inform triage decisions.

Prophylactic retromuscular mesh placement for parastomal hernia prevention: a retrospective cohort study of permanent colostomies and ileostomies.

PURPOSE: Parastomal hernia (PSH) is the most common complication of stoma formation. The safety and efficiency of prophylactically placing mesh to prevent PSH remain controversial. To address this question, we examined the incidence of clinical and radiological PSH when using parastomal prophylactic mesh (PPM). METHODS: We performed a retrospective, single-center, cohort study that included all patients with permanent stoma creation between 2015 and 2018. Patients were divided into two groups according to the utilization of PPM or not. RESULTS: During the study period, 185 patients had a permanent stoma created, 144 with colostomy and 41 with ileostomy. PPM was placed in 79 patients. There was no difference in the need for early surgical reintervention (p = 0.652) or rehospitalization (p = 0.314) for stoma-related complications in patients with mesh as compared with patients without. Similarly, there was no difference in operative time (p = 0.782) or in length of hospital stay (p = 0.806). No patients experienced infection of the mesh or required prosthesis removal. There was a lower incidence rate of PSH with PPM placement in patients with permanent colostomy [adjusted hazard ratio (HR) 0.50 (95% confidence interval 0.28-0.89); p = 0.018]. In contrast, a higher incidence rate of PSH was observed in patients with ileostomy and PPM [adjusted HR 5.92 (95% confidence interval 1.07-32.65); p = 0.041]. CONCLUSION: Parastomal prophylactic mesh placement to prevent PSH is a safe and efficient approach to reduce the incidence of PSH in patients requiring a permanent colostomy. However, mesh may increase the rate of PSH after permanent ileostomy.

Ultrasound-guided transthoracic needle biopsy of the lung: sensitivity and safety variables.

OBJECTIVES: Variables affecting the performance of ultrasound-guided transthoracic needle biopsy (US-TTNB) are not well established. We examined clinical and imaging variables affecting the sensitivity and the complication rates of US-TTNB. METHODS: We retrospectively reviewed a consecutive series of 528 US-TTNBs performed from 2008 to 2017. Univariate analyses were used to assess the influence of clinical and imaging variables on sensitivity and complication rates. Multivariate logistic regression was used to account for possible confounding variables. RESULTS: In 397 malignant lesions, the sensitivity of US-TTNB was 72% (95% CI 68-77%; 285/397). The overall pneumothorax rate was 15% (95% CI 12-18%; 77/528), leading to a chest tube in 2% (95% CI 1-3%; 9/528). Multivariate analysis showed that increasing pleural contact length (up to 30 mm) was associated with increased sensitivity (OR 1.08 per mm; 95% CI 1.04-1.12; p < 0.001), and pleural contact length (OR 0.98 per mm; 95% CI 0.97-0.99; p = 0.013), lesion size (OR 0.98 per mm; 95% CI 0.96-0.99; p = 0.006), and core needle diameter of 18G (OR 0.47 as compared with 20G; 95% CI 0.26-0.83; p = 0.010) were associated with a decreased pneumothorax rate. Graphical inspection of cubic splines showed that the probability of a positive biopsy rose sharply with increasing pleural contact length up to 30 mm and was stable thereafter. A similar, but inverse, relationship was observed for the probability of a pneumothorax. CONCLUSION: Pleural contact length is a key variable predicting the sensitivity of US-TTNB and pneumothorax rate after US-TTNB. Lesion size also predicts pneumothorax rates. KEY POINTS: • US-TTNB has a high sensitivity and a low complication rate for pleural and pulmonary lesions with pleural contact. • Pleural contact length is a key variable predicting the sensitivity of US-TTNB and pneumothorax rate after US-TTNB. • This study suggests that relying on US-TTNB may not be optimal for lesions < 10 mm for which the risk of pneumothorax is as high as the chance of obtaining diagnosis.

The role of radiological classification of parastomal hernia as a predictor of the need for surgical hernia repair: a retrospective cohort study.

PURPOSE: Parastomal hernia (PSH) is a frequent complication of stoma creation during colorectal surgery. Radiological classification systems have been proposed for PSH but are primarily used for research. Our objective was to determine if PSH radiological classification at diagnosis could predict the need for surgical repair during follow-up. METHODS: In this retrospective cohort study, we reviewed 705 postoperative CT scans from 154 patients with permanent stoma creation from 2015 to 2018. Patients were included for analysis if a primary PSH was diagnosed on any exam. PSH were classified according to the European Hernia Society (EHS) and Moreno-Matias (MM) classification systems. RESULTS: The incidence of radiological PSH was 41% (63/154) after a median radiological follow-up of 19.2 months (interquartile range, 10.9-32.9). Surgical repair was required in 17 of 62 patients with a primary PSH. There was no significant correlation between PSH classification and surgical hernia repair for either the EHS (p = 0.56) or MM classification systems (p = 0.35) in a univariate analysis. However, in a multivariate analysis, the type of PSH according to the EHS classification was significantly correlated with PSH repair during follow-up (p = 0.02). Type III PSH were associated with a lower incidence of surgical hernia repair as compared with type I, with a hazard ratio (HR) of 0.01 (95% CI, <0.00-0.20). A similar correlation was not seen using the MM classification (p = 0.10). CONCLUSION: EHS classification of PSH was significant correlated with the need for surgical repair during short-term follow-up. Prospective studies are required to establish a potential role in patient care.

Effect of Yttrium-90 transarterial radioembolization in patients with non-surgical hepatocellular carcinoma: A systematic review and meta-analysis.

BACKGROUND: Recently, the use of Yttrium-90 transarterial radioembolization in non-surgical hepatocellular carcinoma was suggested but the evidence supporting its use is unclear. METHODS: We searched Medline, Embase, Web of Science and Cochrane CENTRAL from inception up to April 14, 2020 for randomized controlled trials comparing Y90-TARE to standard of care in non-surgical HCC patients. Our primary outcome was overall survival (OS). Our secondary outcomes were progression-free survival, time to progression, disease control rate, grade ≥3 adverse events and rates of gastro-intestinal ulcers. Hazard ratios (HR) and risk ratios (RR) with random-effects model were used for our analyses. The risk of bias of the included studies was assessed using Cochrane's RoB 2 tool. RESULTS: Of 1,604 citations identified, eight studies (1,439 patients) were included in our analysis. No improvement in overall survival were noted when Yttrium-90 transarterial radioembolization was compared to standard treatments (HR 0.99 [95% CI 0.81-1.21], 6 studies, I2 = 77.6%). However, Yttrium-90 transarterial radioembolization was associated with fewer grade ≥3 adverse events (RR 0.64 [95% CI 0.45-0.92], 7 studies, I2 = 66%). No difference was observed on other secondary outcomes. DISCUSSION: In non-surgical HCC patients, Yttrium-90 transarterial radioembolization was not associated with significant effect on survival, progression-free survival, time to progression, disease control rate and the incidence of gastro-intestinal ulcers but was however associated with significantly lower rates of grade ≥3 adverse events. Further randomized controlled trials are warranted to better delineate optimal treatment.

Management of retroperitoneal hemorrhage compressing the inferior vena cava in a patient with a renal transplant: A case report.

We report a case of a right retroperitoneal hematoma compressing the inferior vena cava (IVC) in a patient with a left pelvic renal transplant. Noncontrast abdominal computed tomography scan diagnosed the cause of the hematoma, which was a ruptured nontraumatic renal cyst hemorrhage from the right native kidney. The patient had been anticoagulated for 5 days to treat pulmonary embolism upon clinical presentation. To minimize the risk of venous renal transplant thrombosis and to resume anticoagulation as fast as possible without the need of a long-term IVC filter, priority in management was to relieve the IVC compression and to stop the hemorrhage by selective embolization of the right native kidney. This case report will review the clinical presentation, the radiological findings and the management of retroperitoneal hematoma compressing the IVC in a patient with renal transplant.