Electron density dual-energy CT can improve the detection of lumbar disc herniation with higher image quality than standard and virtual non-calcium images.

OBJECTIVES: To compare the diagnostic performance and image quality of dual-energy computed tomography (DECT) with electron density (ED) image reconstruction with those of DECT with standard CT (SC) and virtual non-calcium (VNCa) image reconstructions, for diagnosing lumbar disc herniation (L-HIVD). METHODS: A total of 59 patients (354 intervertebral discs from T12/L1 to L5/S1; mean age, 60 years; 30 women and 29 men) who underwent DECT with spectral reconstruction and 3-T MRI within 2 weeks were enrolled between March 2021 and February 2022. Four radiologists independently assessed three image sets of randomized ED, SC, and VNCa images to detect L-HIVD at 8-week intervals. The coefficient of variance (CV) and the Weber contrast of the ROIs in the normal and diseased disc to cerebrospinal fluid space (NCR-normal/-diseased, respectively) were calculated to compare the image qualities of the noiseless ED and other series. RESULTS: Overall, 129 L-HIVDs were noted on MRI. In the detection of L-HIVD, ED showed a higher AUC and sensitivity than SC and VNCa; 0.871 vs 0.807 vs 833 (p = 0.002) and 81% vs 70% vs 74% (p = 0.006 for SC), respectively. CV was much lower in all measurements of ED than those for SC and VNCa (p < 0.001). Furthermore, NCR-normal and NCR-diseased were the highest in ED (ED vs SC in NCR-normal and NCR-diseased, p = 0.001 and p = 0.004, respectively; ED vs VNCa in NCR-diseased, p = 0.044). CONCLUSION: Compared to SC and VNCa images, DECT with ED reconstruction can enhance the AUC and sensitivity of L-HIVD detection with a lower CV and higher NCR. CLINICAL RELEVANCE STATEMENT: To our knowledge, this is the first study to quantify the image quality of noiseless ED images. ED imaging may be helpful for detecting L-HIVD in patients who cannot undergo MRI. KEY POINTS: ED images have diagnostic potential, but relevant quantitative analyses of image quality are limited. ED images detect disc herniation, with a better coefficient of variance and normalized contrast ratio values. ED images could detect L-HIVD when MRI is not an option.

Medial Patellar Plica Thickness as a Morphologic Predictor of the Medial Patellar Plica Syndrome.

OBJECTIVE: The aim of this study was to evaluate the association between medial patellar plica (MPP) syndrome and the morphological features of the MPP, including length, width, and thickness, on knee magnetic resonance imaging (MRI). MATERIALS AND METHODS: From 2018 to 2022, 167 patients diagnosed with isolated MPP syndrome based on both MRI and arthroscopic findings were included in the "study group" and 226 patients without knee pathology on both MRI and physical examination were included in the "control group." Finally, 393 patients (mean age, 38.9 ± 5.7 years) with 405 knee MRI examinations were included. Morphological MR features of MPP were assessed, including width, length, and thickness. Multivariate regression and receiver operating characteristic analyses were performed to identify the factors associated with MPP syndrome. RESULTS: The mean thickness of MPP was significantly higher in the study group than control group (2.3 ± 0.5 mm vs 1.0 ± 0.8 mm, P < 0.001). Moreover, on multivariate analysis, MPP thickness was the only significant factor associated with MPP syndrome (odds ratio, 6.452; 95% confidence interval, 0.816-15.073; P = 0.002). On receiver operating characteristic analysis, thickness ≥1.8 mm was estimated as the optimal cutoff for predicting MPP syndrome with sensitivity of 75.9%, specificity of 65.4%, and area under the curve of 0.727 (95% confidence interval, 0.667-0.788; P < 0.001). CONCLUSIONS: Measurement of MPP thickness on MRI could be a morphological predictor of MPP syndrome.

Is the epicardial adipose tissue area on non-ECG gated low-dose chest CT useful for predicting coronary atherosclerosis in an asymptomatic population considered for lung cancer screening?

OBJECTS: The purpose was to determine whether the epicardial adipose tissue (EAT) area on low-dose chest CT (LDCT) could be used to predict coronary atherosclerosis in an asymptomatic population considered for lung cancer screening. METHODS: Subjects aged 55-80 years with smoking history who underwent both LDCT and coronary CT angiography (CCTA) were retrospectively enrolled. Correlation between the EAT volume in CCTA and EAT area in LDCT was evaluated. Coronary risk factors including the body surface area (BSA) indexed EAT area were compared between coronary plaque negative and positive groups. Significant factors for predicting coronary atherosclerosis were analyzed with logistic regression analysis. Receiver-operating characteristic curve analysis was performed to determine the cutoff value. RESULTS: A total of 438 subjects were enrolled, including 299 subjects with coronary atherosclerosis. There was a good correlation between the EAT volume in CCTA and EAT area in LDCT (ρ = 0.712, p < 0.001). There were significant differences in age, systolic blood pressure, all BSA indexed EAT area, sex, and hypertension between plaque negative and positive groups. In multivariate logistic regression for the BSA indexed EAT area in LDCT at the RCA level, sex (OR: 11.168, 95% CI: 2.107-59.201, p = 0.005), systolic blood pressure (OR: 1.021, 95% CI: 1.005-1.036, p = 0.009), hypertension (OR: 1.723, 95% CI: 1.103-2.753, p = 0.017), and EAT area (OR: 1.273, 95% CI: 1.154-1.405, p < 0.001) were significant. The area under the curve of the BSA indexed EAT area in LDCT at the RCA level for coronary atherosclerosis was 0.657, and the cut-off value was 7.66 cm2/m2. CONCLUSION: The EAT area in LDCT could be used to predict coronary atherosclerosis in an asymptomatic population considered for lung cancer screening. KEY POINTS: • To quantify EAT, the EAT area in LDCT can be used instead of the EAT volume in CCTA. • The EAT area measured in LDCT can be used as a predictor of coronary artery disease. • The extensive CAD group tended to have a greater EAT area than the non-extensive CAD group.

Contrast-enhanced Magnetic Resonance Imaging of Pelvic Bone Metastases at 3.0 T: Comparison Between 3-dimensional T1-weighted CAIPIRINHA-VIBE Sequence and 2-dimensional T1-weighted Turbo Spin-Echo Sequence.

OBJECTIVE: This study aimed to compare 3-dimensional T1-weighted gradient-echo sequence (CAIPIRINHA-volumetric interpolated breath-hold examination [VIBE]) with 2-dimensional T1-weighted turbo spin-echo sequence for contrast-enhanced magnetic resonance imaging (MRI) of pelvic bone metastases at 3.0 T. METHODS: Thirty-one contrast-enhanced MRIs of pelvic bone metastases were included. Two contrast-enhanced sequences were evaluated for the following parameters: overall image quality, sharpness of pelvic bone, iliac vessel clarity, artifact severity, and conspicuity and edge sharpness of the smallest metastases. Quantitative analysis was performed by calculating signal-to-noise ratio and contrast-to-noise ratio of the smallest metastases. Significant differences between the 2 sequences were assessed. RESULTS: CAIPIRINHA-VIBE had higher scores for overall image quality, pelvic bone sharpness, iliac vessel clarity, and edge sharpness of the metastatic lesions, and had less artifacts (all P < 0.05). There was no significant difference in conspicuity, signal-to-noise ratio, or contrast-to-noise ratio of the smallest metastases (P > 0.05). CONCLUSIONS: Our results suggest that CAIPIRINHA-VIBE may be superior to turbo spin-echo for contrast-enhanced MRI of pelvic bone metastases at 3.0 T.

Desmoid-type fibromatosis mimicking cystic retroperitoneal mass: case report and literature review.

BACKGROUND: Retroperitoneal desmoid-type fibromatosis (DF) is an uncommon mesenchymal neoplasm presenting as a firm mass with locally aggressive features. It usually manifests as a well-circumscribed or ill-defined, solid mass on cross-sectional imaging. Cystic changes of DF have been described in the literature in association with prolonged medical treatment or abscess formation. However, spontaneous cystic change is rarely reported. CASE PRESENTATION: Here we report the case of a 46-year-old patient with a DF mimicked a large cystic tumor in the retroperitoneum. Ultrasonography and computed tomography were performed in order to search for localizations and characteristics of the cystic tumor. Radiological findings showed an oval cystic mass with a relatively thick wall, measuring 18.3 × 12.3 × 21.5 cm in the left upper abdomen. Laparoscopic spleen-preserving distal pancreatectomy was performed and histopathological examination by immunohistochemical study enabled us to diagnose a DF invading the pancreatic parenchyma. The patient remained asymptomatic during an 8-month follow up period. CONCLUSIONS: We report an extremely rare case of retroperitoneal DF with spontaneous cystic change. DF can manifest as a mainly cystic mass with a thick wall, as in our case, which makes the correct diagnosis difficult. DF should be included in the preoperative differential diagnosis of a cystic retroperitoneal mass, regardless of its rarity.

Detection Rate of Small Pancreas Cysts and Intrareader Reliability of the Cysts Size Measurements on Transabdominal Ultrasonography.

ABSTRACT: This study aimed to assess the detection rate of small (<10 mm) pancreas cyst and intrareader reliability for cyst size measurements on transabdominal ultrasonography (US). From 2020 to 2022, 194 pancreas cysts in 173 patients, incidentally detected on computed tomography or magnetic resonance imaging, were evaluated on US by 1 of 2 radiologists (readers 1 and 2). Intrareader agreements of cyst size measurements on US were assessed by intraclass correlation coefficient (ICC). Bland-Altman plot was used to visualize the differences between the first and second size measurements in each reader. In this study, readers 1 and 2 evaluated 86 cysts in 76 patients and 108 cysts in 97 patients, respectively. Most of the cysts (191 of 194) were located in the nontail portion of the pancreas. Overall detection rate of pancreas cysts by US was 92.3% (179 of 194). The mean size of measured 179 pancreas cysts was 4.7 ± 1.5 mm. The readers showed excellent intrareader agreements (ICC = 0.925 and 0.960) for cyst size measurements, except for the cysts with size ≤5 mm, where both readers showed good intrareader agreements (ICC = 0.848 and 0.873). The 95% limits of agreement of readers 1 and 2 were 13.8% and 14.9% of the mean, respectively. Therefore, transabdominal US could be a reliable follow-up imaging modality for small (<10 mm) nontail pancreas cysts incidentally detected on computed tomography or magnetic resonance imaging, especially for the cysts with size between 5 and 10 mm. Size changes of the pancreas cysts approximately less than 15% may be within the measurement error.

Assessment of Imaging Factors Associated with Baker's Cyst Rupture on Knee MRI.

Objectives: To identify the factors associated with Baker's cyst rupture on MRI. Material and methods: From January 2021 to December 2022, a total of 441 knee MRI examinations in 441 patients (mean age: 47.7 ± 13.8 years) with Baker's cyst were included in this study. Patients were classified into two groups: those with ruptured vs. unruptured Baker's cysts. On knee radiograph, osteoarthritis grade was assessed based on Kellgren-Lawrence grade. On MRI, combined structure injuries, alignment type between semimembranosus tendon and medial head of gastrocnemius tendon, amount of joint effusion, presence of septation, maximal diameters of cyst, and cyst volume were evaluated. Receiver operating characteristic (ROC) analysis was performed to assess the predictive performances of imaging factors for cyst rupture. Results: There were 146 patients with Baker's cyst rupture and 295 patients without rupture. Patients with cyst rupture showed significantly longer maximal transverse diameter (25.8 ± 6.8 mm vs. 21.6 ± 5.8 mm, p = 0.035) and larger volume (13.3 ± 6.2 cm3 vs. 9.9 ± 5.1 cm3, p = 0.012) than those without rupture. On ROC analysis, maximal transverse diameter of cyst ≥ 22.2 mm (sensitivity = 64.4%, specificity = 54.9%) and cyst volume ≥ 10.9 cm3 (sensitivity = 71.2%, specificity = 58.3%) were the cutoff values for predicting rupture of cyst, respectively. The cyst volume showed significantly higher area under the curve (AUC) than maximal transverse diameter (0.726 vs. 0.642, p = 0.002). Conclusion: Longer transverse diameter and larger volume of Baker's cyst could be predictive imaging parameters for cyst rupture.

Clinical Validation of an Artificial Intelligence Model for Detecting Distal Radius, Ulnar Styloid, and Scaphoid Fractures on Conventional Wrist Radiographs.

This study aimed to assess the feasibility and performance of an artificial intelligence (AI) model for detecting three common wrist fractures: distal radius, ulnar styloid process, and scaphoid. The AI model was trained with a dataset of 4432 images containing both fractured and non-fractured wrist images. In total, 593 subjects were included in the clinical test. Two human experts independently diagnosed and labeled the fracture sites using bounding boxes to build the ground truth. Two novice radiologists also performed the same task, both with and without model assistance. The sensitivity, specificity, accuracy, and area under the curve (AUC) were calculated for each wrist location. The AUC for detecting distal radius, ulnar styloid, and scaphoid fractures per wrist were 0.903 (95% C.I. 0.887-0.918), 0.925 (95% C.I. 0.911-0.939), and 0.808 (95% C.I. 0.748-0.967), respectively. When assisted by the AI model, the scaphoid fracture AUC of the two novice radiologists significantly increased from 0.75 (95% C.I. 0.66-0.83) to 0.85 (95% C.I. 0.77-0.93) and from 0.71 (95% C.I. 0.62-0.80) to 0.80 (95% C.I. 0.71-0.88), respectively. Overall, the developed AI model was found to be reliable for detecting wrist fractures, particularly for scaphoid fractures, which are commonly missed.

Deep-Learning-Based Automated Rotator Cuff Tear Screening in Three Planes of Shoulder MRI.

This study aimed to develop a screening model for rotator cuff tear detection in all three planes of routine shoulder MRI using a deep neural network. A total of 794 shoulder MRI scans (374 men and 420 women; aged 59 ± 11 years) were utilized. Three musculoskeletal radiologists labeled the rotator cuff tear. The YOLO v8 rotator cuff tear detection model was then trained; training was performed with all imaging planes simultaneously and with axial, coronal, and sagittal images separately. The performances of the models were evaluated and compared using receiver operating curves and the area under the curve (AUC). The AUC was the highest when using all imaging planes (0.94; p < 0.05). Among a single imaging plane, the axial plane showed the best performance (AUC: 0.71), followed by the sagittal (AUC: 0.70) and coronal (AUC: 0.68) imaging planes. The sensitivity and accuracy were also the highest in the model with all-plane training (0.98 and 0.96, respectively). Thus, deep-learning-based automatic rotator cuff tear detection can be useful for detecting torn areas in various regions of the rotator cuff in all three imaging planes.

A Systematic Approach to Diagnosing Arthritis Based on Radiological Imaging.

Radiology plays a key role in the diagnosis of arthritis. We herein suggest an algorithmic approach to diagnosing arthritis. First, the number of joint involvements is reviewed. Monoarticular arthritis includes septic arthritis, pigmented villonodular synovitis, and synovial chondromatosis. Second, polyarticular arthritis can be categorized by its characteristics: erosive, productive, and mixed. Erosive disease includes rheumatoid arthritis, hemophilia, and amyloidosis, while productive disease includes osteoarthritis and hemochromatosis. Third, mixed diseases are subcategorized by symmetricity. Ankylosing spondylitis and inflammatory bowel disease related arthritis affect joints symmetrically, while psoriatic arthritis, reactive arthritis, and crystalline arthropathy are asymmetric. Adjacent soft tissue density, periostitis, and bone density are ancillary findings that can be used as additional differential diagnostic clues. The final step in identifying the type of arthritis is to check whether the location is a site frequently affected by one particular disease over another. This systematic approach would be helpful for radiologists in diagnosing arthritis.

Characteristic Imaging Features of Merkel Cell Carcinoma: A Case Report.

BACKGROUND: Merkel cell carcinoma (MCC) is a rare primary cutaneous tumor. The standardized imaging guidelines for the diagnosis of MCC have not been established. We report the multimodality imaging features of MCC, including CT, MRI, and ultrasound with grayscale and color Doppler mode as well as the elastography and even a histopathologic confirmation. CASE REPORT: We report the case of a 76-year old male patient with MCC on the elbow that was treated by excision. On MRI, prominent T2 low signal voiding was noted with branching or chaotic pattern and marked, branching, or chaotic vascularity was also seen on color doppler ultrasound. Those findings corresponded to histology that showed increased vascularity in stromal tissues of the tumor and in between the tumor cells. CONCLUSION: A mass in the dermal and subcutaneous layer with marked and branching or chaotic vascularity may be the unique characteristic that may contribute to early diagnosis of MCC.

Clinical Validation of a Deep Learning-Based Hybrid (Greulich-Pyle and Modified Tanner-Whitehouse) Method for Bone Age Assessment.

OBJECTIVE: To evaluate the accuracy and clinical efficacy of a hybrid Greulich-Pyle (GP) and modified Tanner-Whitehouse (TW) artificial intelligence (AI) model for bone age assessment. MATERIALS AND METHODS: A deep learning-based model was trained on an open dataset of multiple ethnicities. A total of 102 hand radiographs (51 male and 51 female; mean age ± standard deviation = 10.95 ± 2.37 years) from a single institution were selected for external validation. Three human experts performed bone age assessments based on the GP atlas to develop a reference standard. Two study radiologists performed bone age assessments with and without AI model assistance in two separate sessions, for which the reading time was recorded. The performance of the AI software was assessed by comparing the mean absolute difference between the AI-calculated bone age and the reference standard. The reading time was compared between reading with and without AI using a paired t test. Furthermore, the reliability between the two study radiologists' bone age assessments was assessed using intraclass correlation coefficients (ICCs), and the results were compared between reading with and without AI. RESULTS: The bone ages assessed by the experts and the AI model were not significantly different (11.39 ± 2.74 years and 11.35 ± 2.76 years, respectively, p = 0.31). The mean absolute difference was 0.39 years (95% confidence interval, 0.33-0.45 years) between the automated AI assessment and the reference standard. The mean reading time of the two study radiologists was reduced from 54.29 to 35.37 seconds with AI model assistance (p < 0.001). The ICC of the two study radiologists slightly increased with AI model assistance (from 0.945 to 0.990). CONCLUSION: The proposed AI model was accurate for assessing bone age. Furthermore, this model appeared to enhance the clinical efficacy by reducing the reading time and improving the inter-observer reliability.

A Stepwise Diagnostic Approach to Cystic Lung Diseases for Radiologists.

Lung cysts are commonly seen on computed tomography (CT), and cystic lung diseases show a wide disease spectrum. Thus, correct diagnosis of cystic lung diseases is a challenge for radiologists. As the first diagnostic step, cysts should be distinguished from cavities, bullae, pneumatocele, emphysema, honeycombing, and cystic bronchiectasis. Second, cysts can be categorized as single/localized versus multiple/diffuse. Solitary/localized cysts include incidental cysts and congenital cystic diseases. Multiple/diffuse cysts can be further categorized according to the presence or absence of associated radiologic findings. Multiple/diffuse cysts without associated findings include lymphangioleiomyomatosis and Birt-Hogg-Dubé syndrome. Multiple/diffuse cysts may be associated with ground-glass opacity or small nodules. Multiple/diffuse cysts with nodules include Langerhans cell histiocytosis, cystic metastasis, and amyloidosis. Multiple/diffuse cysts with ground-glass opacity include pneumocystis pneumonia, desquamative interstitial pneumonia, and lymphocytic interstitial pneumonia. This stepwise radiologic diagnostic approach can be helpful in reaching a correct diagnosis for various cystic lung diseases.

Primary Peripheral Gamma Delta T-Cell Lymphoma of the Central Nervous System: Report of a Case Involving the Intramedullary Spinal Cord and Presenting with Myelopathy.

Primary central nervous system lymphoma of T-cell origin (T-PCNSL) is rare, and its clinicopathological features remain unclear. Peripheral T-cell lymphoma of γδ T-cell origin is an aggressive lymphoma mainly involving extranodal sites. Here, we report a case of γδ T-PCNSL involving the intramedullary spinal cord and presenting with paraplegia. A 75-year-old Korean woman visited the hospital complaining of back pain and lower extremity weakness. Magnetic resonance imaging revealed multifocal enhancing intramedullary nodular lesions in the thoracic and lumbar spinal cord. An enhancing nodular lesion was observed in the periventricular white matter of the lateral ventricle in the brain. There were no other abnormalities in systemic organs or skin. Laminectomy and tumor removal were performed. The tumor consisted of monomorphic, medium-to-large atypical lymphocytes with pale-to-eosinophilic cytoplasm. Immunohistochemically, the tumor cells were CD3(+), TCRßF1(-), TCRγ(+), CD30(-), CD4(-), CD8(-), CD56(+), TIA1(+), granzyme B(+), and CD103(+). Epstein-Barr virus in situ was negative. This case represents a unique T-PCNSL of γδ T-cell origin involving the spinal cord.

Socioeconomic status and other related factors of seasonal influenza vaccination in the South Korean adult population based on a nationwide cross-sectional study.

PURPOSE: We investigated the association between seasonal influenza vaccination in South Korea and socioeconomic status (SES) as well as other potential related factors. METHODS: The study was based on data obtained in the Korea National Health and Nutrition Examination Survey from 2010 to 2011. Education level and household income were used as indicators for SES. Univariate and multiple logistic regression analyses were used to evaluate SES and other demographic variables as related factors for influenza vaccination, the primary outcome. RESULTS: Higher household income was positively associated with higher vaccine uptake in the younger (19-49 years) group [adjusted odds ratio (aOR) 1.55, 95% confidence interval (CI) 1.08-2.23], whereas the low-income and low-education group had increased vaccination coverage than the middle-income and middle-education group in the older (≥ 50 years) group (aOR 1.36, 95% CI 1.09-1.69). Current smokers tend to be unvaccinated in all age groups. Among individuals aged ≥ 50, older age, mild to moderate alcohol consumption, regular exercise, and having co-morbidities were positively associated with vaccination, while those who self-reported their health status as good were less likely to be vaccinated. CONCLUSIONS: The relationship between SES and seasonal influenza vaccination coverage differed between the age groups throughout the adult South Korean population. Public health policies need to address these inequalities.