Automated detection of steno-occlusive lesion on time-of-flight magnetic resonance angiography: an observer performance study.

BACKGROUND AND PURPOSE: Intracranial steno-occlusive lesions are responsible for acute ischemic stroke. However, the clinical benefits of artificial intelligence-based methods for detecting pathologic lesions in intracranial arteries have not been evaluated. We aimed to validate the clinical utility of an artificial intelligence model for detecting steno-occlusive lesions in the intracranial arteries. MATERIALS AND METHODS: Overall, 138 TOF-MRA images were collected from two institutions, which served as internal (n = 62) and external (n = 76) test sets, respectively. Each study was reviewed by five radiologists (two neuroradiologists and three radiology residents) to compare the usage and non-usage of our proposed artificial intelligence model for TOF-MRA interpretation. They identified the steno-occlusive lesions and recorded their reading time. Observer performance was assessed using the area under the Jackknife free-response receiver operating characteristic curve and reading time for comparison. RESULTS: The average area under the Jackknife free-response receiver operating characteristic curve for the five radiologists demonstrated an improvement from 0.70 without artificial intelligence to 0.76 with artificial intelligence (P = .027). Notably, this improvement was most pronounced among the three radiology residents, whose performance metrics increased from 0.68 to 0.76 (P = .002). Despite an increased reading time upon using artificial intelligence, there was no significant change among the readings by radiology residents. Moreover, the use of artificial intelligence resulted in improved inter-observer agreement among the reviewers (the intraclass correlation coefficient increased from 0.734 to 0.752). CONCLUSIONS: Our proposed artificial intelligence model offers a supportive tool for radiologists, potentially enhancing the accuracy of detecting intracranial steno-occlusion lesions on TOF-MRA. Less-experienced readers may benefit the most from this model.ABBREVIATIONS: AI = Artificial intelligence; AUC = Area under the receiver operating characteristic curve; AUFROC = Area under the Jackknife free-response receiver operating characteristic curve; DL = Deep learning; ICC = Intraclass correlation coefficient; IRB = Institutional Review Boards; JAFROC = Jackknife free-response receiver operating characteristic.

Analyzing and Assessing the Current Status of Heat-Related Illnesses in the South Korean Military.

INTRODUCTION: The population of the Republic of Korea often experiences heat-related illnesses during summer that are exacerbated by significant variations. With rising temperatures attributed to global warming and other environmental changes within the military, combined with the military medical services' mission to uphold combat capabilities and promote health, it has become crucial to accurately understand the status of heat-related illnesses and integrate more comprehensive and systematic preventive measures. This study aimed to analyze data on heat-related illnesses between 2018 and 2022 to assess and reflect on the said diseases in the South Korean Military. MATERIALS AND METHODS: We performed a secondary analysis using data provided by the Defense Medical Statistic Information System. This single-institution retrospective, cross-sectional study was approved by the Institutional Review Board of the Armed Forces Medical Command (approval number: AFMC-2023-11-001). RESULTS: Over the past 5 years, the annual number of soldiers treated for heat-related illnesses, whether as outpatients or inpatients, at division medical facilities and military hospitals ranged from 846 to 1,250 cases per year. The proportion of severe cases fluctuates annually between 1.1% and 1.8%. Notably, 94 to 96% of all heat-related illnesses were recorded between May and September, with peak rates in July and August. CONCLUSION: The army reported the highest number of heat-related illnesses among military branches, with soldiers comprising the majority of cases. This highlights the urgent need for enhanced heat illness prevention measures within army ranks. Notably, the incidence of these illnesses peaked during July and August, underlining the critical periods for intensified preventive efforts.

Clinical value of deep vein thrombosis density on lower-extremity CT venography: prediction of pulmonary thromboembolism.

AIM: Diagnosis of pulmonary thromboembolism (PTE) can be delayed if the signs and symptoms of patients are nonspecific. INTRODUCTION: To assess the clinical value of deep vein thrombosis (DVT) density on computed tomography (CT) venography for predicting PTE. METHOD: From 2016 to 2021, patients with DVT diagnosed on lower-extremity CT venography were included. Of these patients, those without PTE were classified into 'DVT-only group' and those with PTE were classified into the 'DVT with PTE group'. The DVT Hounsfield unit (HU) density was measured by drawing free-hand region-of-interests within the thrombus at the most proximal filling defect level. The risk factors associated with PTE were identified by using multivariate logistic regression analysis. A receiver operating characteristic (ROC) analysis was used to evaluate the value of DVT density for predicting the risk of PTE. RESULTS AND DISCUSSION: This study included 177 patients with a mean age of 41.7 ± 10.3 years (DVT-only group: 105 patients; DVT with PTE group: 72 patients). DVT density was significantly higher in DVT with the PTE group than DVT-only group (66.8HU ± 8.7 vs. 57.9HU ± 11.1, p < 0.001). The ROC analysis revealed that the area under the curve (AUC), sensitivity, and specificity for predicting the risk of PTE were 0.737, 72.2%, and 66.7%, respectively, at a DVT density cutoff of 63.0 HU. On univariate and multivariate analysis, DVT density was the only significant risk factor associated with PTE. CONCLUSION: Higher DVT density was a significant risk factor for PTE. In addition, DVT density could be a predictive factor for PTE.

Thrombus volume and Hounsfield unit density as a predictor of pulmonary embolism in patients with deep vein thrombosis.

BACKGROUND: There is a lack of studies evaluating the association between thrombus volume and density of deep vein thrombosis (DVT) and pulmonary embolism (PE). PURPOSE: To assess the clinical value of thrombus volume and density for prediction of PE in patients with DVT. MATERIAL AND METHODS: Among the patients with DVT, those without PE were classified as the "DVT-only group" and those with PE were classified as the "DVT-PE group." Thrombus volume and Hounsfield unit (HU) density of DVT was measured by drawing free-hand volume of interests within the thrombus. Multivariate regression and receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of thrombus volume and density for PE. RESULTS: Of the included 145 patients (mean age=41.7 ± 10.3 years), there were 87 patients in the DVT-only group and 58 patients in the DVT-PE group. The DVT-PE group showed a significantly higher DVT density (67.4 ± 8.6 HU vs. 57.3 ± 10.4 HU; P < 0.001) and larger DVT volume (16.4 ± 13.9 cm3 vs. 12.8 ± 10.1 cm3; P = 0.016) than the DVT-only group. On multivariate analysis, thrombus density was the only associated factor for PE. ROC analysis showed that thrombus density ≥61.8 HU was the optimal cutoff for predicting PE with an area under the curve (AUC) of 0.774 and thrombus volume ≥14.0 cm3 was the cutoff with an AUC of 0.638. CONCLUSION: Though the results of our study should be considered within the limitations, DVT density could be a predictor for acute PE. Further studies are needed to clarify the clinical value of quantitative features of DVT including thrombus volume as an imaging biomarker for PE.

Clinical value of deep vein thrombosis density on pre-contrast and post-contrast lower-extremity CT for prediction of pulmonary thromboembolism.

BACKGROUND: There was a lack of studies assessing the relationship between deep vein thrombosis (DVT) Hounsfield unit (HU) density and pulmonary thromboembolism (PTE). PURPOSE: To evaluate the clinical value of DVT density measured on pre- and post-contrast lower-extremity computed tomography (CT) for the prediction of PTE. MATERIAL AND METHODS: From 2017 to 2021, patients who underwent pulmonary CT angiography within one week after diagnosis of DVT on lower-extremity CT were included in this retrospective study. Then, the patients without PTE were included in "DVT group" and those with both DVT and PTE were included in the "DVT-PTE group." The DVT HU density was measured by drawing free-hand region of interests (ROIs) within the thrombus at the most proximal filling defect level. A receiver operating characteristic (ROC) analysis was used to evaluate the predictive value of DVT density for the risk of PTE. RESULTS: This study included a total of 94 patients (DVT group: n=56; DVT-PTE group: m=38). DVT density was significantly higher in the DVT-PTE group than the DVT group in both pre-contrast (53.5 ± 6.2 HU vs. 44.1 ± 7.9 HU; P < 0.001) and post-contrast CT (67.0 ± 8.6 HU vs. 57.1 ± 10.6 HU; P < 0.001). ROC analysis revealed that the area under curve, sensitivity, and specificity for predicting the risk of PTE were 0.739, 71.1%, and 64.2%, respectively, at a DVT density cutoff of 48.2 HU on pre-contrast CT and were 0.779, 73.7%, and 69.6% at a DVT density cutoff of 61.8 HU on post-contrast CT. CONCLUSION: The DVT density on both pre- and post-contrast CT could be a predictive factor of PTE.

Prevalence and neglected rate of sacroiliitis on lumbar spine CT in patients with low back pain.

OBJECTIVE: The study aims to investigate the prevalence and neglected rate of sacroiliitis on lumbar spine computed tomography (CT) in patients with low back pain. MATERIALS AND METHODS: From January 2016 to December 2020, a total of 4827 patients (mean age: 35.4 ± 9.5 years) who underwent lumbar spine CT examinations were included in this retrospective study. The CT degree of sacroiliitis in all study population were retrospectively reviewed by two radiologists. The independent sample t-test was used to compare the continuous values and chi-squared or Fisher's exact test was used to compare the categorized values. RESULTS: Sacroiliitis was identified in 514 of 4827 patients (10.6%). Patients with sacroiliitis were significantly younger than those without sacroiliitis (32.1 ± 8.9 vs. 35.8 ± 9.5 years, p < 0.001). Moreover, significantly more patients with sacroiliitis had HLA-B27 (p < 0.001) positivity and inflammatory back pain syndrome (p = 0.003) than those without sacroiliitis. Among the 514 patients, sacroiliitis was recognized on primary reading in 386 patients (75.1%) but was neglected in the remaining 128 patients (24.9%). Of the 386 patients, 371 patients were followed up, and finally, 295 patients of them (79.5%) were diagnosed with axSpA. CONCLUSION: Radiologists should pay careful and more attention to sacroiliac joint on lumbar spine CT for early diagnosis of sacroiliitis in young patients with low back pain, which could result in early diagnosis and treatment of axSpA.

Newly Appearing Hepatic Lesion After Curative Surgery For Colorectal Cancer: Single-phase CT Findings Implying Metastasis.

BACKGROUND: In patients treated with curative surgery for colorectal cancer, the single-phase (portal phase) abdomen-pelvic computed tomography (CT) follow-up is routinely performed to detect any recurrent lesions. OBJECTIVE: The objective of this study is to evaluate CT features implying metastasis in newly appearing hepatic lesions on single-phase CT after colorectal cancer surgery. METHODS: Of 1,227 patients who underwent curative colorectal surgery between 2011 and 2014, 267 patients with new hepatic lesions on follow-up single-phase CT (metastasis, n=192; benign, n=75) were included. The CT features of the hepatic lesions were analyzed by two radiologists retrospectively, and clinical information, including carcinoembryonic antigen (CEA) level was also reviewed. The risk factors for hepatic metastasis were evaluated by multivariable logistic regression. RESULTS: In this study, independent CT features associated with metastasis were spherical shape (p < 0.001), circumscribed margin (p = 0.021), heterogeneous attenuation (p = 0.024) and bulging appearance (p = 0.007). Among the clinical factors, increased CEA level (p = 0.013), higher preoperative stage (p = 0.014) and lymphovascular invasion (p = 0.003) were associated with metastasis. However, on multivariable analysis, spherical shape was the only significant predictive factor for hepatic metastasis. The diagnostic performance of 'spherical shape' for detection of hepatic metastasis showed an accuracy of 84.6%, sensitivity of 83.9%, and specificity of 86.7%. CONCLUSION: Specific single-phase CT features could be useful in distinguishing hepatic metastasis from benign, resulting in continuing routine CT follow-up without liver magnetic resonance imaging (MRI) when metastasis is unlikely.

Transperineal ultrasonography for treatment response evaluation in children with perianal Crohn's disease.

PURPOSE: This study assessed the performance of transperineal ultrasonography (TPUS) in evaluating the treatment response in children with perianal Crohn's disease (PACD) compared with pelvic magnetic resonance imaging (MRI). METHODS: This retrospective study was approved by the Institutional Review Board of our institution, which waived the requirement for informed consent. Twenty-nine patients (19 boys and 10 girls; median age, 14 years [range, 8 to 18 years]) with 56 fistulas were examined. Each fistula's thickness and abscess size were measured using both modalities, and treatment response was classified as positive or negative based on each modality. The concordance of the classifications was compared between TPUS and pelvic MRI. A receiver operating characteristic curve (ROC) was used to evaluate the performance of TPUS. RESULTS: TPUS found 80.4% (45/56) of the fistulas. On MRI, 39 fistulas (70%) were classified as having positive treatment responses, and the remaining 17 as having no response. The agreement of the classifications between TPUS and MRI was moderate (κ=0.486; P<0.001; Spearman ρ=0.573; P<0.001). Based on the ROC analysis with the MRI findings as a reference to distinguish positive from negative treatment responses, TPUS exhibited sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 63.3%, 93.3%, 95.0%, 56.0%, and 73.3%, respectively. CONCLUSION: TPUS can be an appropriate adjuvant imaging modality for pelvic MRI to evaluate the treatment response of PACD in children when initial TPUS detects PACD with a location and imaging features comparable to those visualized on MRI.