Benign tumors and tumor like lesions in the foot are uncommon and those that are malignant are rare. Metastatic cancer of bone distal to the knee and elbow is unusual. By contrast, non-tumorous lisions that cause swelling, pretuberance, or deformity are common. Fifty two cases of tumors on foot were treated at our department from Jan. 1970 to Dec. 1991, we have treated fifty two cases of foot tumor and analysed their clinical characteristics. Bone tumors were more frequent than soft tissue tumors (2:1). Among soft tissue tumors benign tumors were frequent than malignant(1.4:1), and fibroma was the most frequent tumor(30%). Benign soft tissue tumors occured frequently at Edward and Michael's Zone 3(57%). Benign bone tumors has higher incidence than malignant(20:1). Osteochondroma was the most frequent tumor (48%). Predilection sites for osteochondroma and enchondroma of foot was distal phalanges and mitatarsal bone, respectively.
Bone Neoplasms ; Chondroma ; Congenital Abnormalities ; Elbow ; Fibroma ; Foot ; Incidence ; Knee ; Osteochondroma

Acute necrotizing encephalopathy (ANE) is a rare but distinctive type of influenza-associated encephalopathy characterized by symmetric multiple lesions with an invariable thalamic involvement. Although the exact pathogenesis of ANE remains unclear, the most prevalent hypothesis is the “cytokine storm,” which results in blood-brain-barrier breakdown. We present the case of a 10-year-old boy with fulminant ANE confirmed with serial MRI studies, including diffusion-weighted imaging and susceptibility-weighted imaging. A comparison of these serial images demonstrated detailed and longitudinal changes in MRI findings during the clinical course corresponding to pathophysiological changes. Our case clarifies the pathogenesis of ANE brain lesions using serial imaging studies and suggests that early immunomodulatory therapy reduces brain damage.

Acute necrotizing encephalopathy (ANE) is a rare but distinctive type of influenza-associated encephalopathy characterized by symmetric multiple lesions with an invariable thalamic involvement. Although the exact pathogenesis of ANE remains unclear, the most prevalent hypothesis is the “cytokine storm,” which results in blood-brain-barrier breakdown. We present the case of a 10-year-old boy with fulminant ANE confirmed with serial MRI studies, including diffusion-weighted imaging and susceptibility-weighted imaging. A comparison of these serial images demonstrated detailed and longitudinal changes in MRI findings during the clinical course corresponding to pathophysiological changes. Our case clarifies the pathogenesis of ANE brain lesions using serial imaging studies and suggests that early immunomodulatory therapy reduces brain damage.

Purpose: This study aimed to develop and validate a convolutional neural network (CNN) that automatically detects an aberrant right subclavian artery (ARSA) on preoperative computed tomography (CT) for thyroid cancer evaluation. Materials and Methods: A total of 556 CT with ARSA and 312 CT with normal aortic arch from one institution were used as the training set for model development. A deep learning model for the classification of patch images for ARSA was developed using two-dimension CNN from EfficientNet. The diagnostic performance of our model was evaluated using external test sets (112 and 126 CT) from two institutions. The performance of the model was compared with that of radiologists for detecting ARSA using an independent dataset of 1683 consecutive neck CT. Results: The performance of the model was achieved using two external datasets with an area under the curve of 0.97 and 0.99, and accuracy of 97% and 99%, respectively. In the temporal validation set, which included a total of 20 patients with ARSA and 1663 patients without ARSA, radiologists overlooked 13 ARSA cases. In contrast, the CNN model successfully detected all the 20 patients with ARSA. Conclusion We developed a CNN-based deep learning model that detects ARSA using CT. Our model showed high performance in the multicenter validation.

Purpose: This study aimed to develop and validate a convolutional neural network (CNN) that automatically detects an aberrant right subclavian artery (ARSA) on preoperative computed tomography (CT) for thyroid cancer evaluation. Materials and Methods: A total of 556 CT with ARSA and 312 CT with normal aortic arch from one institution were used as the training set for model development. A deep learning model for the classification of patch images for ARSA was developed using two-dimension CNN from EfficientNet. The diagnostic performance of our model was evaluated using external test sets (112 and 126 CT) from two institutions. The performance of the model was compared with that of radiologists for detecting ARSA using an independent dataset of 1683 consecutive neck CT. Results: The performance of the model was achieved using two external datasets with an area under the curve of 0.97 and 0.99, and accuracy of 97% and 99%, respectively. In the temporal validation set, which included a total of 20 patients with ARSA and 1663 patients without ARSA, radiologists overlooked 13 ARSA cases. In contrast, the CNN model successfully detected all the 20 patients with ARSA. Conclusion We developed a CNN-based deep learning model that detects ARSA using CT. Our model showed high performance in the multicenter validation.

Purpose: This study aimed to develop and validate a convolutional neural network (CNN) that automatically detects an aberrant right subclavian artery (ARSA) on preoperative computed tomography (CT) for thyroid cancer evaluation. Materials and Methods: A total of 556 CT with ARSA and 312 CT with normal aortic arch from one institution were used as the training set for model development. A deep learning model for the classification of patch images for ARSA was developed using two-dimension CNN from EfficientNet. The diagnostic performance of our model was evaluated using external test sets (112 and 126 CT) from two institutions. The performance of the model was compared with that of radiologists for detecting ARSA using an independent dataset of 1683 consecutive neck CT. Results: The performance of the model was achieved using two external datasets with an area under the curve of 0.97 and 0.99, and accuracy of 97% and 99%, respectively. In the temporal validation set, which included a total of 20 patients with ARSA and 1663 patients without ARSA, radiologists overlooked 13 ARSA cases. In contrast, the CNN model successfully detected all the 20 patients with ARSA. Conclusion We developed a CNN-based deep learning model that detects ARSA using CT. Our model showed high performance in the multicenter validation.

Purpose: To explore cerebrovascular reservoir (CVR) and arterial transit time (ATT) changes using acetazolamide-challenged multi-phase arterial spin labeling (MP-ASL) perfusion-weighted MRI in chronic cerebrovascular steno-occlusive disease. Materials and Methods: This retrospective study enrolled patients with chronic steno-occlusion who underwent acetazolamide-challenged MP-ASL between June 2019 and October 2020.Cerebral blood flow, CVR, basal ATT, and ATT changes associated with severe stenosis, total occlusion, and chronic infarction lesions were compared. Results: There were 32 patients (5 with bilateral steno-occlusion) in our study sample. The CVR was significantly reduced during total occlusion compared with severe stenosis (26.2% ± 28.8% vs. 41.4% ± 34.1%, respectively, p = 0.004). The ATT changes were not significantly different (p = 0.717). The CVR was marginally lower in patients with chronic infarction (29.6% ± 39.1% vs. 38.9% ± 28.7%, respectively, p = 0.076). However, the ATT was less shortened in pa-tients with chronic infarction (-54 ± 135 vs. -117 ± 128 ms, respectively, p = 0.013). Conclusion Acetazolamide-challenged MP-ASL provides an MRI-based CVR evaluation tool for chronic steno-occlusive disease.

Objectives: . This study was conducted to compare clinicopathologic and radiologic factors between benign and malignant thyroid nodules and to evaluate the diagnostic performance of shear wave elastography (SWE) combined with B-mode ultrasonography (US) in differentiating malignant from benign thyroid nodules. Methods: . This retrospective study included 92 consecutive patients with 95 thyroid nodules examined on B-mode US and SWE before US-guided fine-needle aspiration biopsy or surgical excision. B-mode US findings (composition, echogenicity, margin, shape, and calcification) and SWE elasticity parameters (maximum [Emax], mean, minimum, and nodule-to-normal parenchymal ratio of elasticity) were reviewed and compared between benign and malignant thyroid nodules. The diagnostic performance of B-mode US and SWE for predicting malignant thyroid nodules was analyzed. The optimal cutoff values of elasticity parameters for identifying malignancy were determined. Diagnostic performance was compared between B-mode US only, SWE only, and the combination of B-mode US with SWE. Results: . On multivariate logistic regression analysis, age (odds ratio [OR], 0.90; P=0.028), a taller-than-wide shape (OR, 11.3; P=0.040), the presence of calcifications (OR, 15.0; P=0.021), and Emax (OR, 1.22; P=0.021) were independent predictors of malignancy in thyroid nodules. The combined use of B-mode US findings and SWE yielded improvements in sensitivity, the positive predictive value, the negative predictive value, and accuracy compared with the use of B-mode US findings only, but with no statistical significance. Conclusion . When SWE was combined with B-mode US, the diagnostic performance was better than when only B-mode US was used, although the difference was not statistically significant.

OBJECTIVE: Coiled aneurysms are known to recanalize over time, making follow-up evaluations mandatory. Although de novo intracranial aneurysms (DNIAs) are occasionally detected during routine patient monitoring, such events have not been thoroughly investigated to date. Herein, we generated estimates of DNIA development during long-term observation of coiled cerebral aneurysms, focusing on incidence and the risk factors involved. MATERIALS AND METHODS: In total, 773 patients undergoing coil embolization of intracranial aneurysms between 2008 and 2010 were reviewed retrospectively. Their medical records and radiologic data accrued over the extended period (mean, 52.7 ± 29.7 months) were analyzed. For the detection of DNIA, follow-up magnetic resonance angiography and/or conventional angiography were used. The incidence of DNIAs and related risk factors were analyzed using Cox proportional hazards regression and Kaplan-Meier product-limit estimator. RESULTS: In 19 (2.5%) of the 773 patients with coiled aneurysms, DNIAs (0.56% per patient-year) developed during continued long-term monitoring (3395.3 patient-years). Of these, 9 DNIAs (47.4%) were detected within 60 months, with 10 (52.6%) emerging thereafter. The most common site involved was the posterior communicating artery (n = 6), followed by the middle cerebral artery (n = 5) and the basilar top (n = 4). Multivariate analysis indicated that younger age (< 50 years) (hazard ratio [HR] = 1.045; p = 0.010) and recanalization of coiled aneurysms (HR = 2.560; p = 0.047) were significant factors in DNIA formation, whereas female sex, smoking, and hypertension fell short of statistical significance. Cumulative survival rates without DNIA were significantly higher in older subjects (> 60 years; p < 0.001) and in the absence of post-coiling aneurysm recurrence (p = 0.006). CONCLUSION: In most patients with coiled aneurysms, development of DNIAs during long-term monitoring is rare. However, younger patients (< 50 years) or patients with recurring aneurysms appear to be predisposed to DNIAs.
Aneurysm ; Angiography ; Arteries ; Embolization, Therapeutic ; Female ; Follow-Up Studies ; Humans ; Hypertension ; Incidence ; Intracranial Aneurysm ; Magnetic Resonance Angiography ; Medical Records ; Middle Cerebral Artery ; Monitoring, Physiologic ; Multivariate Analysis ; Recurrence ; Retrospective Studies ; Risk Factors ; Smoke ; Smoking ; Survival Rate

Purpose: To explore cerebrovascular reservoir (CVR) and arterial transit time (ATT) changes using acetazolamide-challenged multi-phase arterial spin labeling (MP-ASL) perfusion-weighted MRI in chronic cerebrovascular steno-occlusive disease. Materials and Methods: This retrospective study enrolled patients with chronic steno-occlusion who underwent acetazolamide-challenged MP-ASL between June 2019 and October 2020.Cerebral blood flow, CVR, basal ATT, and ATT changes associated with severe stenosis, total occlusion, and chronic infarction lesions were compared. Results: There were 32 patients (5 with bilateral steno-occlusion) in our study sample. The CVR was significantly reduced during total occlusion compared with severe stenosis (26.2% ± 28.8% vs. 41.4% ± 34.1%, respectively, p = 0.004). The ATT changes were not significantly different (p = 0.717). The CVR was marginally lower in patients with chronic infarction (29.6% ± 39.1% vs. 38.9% ± 28.7%, respectively, p = 0.076). However, the ATT was less shortened in pa-tients with chronic infarction (-54 ± 135 vs. -117 ± 128 ms, respectively, p = 0.013). Conclusion Acetazolamide-challenged MP-ASL provides an MRI-based CVR evaluation tool for chronic steno-occlusive disease.