Cancer Detection Rate and Abnormal Interpretation Rate of Prostate MRI in Patients With Low-Grade Cancer.

PURPOSE: The aim of this study was to evaluate the utility of cancer detection rate (CDR) and abnormal interpretation rate (AIR) in prostate MRI for patients with low-grade prostate cancer (PCa). METHODS: This three-center retrospective study included patients who underwent prostate MRI from 2017 to 2021 with known low-grade PCa (Gleason score 6) without prior treatment. Patient-level highest Prostate Imaging Reporting & Data System (PI-RADS®) score and pathologic diagnosis within 1 year after MRI were used to evaluate the diagnostic performance of prostate MRI in detecting clinically significant PCa (csPCa; Gleason score ≥ 7). The metrics AIR, CDR, and CDR adjusted for pathologic confirmation rate were calculated. Radiologist-level AIR-CDR plots were shown. Simulation AIR-CDR lines were created to assess the effects of different diagnostic performances of prostate MRI and the prevalence of csPCa. RESULTS: A total of 3,207 examinations were interpreted by 33 radiologists. Overall AIR, CDR, and CDR adjusted for pathologic confirmation rate at PI-RADS 3 to 5 (PI-RADS 4 and 5) were 51.7% (36.5%), 22.1% (18.8%), and 30.7% (24.6%), respectively. Radiologist-level AIR and CDR at PI-RADS 3 to 5 (PI-RADS 4 and 5) were in the 36.8% to 75.6% (21.9%-57.5%) range and the 16.3%-28.7% (10.9%-26.5%) range, respectively. In the simulation, changing parameters of diagnostic performance or csPCa prevalence shifted the AIR-CDR line. CONCLUSIONS: The authors propose CDR and AIR as performance metrics in prostate MRI and report reference performance values in patients with known low-grade PCa. There was variability in radiologist-level AIR and CDR. Combined use of AIR and CDR could provide meaningful feedback for radiologists to improve their performance by showing relative performance to other radiologists.

Cancer Detection Rate and Abnormal Interpretation Rate of Prostate MRI Performed for Clinical Suspicion of Prostate Cancer.

PURPOSE: To report cancer detection rate (CDR) and abnormal interpretation rate (AIR) in prostate MRI performed for clinical suspicion of prostate cancer (PCa). MATERIALS AND METHODS: This retrospective single-institution, three-center study included patients who underwent MRI for clinical suspicion of PCa between 2017 and 2021. Patients with known PCa were excluded. Patient-level Prostate Imaging-Reporting and Data System (PI-RADS) score was extracted from the radiology report. AIR was defined as number of abnormal MRI (PI-RADS score 3-5) / total number of MRIs. CDR was defined as number of clinically significant PCa (csPCa: Gleason score ≥7) detected at abnormal MRI / total number of MRI. AIR, CDR, and CDR adjusted for pathology confirmation rate were calculated for each of three centers and pre-MRI biopsy status (biopsy-naive and previous negative biopsy). RESULTS: A total of 9,686 examinations (8,643 unique patients) were included. AIR, CDR, and CDR adjusted for pathology confirmation rate were 45.4%, 23.8%, and 27.6% for center I; 47.2%, 20.0%, and 22.8% for center II; and 42.3%, 27.2%, and 30.1% for center III, respectively. Pathology confirmation rate ranged from 81.6% to 88.0% across three centers. AIR and CDR for biopsy-naive patients were 45.5% to 52.6% and 24.2% to 33.5% across three centers, respectively, and those for previous negative biopsy were 27.2% to 39.8% and 11.7% to 14.2% across three centers, respectively. CONCLUSION: We reported CDR and AIR in prostate MRI for clinical suspicion of PCa. CDR needs to be adjusted for pathology confirmation rate and pre-MRI biopsy status for interfacility comparison.

Preemptive Embolization of the Lumbar Arteries and Inferior Mesenteric Artery to Prevent Abdominal Aortic Aneurysm Enlargement Associated with Type 2 Endoleak Following Endovascular Aneurysm Repair.

Purpose: This study aims to evaluate the efficacy of preemptive embolization (PE) of the lumbar arteries (LAs) and inferior mesenteric artery (IMA) (PELI) for preventing abdominal aortic aneurysm (AAA) enlargement associated with type 2 endoleak (T2EL). Material and Methods: Patients who underwent endovascular aneurysm repair (EVAR) between January 2015 and December 2020 were classified into the control (without PE), IMA (PE of a patent IMA with a diameter ≥2.5 mm), and PELI (PE of patent LAs with a diameter ≥2 mm and IMA) groups. The rate of freedom from AAA enlargement following EVAR (enlargement ≥5 mm from pre-EVAR) was compared using the log-rank test. The prevalence of T2EL at 6 months and 1 year after EVAR was compared using Fisher's exact test. Results: The cumulative rates of freedom from AAA enlargement at 54 months after EVAR (maximum observational period in the PELI group) were as follows: control group, 77.5%; IMA group, 62.5%; and PELI group, 100%. The mean CT follow-up periods of the control, IMA, and PELI groups were 46.4 ± 22.3, 31.1 ± 20.6, and 22.9 ± 15.5 months, respectively. None of the 31 patients in the PELI group experienced AAA enlargement after EVAR, whereas 2 out of the 16 patients in the IMA group and 20 out of the 98 patients in the control group had AAA enlargement. No significant differences were observed in the rate of freedom from AAA enlargement (PELI group vs. IMA group, P = 0.11; PELI group vs. control group, P = 0.11). The prevalence of T2EL was significantly lower in the PELI group than in the control group at 6 months (13.6% in PELI group vs. 42.1% in control group, P = 0.02) and 1 year (14.3% in PELI group vs. 40.0% in control group, P = 0.04). Conclusions: PELI was significantly associated with a low prevalence of T2EL and may prevent T2EL-associated AAA enlargement.

Decreased prostate MRI cancer detection rate due to moderate to severe susceptibility artifacts from hip prosthesis.

OBJECTIVES: To evaluate the impact of susceptibility artifacts from hip prosthesis on cancer detection rate (CDR) in prostate MRI. MATERIALS AND METHODS: This three-center retrospective study included prostate MRI studies for patients without known prostate cancer between 2017 and 2021. Exams with hip prosthesis were searched on MRI reports. The degree of susceptibility artifact on diffusion-weighted images was retrospectively categorized into mild, moderate, and severe (> 66%, 33-66%, and < 33% of the prostate volume are evaluable) by blind reviewers. CDR was defined as the number of exams with Gleason score ≥7 detected by MRI (PI-RADS ≥3) divided by the total number of exams. For each artifact grade, control exams without hip prosthesis were matched (1:6 match), and CDR was compared. The degree of CDR reduction was evaluated with ratio, and influential factors were evaluated by expanding the equation. RESULTS: Hip arthroplasty was present in 548 (4.8%) of the 11,319 MRI exams. CDR of the cases and matched control exams for each artifact grade were as follows: mild (n = 238), 0.27 vs 0.25, CDR ratio = 1.09 [95% CI: 0.87-1.37]; moderate (n = 143), 0.18 vs 0.27, CDR ratio = 0.67 [95% CI: 0.46-0.96]; severe (n = 167), 0.22 vs 0.28, CDR ratio = 0.80 [95% CI: 0.59-1.08]. When moderate and severe artifact grades were combined, CDR ratio was 0.74 [95% CI: 0.58-0.93]. CDR reduction was mostly attributed to the increased frequency of PI-RADS 1-2. CONCLUSION: With moderate to severe susceptibility artifacts from hip prosthesis, CDR was decreased to 74% compared to the matched control. CLINICAL RELEVANCE STATEMENT: Moderate to severe susceptibility artifacts from hip prosthesis may cause a non-negligible CDR reduction in prostate MRI. Expanding indications for systematic prostate biopsy may be considered when PI-RADS 1-2 was assigned. KEY POINTS: • We proposed cancer detection rate as a diagnostic performance metric in prostate MRI. • With moderate to severe susceptibility artifacts secondary to hip arthroplasty, cancer detection rate decreased to 74% compared to the matched control. • Expanding indications for systematic prostate biopsy may be considered when PI-RADS 1-2 is assigned.

Artificial intelligence-powered software detected more than half of the liver metastases overlooked by radiologists on contrast-enhanced CT.

PURPOSE: To evaluate the sensitivity of artificial intelligence (AI)-powered software in detecting liver metastases, especially those overlooked by radiologists. METHODS: Records of 746 patients diagnosed with liver metastases (November 2010-September 2017) were reviewed. Images from when radiologists first diagnosed liver metastases were reviewed, and prior contrast-enhanced CT (CECT) images were checked for availability. Two abdominal radiologists classified the lesions into overlooked lesions (all metastases missed by radiologists on prior CECT) and detected lesions (all metastases if any of them were correctly identified and invisible on prior CECT or those with no prior CECT). Finally, images from 137 patients were identified, 68 of which were classified as "overlooked cases." The same radiologists created the ground truth for these lesions and compared them with the software's output at 2-month intervals. The primary endpoint was the sensitivity in detecting all liver lesion types, liver metastases, and liver metastases overlooked by radiologists. RESULTS: The software successfully processed images from 135 patients. The per-lesion sensitivity for all liver lesion types, liver metastases, and liver metastases overlooked by radiologists was 70.1%, 70.8%, and 55.0%, respectively. The software detected liver metastases in 92.7% and 53.7% of patients in detected and overlooked cases, respectively. The average number of false positives was 0.48 per patient. CONCLUSION: The AI-powered software detected more than half of liver metastases overlooked by radiologists while maintaining a relatively low number of false positives. Our results suggest the potential of AI-powered software in reducing the frequency of overlooked liver metastases when used in conjunction with the radiologists' clinical interpretation.

Severe TAFRO Syndrome Mimicking Hepatorenal Syndrome Successfully Treated with a Multidisciplinary Approach: A Case Report and Literature Review.

Finding the ideal balance between efficacy and safety of immunosuppression is challenging, particularly in cases of severe TAFRO syndrome. We herein report a 60-year-old man diagnosed with grade 5 TAFRO syndrome mimicking hepatorenal syndrome that was successfully treated by glucocorticoid, tocilizumab, and cyclosporin despite virus infection. Furthermore, by examining 14 peer-reviewed remission cases, we revealed that the recovery periods among inflammation, renal dysfunction, and thrombocytopenia were quite different, with recovery from thrombocytopenia notably slow. All patients requiring dialysis were successfully withdrawn from dialysis, and the reversibility from kidney injury was good. This clinical information will help clinicians plan treatments and tailor the intensity of immunosuppression.

Chest wall systemic artery-to-pulmonary artery vascular malformation treated by embolization of feeders and drainers: A case report.

A 74-year-old woman presented with progressive dyspnea. Computed tomography revealed a large systemic artery-to-pulmonary artery vascular malformation (VM) on the right chest wall. Embolization of the VM was performed. First, the main drainers of the VM were retrogradely selected from the segmental pulmonary arteries and embolized using microcoils. Second, 2 main feeders of the VM were selected and embolized with N-butyl cyanoacrylate. Thus, marked flow reduction in the VM was achieved, and the patient's symptom improved dramatically. We believe that embolization of both feeders and drainers is an effective technique for treatment of a chest wall systemic artery-to-pulmonary artery VM.

Long-term efficacy and risk factors for stent occlusion in portal vein stent placement: a multi-institutional retrospective study.

BACKGROUND: Surgical treatment for PV (portal vein) stenosis/occlusion can pose a fatal risk of massive bleeding from severe adhesions and collateral vessel formation. PV stents placement is a minimally invasive and effective procedure for PV stenosis/occlusion, but PV stents sometimes occlude. The relationship between post-stent PV hemodynamics and stent occlusion has not been thoroughly investigated. Certain precautions during PV stent placement may reduce the risk of stent occlusion. This study aimed to evaluate long-term outcomes of PV stent patency and investigate factors including PV hemodynamics associated with stent occlusion. MATERIALS AND METHODS: Thirty-four consecutive patients with PV stenosis/occlusion who underwent PV stent placement in four institutions between December 2006 and February 2021 were retrospectively examined. The primary study endpoints were technical success, clinical success, and cumulative stent patency rate. The secondary endpoints were risk factors of stent occlusion. A univariable Cox proportional hazards model with sixteen variables was used to determine predictors of stent occlusion. Factors with p-value ≤ 0.1 in univariable analysis were included in the multivariable analysis. Alpha was set at 0.05. RESULTS: Technical and clinical success rates were 88.2% and 79.4%, respectively. Six patients (17.7%) experienced stent occlusion. The cumulative stent patency rate at six months, one year, and three years was 79.1%, 79.1%, and 65.9%, respectively. In the univariate analysis, the variables with p-value ≤ 0.1 were lesion length > 4 cm, hepatofugal collateral vein visualization after stent placement, and residual stenosis > 30% after stent placement. In the multivariate analysis, residual stenosis > 30% after stent placement was significantly associated with stent occlusion (hazard ratio, 10.80; 95% confidence interval, 1.08-108.44; p = 0.04). CONCLUSION: PV stent placement was technically feasible and effective in improving portal hypertension. However, stent occlusion was not uncommon. Residual stenosis > 30% after stent placement was significantly associated with stent occlusion. We should pay attention to correctly assess the range of stenosis and release the stenosis as much as possible.

A rare case of atypical ANCA-associated vasculitis without crescents overlapping with invasive pulmonary aspergillosis, successfully treated to remission with intravenous immunoglobulin therapy.

Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is life-threatening without treatment, but aggressive immunosuppression increases the risk of exacerbating a coexisting infection. Finding the balance between efficacy and safety of immunosuppression is challenging. We describe a 74-year-old man who was diagnosed with AAV following the aggravation of chronic pulmonary aspergillosis that required an aggressive antifungal agent. The laboratory data on admission demonstrated severe kidney failure requiring hemodialysis. Due to the active infection, we chose intravenous immunoglobulin (IVIg) as a low-risk initial treatment, which remarkably improved renal dysfunction (serum creatinine; 16.7 mg/dL-3.7 mg/dL) and systemic inflammation. Renal biopsy that was performed after renal recovery revealed atypical ANCA-associated nephritis without cellular crescents but with massive arteritis with multiple vascular sizes and diffuse interstitial inflammation. Despite these active AAV findings, adding plasma exchange therapy (PE) and low-dose steroids were sufficient to induce remission. The main pathogenesis of severe renal impairment was probably the reduction of blood flow, resulting from occlusions of small arteries by inflammatory cell infiltration and vascular endothelial injury due to AAV. Combination treatment with antifungal agents, IVIg, PE, and low-dose steroid treatment led to complete resolution of vasculitis. The specific histological findings and the good response to treatments suggest that pulmonary aspergillosis might trigger vasculitis through induction of ANCA antigen expression. IVIg could be an important option especially for cases of AAV associated with pulmonary aspergillosis.

Convolutional neural network for classifying primary liver cancer based on triple-phase CT and tumor marker information: a pilot study.

PURPOSE: To develop convolutional neural network (CNN) models for differentiating intrahepatic cholangiocarcinoma (ICC) from hepatocellular carcinoma (HCC) and predicting histopathological grade of HCC. MATERIALS AND METHODS: Preoperative computed tomography and tumor marker information of 617 primary liver cancer patients were retrospectively collected to develop CNN models categorizing tumors into three categories: moderately differentiated HCC (mHCC), poorly differentiated HCC (pHCC), and ICC, where the histopathological diagnoses were considered as ground truths. The models processed manually cropped tumor with and without tumor marker information (two-input and one-input models, respectively). Overall accuracy was assessed using a held-out dataset (10%). Area under the curve, sensitivity, and specificity for differentiating ICC from HCCs (mHCC + pHCC), and pHCC from mHCC were also evaluated. We assessed two radiologists' performance without tumor marker information as references (overall accuracy, sensitivity, and specificity). The two-input model was compared with the one-input model and radiologists using permutation tests. RESULTS: The overall accuracy was 0.61, 0.60, 0.55, 0.53 for the two-input model, one-input model, radiologist 1, and radiologist 2, respectively. For differentiating pHCC from mHCC, the two-input model showed significantly higher specificity than radiologist 1 (0.68 [95% confidence interval: 0.50-0.83] vs 0.45 [95% confidence interval: 0.27-0.63]; p = 0.04). CONCLUSION: Our CNN model with tumor marker information showed feasibility and potential for three-class classification within primary liver cancer.

Attribute-guided image generation of three-dimensional computed tomography images of lung nodules using a generative adversarial network.

PURPOSE: To develop and evaluate a three-dimensional (3D) generative model of computed tomography (CT) images of lung nodules using a generative adversarial network (GAN). To guide the GAN, lung nodule size was used. MATERIALS AND METHODS: A public CT dataset of lung nodules was used, from where 1182 lung nodules were obtained. Our proposed GAN model used masked 3D CT images and nodule size information to generate images. To evaluate the generated CT images, two radiologists visually evaluated whether the CT images with lung nodule were true or generated, and the diagnostic ability was evaluated using receiver-operating characteristic analysis and area under the curves (AUC). Then, two models for classifying nodule size into five categories were trained, one using the true and the other using the generated CT images of lung nodules. Using true CT images, the classification accuracy of the sizes of the true lung nodules was calculated for the two classification models. RESULTS: The sensitivity, specificity, and AUC of the two radiologists were respectively as follows: radiologist 1: 81.3%, 37.7%, and 0.592; radiologist 2: 77.1%, 30.2%, and 0.597. For categorization of nodule size, the mean accuracy of the classification model constructed with true CT images was 85% (range 83.2-86.1%), and that with generated CT images was 85% (range 82.2-88.1%). CONCLUSIONS: Our results show that it was possible to generate 3D CT images of lung nodules that could be used to construct a classification model of lung nodule size without true CT images.

Quantitative and Qualitative Evaluation of Convolutional Neural Networks with a Deeper U-Net for Sparse-View Computed Tomography Reconstruction.

RATIONALE AND OBJECTIVES: To evaluate the utility of a convolutional neural network (CNN) with an increased number of contracting and expanding paths of U-net for sparse-view CT reconstruction. MATERIALS AND METHODS: This study used 60 anonymized chest CT cases from a public database called "The Cancer Imaging Archive". Eight thousand images from 40 cases were used for training. Eight hundred and 80 images from another 20 cases were used for quantitative and qualitative evaluation, respectively. Sparse-view CT images subsampled by a factor of 20 were simulated, and two CNNs were trained to create denoised images from the sparse-view CT. A CNN based on U-net with residual learning with four contracting and expanding paths (the preceding CNN) was compared with another CNN with eight contracting and expanding paths (the proposed CNN) both quantitatively (peak signal to noise ratio, structural similarity index), and qualitatively (the scores given by two radiologists for anatomical visibility, artifact and noise, and overall image quality) using the Wilcoxon signed-rank test. Nodule and emphysema appearance were also evaluated qualitatively. RESULTS: The proposed CNN was significantly better than the preceding CNN both quantitatively and qualitatively (overall image quality interquartile range, 3.0-3.5 versus 1.0-1.0 reported from the preceding CNN; p < 0.001). However, only 2 of 22 cases used for emphysematous evaluation (2 CNNs for every 11 cases with emphysema) had an average score of ≥ 2 (on a 3 point scale). CONCLUSION: Increasing contracting and expanding paths may be useful for sparse-view CT reconstruction with CNN. However, poor reproducibility of emphysema appearance should also be noted.

Imaging Characteristics of Liver Metastases Overlooked at Contrast-Enhanced CT.

OBJECTIVE: The purpose of this study was to evaluate the imaging characteristics of liver metastases overlooked at contrast-enhanced CT. MATERIALS AND METHODS: The records of 746 patients with a diagnosis of liver metastases from colorectal, breast, gastric, or lung cancer between November 2010 and September 2017 were reviewed. Images were reviewed when liver metastases were first diagnosed, and images from prior contrast-enhanced CT examinations were checked if available. These lesions were classified into two groups: missed lesions (those missed on the prior images) and detected lesions (those correctly identified and invisible on the prior images or there were no prior images). Tumor size, contrast-to-noise ratio, location, presence of coexisting liver cysts and hepatic steatosis, and indications for examination were compared between the groups. The t test and Fisher exact test were used to analyze the imaging characteristics of previously overlooked lesions. RESULTS: The final analysis included 137 lesions, of which 68 were classified as missed. In univariate analysis, contrast-to-noise ratio was significantly lower in missed lesions (95% CI, 2.65 ± 0.24 vs 3.90 ± 0.23; p < 0.001). The proportion of subcapsular lesions (odds ratio, 3.44; p < 0.001), hepatic steatosis (odds ratio, 6.35; p = 0.007), and examination indication other than survey of malignant tumors (odds ratio, 9.07; p = 0.02) were significantly higher for missed lesions. CONCLUSION: Liver metastases without sufficient contrast enhancement, those in patients with hepatic steatosis, those in subcapsular locations, and those found at examinations for indications other than to assess for tumors were significantly more likely to be overlooked.