Woo Hyun Shim

Web-Based Malignancy Risk Estimation for Thyroid Nodules Using Ultrasonography Characteristics: Development and Validation of a Predictive Model

BACKGROUND To establish a practical and simplified method for analyzing thyroid nodules in a clinical setting, the development of a new practical prediction model was required. This study aimed to construct and validate a simple and reliable web-based predictive model using the ultrasonography characteristics of thyroid nodules to stratify the risk of malignancy. METHODS To analyze ultrasonography images, radiologists were asked to assess thyroid nodules according to the following criteria: internal content, echogenicity of the solid portion, shape, margin, and calcifications. Multivariate logistic regression was performed to predict whether nodules were diagnosed as malignant or benign. The developmental data set included 849 nodules (January-June 2003). The validation set included different data (n = 453, June 2008-February 2009). RESULTS Ultrasonography features, including solid content, taller-than-wide shape, spiculated margin, ill-defined margin, hypoechogenicity, marked hypoechogenicity, microcalicifications, and rim calcifications, were selected as predictors for malignant nodules in the development set. A 14-point risk scoring system was developed. Malignancy risk ranged from 3.8% to 97.4%, and the risk of malignancy was positively associated with increases in risk scores. The areas under the receiver operating characteristic curve of the development and validation sets were 0.903 and 0.897, respectively. CONCLUSION A simple and reliable web-based predictive model was designed using ultrasonography characteristics to stratify thyroid nodules according to the probability of malignancy.

Core-needle biopsy versus repeat fine-needle aspiration for thyroid nodules initially read as atypia/follicular lesion of undetermined significance

The purpose of this study was to evaluate the role of core‐needle biopsy (CNB) by comparing the results of CNB and repeat fine‐needle aspiration (FNA) for thyroid nodules that are initially read as atypia/follicular lesion of undetermined significance (AUS/FLUS) on FNA.

Up to 52 administrations of macrocyclic ionic MR contrast agent are not associated with intracranial gadolinium deposition: Multifactorial analysis in 385 patients

Purpose To determine whether multiple repeated administrations of gadolinium-based macrocyclic ionic MR contrast agent (MICA) are associated with intracranial gadolinium deposition and identify the predisposing factors for deposition in various clinical situations. Materials and methods In this institutional review board-approved retrospective study, 385 consecutive patients who underwent MICA-enhanced MR imaging were enrolled. The dentate nucleus-to-pons (DN/P) and globus pallidus-to-thalamus (GP/Th) signal intensity (SI) ratios on unenhanced T1-weighted images were recorded by 2 independent readers and averaged. The mean DN/P and GP/Th SI ratio difference between the last and the first examinations were tested using the one-sample t-test. Student’s t-test and stepwise regression analysis were used to identify the predisposing factors for deposition based on the number of administrations, time interval, hepatic and renal function, magnetic field strength, and chemo- or radiation therapy. Results The mean DN/P SI ratio difference was not different from zero (P = .697), even in patients with ≥20 administrations (n = 33). Only patients with abnormal renal function showed an increase in the mean DN/P SI ratio difference (P = .019). The mean DN/P SI ratio difference was not associated with any predisposing factors. However, the mean GP/Th SI ratio difference showed decrease (P < .001), which was associated with age (P = .007), number of administrations (P = .01) and number of radiation therapy sessions (P = .022) on multivariate analysis. Conclusion Multiple repeated administrations of MICA were not associated with increased T1 signal intensity in deep brain nuclei suggestive of Gd deposition in patients with normal renal function.

Tumor Vascular Permeability Pattern Is Associated With Complete Response in Immunocompetent Patients With Newly Diagnosed Primary Central Nervous System Lymphoma: Retrospective Cohort Study

AbstractA dynamic contrast-enhanced MR imaging (DCE-MRI) could provide the information about tumor drug delivery efficacy. We investigated the potential utility of the permeability pattern of DCE-MRI for predicting tumor response to high dose-methotrexate treatment and progression-free survival (PFS) in patients with primary CNS lymphoma (PCNSL). Clinical and conventional imaging parameters were assessed as potential predictors of tumor response in 48 immunocompetent PCNSL patients in a preliminary study. Fifty additional immunocompetent patients (27 men and 23 women; mean age, 60.6 years) with PCNSL underwent DCE-MRI before starting first-line treatment with high dose-methotrexate. The DCE-MRI pattern was categorized as diffuse or nondiffuse. After 4 courses of high dose methotrexate, patients underwent follow-up brain MR imaging to identify their complete response (CR). Predictors of CR and PFS were analyzed using clinical parameters, conventional MRI, and DCE-MRI. CR was noted in 20 (74.1%) of 27 patients with diffuse DCE-MRI pattern and in 4 (17.4%) of 23 patients with nondiffuse DCE-MRI pattern. The diffuse DCE-MRI pattern showed a significantly higher association with CR than the nondiffuse pattern (P < 0.001). Multivariate Cox proportional hazards model revealed that the DCE-MRI pattern (hazard ratio = 0.70; P = 0.045), age (hazard ratio = 1.47; P = 0.041), and adjuvant autologous stem-cell transplantation (hazard ratio = 6.97; P = 0.003) tended to be associated with a PFS. The pretreatment diffuse DCE-MRI pattern can be used as a potential imaging biomarker for predicting CR and a longer PFS in patients with newly diagnosed PCNSLs.

Differentiation of Recurrent Glioblastoma from Delayed Radiation Necrosis by Using Voxel-based Multiparametric Analysis of MR Imaging Data

Purpose To assess a volume-weighted voxel-based multiparametric (MP) clustering method as an imaging biomarker to differentiate recurrent glioblastoma from delayed radiation necrosis. Materials and Methods The institutional review board approved this retrospective study and waived the informed consent requirement. Seventy-five patients with pathologic analysis-confirmed recurrent glioblastoma (n = 42) or radiation necrosis (n = 33) who presented with enlarged contrast material-enhanced lesions at magnetic resonance (MR) imaging after they completed concurrent chemotherapy and radiation therapy were enrolled. The diagnostic performance of the total MP cluster score was determined by using the area under the receiver operating characteristic curve (AUC) with cross-validation and compared with those of single parameter measurements (10% histogram cutoffs of apparent diffusion coefficient [ADC10] or 90% histogram cutoffs of normalized cerebral blood volume and initial time-signal intensity AUC). Results Receiver operating characteristic curve analysis showed that an AUC for differentiating recurrent glioblastoma from delayed radiation necrosis was highest in the total MP cluster score and lowest for ADC10 for both readers. The total MP cluster score had significantly better diagnostic accuracy than any single parameter (corrected P = .001-.039 for reader 1; corrected P = .005-.041 for reader 2). The total MP cluster score was the best predictor of recurrent glioblastoma (cross-validated AUCs, 0.942-0.946 for both readers), with a sensitivity of 95.2% for reader 1 and 97.6% for reader 2. Conclusion Quantitative analysis with volume-weighted voxel-based MP clustering appears to be superior to the use of single imaging parameters to differentiate recurrent glioblastoma from delayed radiation necrosis.

Perfusion of surgical cavity wall enhancement in early post-treatment MR imaging may stratify the time-to-progression in glioblastoma

Objective To determine if perfusion in surgical cavity wall enhancement (SCWE) obtained in early post-treatment MR imaging can stratify time-to-progression (TTP) in glioblastoma. Materials and methods This study enrolled 60 glioblastoma patients with more than 5-mm-thick SCWEs as detected on contrast-enhanced MR imaging after concurrent chemoradiation therapy. Two independent readers categorized the shape and perfusion state of SCWEs as nodular or non-nodular and as having positive or negative perfusion compared with the contralateral grey matter on arterial spin labeling (ASL). The perfusion fraction on ASL within the contrast-enhancing lesion was calculated. The independent predictability of TTP was analyzed using the Kaplan-Meier method and Cox proportional hazards modelling. Results The perfusion fraction was higher in the non-progression group, significantly for reader 2 (P = 0.03) and borderline significantly for reader 1 (P = 0.08). A positive perfusion state and (P = 0.02) a higher perfusion fraction of the SCWE were found to become an independent predictor of longer TTP (P = 0.001 for reader 1 and P < 0.001 for reader 2). The contrast enhancement pattern did not become a TTP predictor. Conclusion Assessment of perfusion in early post-treatment MR imaging can stratify TTP in patients with glioblastoma for adjuvant temozolomide therapy. Positive perfusion in SCWEs can become a predictor of a longer TTP.

Deep Learning–Based Computer-Aided Diagnosis System for Localization and Diagnosis of Metastatic Lymph Nodes on Ultrasound: A Pilot Study

BACKGROUND The presence of metastatic lymph nodes is a prognostic indicator for patients with thyroid carcinomas and is an important determinant of clinical decision making. However, evaluating neck lymph nodes requires experience and is labor- and time-intensive. Therefore, the development of a computer-aided diagnosis (CAD) system to identify and differentiate metastatic lymph nodes may be useful. METHODS From January 2008 to December 2016, we retrieved clinical records for 804 consecutive patients with 812 lymph nodes. The status of all lymph nodes was confirmed by fine-needle aspiration. The datasets were split into training (263 benign and 286 metastatic lymph nodes), validation (30 benign and 33 metastatic lymph nodes), and test (100 benign and 100 metastatic lymph nodes). Using the VGG-Class Activation Map model, we developed a CAD system to localize and differentiate the metastatic lymph nodes. We then evaluated the diagnostic performance of this CAD system in our test set. RESULTS In the test set, the accuracy, sensitivity, and specificity of our model for predicting lymph node malignancy were 83.0%, 79.5%, and 87.5%, respectively. The CAD system clearly detected the locations of the lymph nodes, which not only provided identifying data, but also demonstrated the basis of decisions. CONCLUSION We developed a deep learning-based CAD system for the localization and differentiation of metastatic lymph nodes from thyroid cancer on ultrasound. This CAD system is highly sensitive and may be used as a screening tool; however, as it is relatively less specific, the screening results should be validated by experienced physicians.

Web-based thyroid imaging reporting and data system: Malignancy risk of atypia of undetermined significance or follicular lesion of undetermined significance thyroid nodules calculated by a combination of ultrasonography features and biopsy results

The purpose of this study was to construct a web‐based predictive model using ultrasound characteristics and subcategorized biopsy results for thyroid nodules of atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS) to stratify the risk of malignancy.

COMPARISON OF QUANTITATIVE TAU DEPOSITION ON THK-5351 PET IMAGING AND HIPPOCAMPAL VOLUME IN DIAGNOSIS OF ALZHEIMER’S DISEASE SPECTRUM

into 44 channels (42 x 30mm and 2 x 8mm). The Stroop task required participants to name pairs of items in the control condition and say the opposite name for the Stroop condition. Data were block averaged and mean haemodynamic response functions for each condition compared on a channel-by-channel basis. Results: Preliminary results in adults with DS aged 30-37 show that our fNIRS headgear is well tolerated and our task is accessible (9/9 participants completed it). Our results have highlighted areas showing differences in activation between Stroop and control conditions, giving targets for future region-of-interest analyses (Figure 2). We are now collecting data from a larger group of adults with DS of all ages, including individuals who are showing early signs of AD.Wewill present findings from these new studies, exploring differences in cortical activity related to age and cognitive decline. Conclusions:fNIRS is well-tolerated in adults with Down syndrome. Future work should focus on developing new paradigms for use in this population and explore resting-state activity.