Yonsei University · 医学
Professor Dae Chul Jung's research lab specializes in diagnostic and interventional radiology, with a strong focus on medical imaging technologies and their applications in urological and genitourinary diseases. The lab investigates advanced imaging techniques such as CT, ultrasonography, and dual-energy CT to improve the diagnosis and classification of renal and penile pathologies, including renal masses, erectile dysfunction, and cystic lesions. A key research direction involves leveraging machine learning and quantitative imaging features to enhance the accuracy of differential diagnosis in renal tumors, such as distinguishing focal parenchymal angiomyolipoma from clear cell renal cell carcinoma. The lab also explores radiation dose optimization and image reconstruction methods to improve the detection of subtle pathologies like small renal cysts.
Figures are computed from collected data and may differ slightly.
Renal papillary necrosis is not a pathologic entity but rather a descriptive term for a condition--necrosis of the renal papillae--that has various possible causes. The renal medulla and papillae are vulnerable to ischemic necrosis because of the peculiar arrangement of their blood supply and the hypertonic environment. The etiology of renal papillary necrosis includes diabetes, analgesic abuse or overuse, sickle cell disease, pyelonephritis, renal vein thrombosis, tuberculosis, and obstructive
Penile Doppler ultrasonography is a high-performing, noninvasive or minimally-invasive imaging modality that allows the depiction of the normal anatomy and macroscopic pathologic changes in real time. Moreover, functional changes in penile blood flow, as seen in erectile dysfunction (ED), can be analyzed using color Doppler ultrasonography (CDUS). This review article describes the normal sonographic anatomy of the penis, the sonographic technique for evaluating ED, the normal phases of erection,
We achieved less pseudoenhancement of renal cysts with virtual monochromatic images of DECT compared with conventional single-energy CT. This method may be useful when an accurate differentiation between small renal cysts and solid masses is critical.
We propose a computer-aided classification system for distinguishing fp-AML from ccRCC using machine learning classifiers with quantitative texture features. Our contribution is to investigate the proper combination between the quantitative features and classification systems on the CE MDCT images. In experiments, it can be demonstrated that (a) the features based on histogram characteristics on bright intensity region and texture patterns on inhomogeneity inside masses were selected as key feat
Renal VII is typically lower in DN than in controls and moderately correlated with SCC, which reflects renal function in DN, but does not offer a significant advantage over arterial resistance index.
Diffuse or partial thickening of the cyst wall with dark-signal-intensity in multilocular cystic masses may suggest ovarian cystadenofibroma, and this type of appearance may be as common as the previously reported characteristic appearance. A prominent solid component with a higher T2-signal intensity and strong enhancement are the typical findings of cystadenocarcinofibroma.
In the xenografted prostate cancer model, the ADC values of the solid portion of the tumors are significantly correlated with tumor necrosis and MVD of the pathologic specimens. The ADC values may be utilized as surrogate markers for the noninvasive assessment of tumor necrosis and MVD in high-grade prostate cancer.
Neurilemmoma of the glans penis is rare, and no imaging findings have been reported. A case of neurilemmoma of the glans penis is presented. Ultrasonography (US) and magnetic resonance imaging revealed a well-defined small mass in the glans penis. The mass appeared hypoechoic on gray-scale US and hypervascular on color Doppler US. Magnetic resonance imaging revealed high signal intensity of the mass on a T2-weighted image and strong enhancement on a contrast-enhanced T1-weighted image.
The classification system of SVL on the basis of their imaged morphologic features can provide an objective standard and simplify the abnormal findings to help predict SVI in prostate cancer. Pattern analysis of SVL with MR imaging improves the accuracy of detecting SVI.
Objective: To assess the relationship between apparent diffusion coefficient (ADC) values on diffusion-weighted magnetic resonance (MR) imaging and pathologic measures of a tumor using a prostate cancer xenograft model. Materials and Methods: Eighteen athymic nude mice with 36 PC-3-induced tumors were sacrificed to obtain specimens immediately after MR imaging in order to compare the findings on MR images with those seen on pathological specimens. Using a high-field small-animal MR scanner, T1-
Open papers in the app to read, cite, and organize with AI.
