Deep-learned 3D black-blood imaging using automatic labelling technique and 3D convolutional neural networks for detecting metastatic brain tumors

Black-blood (BB) imaging is used to complement contrast-enhanced 3D gradient-echo (CE 3D-GRE) imaging for detecting brain metastases, requiring additional scan time. In this study, we proposed deep-learned 3D BB imaging with an auto-labelling technique and 3D convolutional neural networks for brain metastases detection without additional BB scan. Patients were randomly selected for training (29 sets) and testing (36 sets). Two neuroradiologists independently evaluated deep-learned and original BB images, assessing the degree of blood vessel suppression and lesion conspicuity. Vessel signals were effectively suppressed in all patients. The figure of merits, which indicate the diagnostic performance of radiologists, were 0.9708 with deep-learned BB and 0.9437 with original BB imaging, suggesting that the deep-learned BB imaging is highly comparable to the original BB imaging (difference was not significant; p = 0.2142). In per patient analysis, sensitivities were 100% for both deep-learned and original BB imaging; however, the original BB imaging indicated false positive results for two patients. In per lesion analysis, sensitivities were 90.3% for deep-learned and 100% for original BB images. There were eight false positive lesions on the original BB imaging but only one on the deep-learned BB imaging. Deep-learned 3D BB imaging can be effective for brain metastases detection.ope

구강암 환자에서 감시 림프절 탐지를 위한 자기공명림프관조영술에 대한 연구

의학과/박사Background and Purpose: Identification of sentinel lymph nodes (LNs) is important because sentinel LN biopsy is used as an alternative procedure to elective neck dissection in patients with oral cavity cancer and clinically negative neck. The purpose of this study was to evaluate the feasibility of magnetic resonance (MR) lymphography with interstitial injection of a gadolinium-based contrast agent for identifying sentinel LNs in patients with oral cavity cancer and clinically negative neck. Methods: A total of 26 patients with resectable oral cavity cancer and clinically negative neck were recruited for this study. After peritumoral injection of 1-ml diluted gadobutrol, pretreatment MR lymphography with Differential Sub-sampling with Cartesian Ordering (DISCO) sequence was performed. The accuracy of sentinel LN identification of MR lymphography was assessed and compared with the final histopathological results after elective neck dissection. Results: MR lymphography consistently visualized the 44 sentinel LNs, defined as the first LNs to show any enhancement at the periphery portion of LNs near the injection site, in all 26 patients. After elective neck dissection, 42 assumed sentinel LNs were obtained in 24 patients, and histopathology revealed that 27 LNs from 11 patients were metastatic. In all but one patient with pathologically positive neck, assumed sentinel LNs revealed metastatic involvement. Conclusions: Pretreatment MR lymphography is a safe and feasible imaging technique that can help clinicians identify sentinel LNs with a high risk of occult metastases in patients with oral cavity cancer and clinically negative neck, enabling focused preoperative biopsy in these high-risk patientsopen박

COMPUTER DEVICE FOR EDGE COMPUTING QUEUE STABILIZATION USING REINFORCEMENT LEARNING BASED ON LIAPUNOV OPTIMIZATION, AND METHOD OF THE SAME

본 개시는 리아푸노프(Liapunov) 최적화 기반 강화학습(reinforcement learning; RL)을 활용한 에지 컴퓨팅 대기열 안정화를 위한 컴퓨터 장치 및 그의 방법을 제공한다. 본 개시는 엄밀한 수학 이론과 시뮬레이션을 바탕으로 하여, 실제 기술에 직접 적용될 수 있는 기법이다. 본 개시에 따르면, 리아푸노프 최적화를 기반으로 강화학습을 활용하기 때문에, 에지 컴퓨팅 서버가 설치되는 각 상황에 맞도록 자체적으로 학습을 하여 가장 효율적인 대기열 안정화 기법을 학습해 나아가며, 리아푸노프 최적화 기법으로 인하여 더 빠르고 정확한 안정화가 가능해진다

Intra-Suprasellar Schwannoma Presumably Originating from the Internal Carotid Artery Wall : Case Report and Review of the Literature

Intracranial schwannomas are common but intra-suprasellar schwannomas are extremely rare. We represent the case of a 57-year-old woman with an intra-suprasellar tumor that was presurgically diagnosed as an anterior clinoidal meningioma. Intraoperatively it adhered tightly to the internal carotid artery wall and could not easily be dissected, possibly leading to profuse hemorrhage and sacrifice of the carotid artery with coil embolization. Histopathology demonstrated a schwannoma. We reviewed and summarized the clinical, imaging, and intraoperative findings of previously reported intra-suprasellar schwannomas.restrictio

MR lymphography for sentinel lymph node detection in patients with oral cavity cancer: Preliminary clinical study

BACKGROUND: The purpose of this study was to evaluate the feasibility of MR lymphography with interstitial injection of a gadolinium-based contrast agent for identifying sentinel lymph nodes in patients with oral cavity cancer and clinically negative neck. METHODS: Pretreatment MR lymphography with a differential subsampling with cartesian ordering (DISCO) sequence was performed in 26 patients with resectable oral cavity cancer and clinically negative neck, after peritumoral injection of 1-mL diluted gadobutrol. The accuracy of sentinel lymph node identification by MR lymphography was assessed and compared with the final histopathological results. RESULTS: The MR lymphography consistently visualized the 44 sentinel lymph nodes in all 26 patients. In all but 1 patient with pathologically positive neck, assumed sentinel lymph nodes revealed metastatic involvement. CONCLUSION: Pretreatment MR lymphography is a safe and feasible imaging technique that can help clinicians identify sentinel lymph nodes with a high risk of occult metastases in patients with oral cavity cancer, enabling focused preoperative biopsy in these high-risk patients.restrictio

The added prognostic value of radiological phenotype combined with clinical features and molecular subtype in anaplastic gliomas

PURPOSE: To determine whether radiological phenotype can improve the predictive performance of the risk model based on molecular subtype and clinical risk factors in anaplastic glioma patients. METHODS: This retrospective study was approved by our institutional review board with waiver of informed consent. MR images of 86 patients with pathologically diagnosed anaplastic glioma (WHO grade III) between January 2007 and February 2016 were analyzed according to the Visually Accessible Rembrandt Images (VASARI) features set. Significant imaging findings were selected to generate a radiological risk score (RRS) for overall survival (OS) and progression-free survival (PFS) using the least absolute shrinkage and selection operator (LASSO) Cox regression model. The prognostic value of RRS was evaluated with multivariate Cox regression including molecular subtype and clinical risk factors. The C-indices of multivariate models with and without RRS were compared by bootstrapping. RESULTS: Eight VASARI features contributed to RRS for OS and six contributed to PFS. Multifocality or multicentricity was the most influential feature, followed by restricted diffusion. RRS was significantly associated with OS and PFS (P < .001), as well as age and molecular subtype. The multivariate model with RRS demonstrated a significantly higher predictive performance than the model without (C-index difference: 0.074, 95% confidence interval [CI]: 0.031, 0.148 for OS; C-index difference: 0.054, 95% CI: 0.014, 0.123 for PFS). CONCLUSION: RRS derived from VASARI features was an independent predictor of survival in patients with anaplastic gliomas. The addition of RRS significantly improved the predictive performance of the molecular feature based model.restrictio

Detection of clinically occult primary tumours in patients with cervical metastases of unknown primary tumours: comparison of three-dimensional THRIVE MRI, two-dimensional spin-echo MRI, and contrast-enhanced CT

AIM: To evaluate and compare the utility of contrast-enhanced three-dimensional (3D) T1-weighted high-resolution isotropic volume examination (THRIVE), spin-echo (SE) T1-weighted magnetic resonance imaging (MRI), and computed tomography (CT) for detecting clinically occult primary tumours in patients with cervical lymph node metastases. MATERIALS AND METHODS: Seventy-three consecutive patients with tumours that went undetected during endoscopic or physical examinations underwent preoperative contrast-enhanced CT and MRI (SE and 3D THRIVE) after gadolinium injection. Guided biopsy results served as reference standards. The diagnostic performances of the imaging techniques were compared with McNemar's tests. RESULTS: Primary tumours were identified in 59 (80.8%) of the 73 patients after surgery. Of these, 36 were found in the palatine tonsil, 11 in the base of the tongue, seven in the nasopharynx, and five in the pyriform sinus. The sensitivity (72.9%) and accuracy (71.2%) of 3D THRIVE for detecting primary tumours were higher than were those of SE T1-weighted MRI (49.2% and 53.4%, p0.05). CONCLUSION: 3D THRIVE was more sensitive at detecting primary tumours than was SE T1-weighted MRI or CT in patients with cervical metastases of unknown primary tumours. This sequence may improve biopsy and therapeutic planning in these patients.restrictio

Gadolinium deposition in the brain: association with various GBCAs using a generalized additive model

OBJECTIVES: To determine the relationship between the number of administrations of various gadolinium-based contrast agents (GBCAs) and increased T1 signal intensity in the globus pallidus (GP) and dentate nucleus (DN). METHODS: This retrospective study included 122 patients who underwent double-dose GBCA-enhanced magnetic resonance imaging. Two radiologists calculated GP-to-thalamus (TH) signal intensity ratio, DN-to-pons signal intensity ratio and relative change (Rchange) between the baseline and final examinations. Interobserver agreement was evaluated. The relationships between Rchange and several factors, including number of each GBCA administrations, were analysed using a generalized additive model. RESULTS: Six patients (4.9%) received linear GBCAs (mean 20.8 number of administration; range 15-30), 44 patients (36.1%) received macrocyclic GBCAs (mean 26.1; range 14-51) and 72 patients (59.0%) received both types of GBCAs (mean 31.5; range 12-65). Interobserver agreement was almost perfect (0.99; 95% CI: 0.99-0.99). Rchange (DN:pons) was associated with gadodiamide (p = 0.006) and gadopentetate dimeglumine (p < 0.001), but not with other GBCAs. Rchange (GP:TH) was not associated with GBCA administration. CONCLUSIONS: Previous administration of linear agents gadoiamide and gadopentetate dimeglumine is associated with increased T1 signal intensity in the DN, whereas macrocyclic GBCAs do not show an association. KEY POINTS: • Certain linear GBCAs are associated with T1 signal change in the dentate nucleus. • The signal change is related to the administration number of certain linear GBCAs. • Difference in signal change may reflect differences in stability of agents.restrictio

Uterine Artery Embolization for Adenomyosis: Percentage of Necrosis Predicts Midterm Clinical Recurrence

PURPOSE: To evaluate the effect of degree of necrosis after uterine artery embolization (UAE) on symptom recurrence at midterm clinical follow-up in patients with adenomyosis. MATERIALS AND METHODS: Women (N = 50) who underwent UAE for symptomatic adenomyosis were retrospectively analyzed. All patients underwent contrast-enhanced magnetic resonance (MR) imaging at baseline and 3 months after UAE and were followed clinically for at least 18 months. The type of adenomyosis was classified as focal or diffuse. The uterine volume and the percentage of necrosis after embolization were measured three-dimensionally on MR imaging. The percentage of the necrosis cutoff point for predicting recurrence was estimated. Patients were divided into 2 groups according to the cutoff point. The rate of recurrence was compared between groups, and risk factors for recurrence were identified. RESULTS: During the follow-up period (range, 18-48 mo), symptom recurrence occurred in 12 of 50 patients. A necrosis cutoff point of 34.3% was calculated to predict recurrence (area under the curve = 0.721; 95% confidence interval [CI] = 0.577-0.839; P = .004). Patients with 34.3% necrosis (group B, n = 38; hazard ratio = 7.0; 95% CI = 2.2, 22.4; P = .001). Initial uterine volume and type of adenomyosis were not associated with recurrence. CONCLUSIONS: The percentage of necrosis in patients with adenomyosis after UAE may predict symptom recurrence at midterm follow-up. The cutoff percentage of necrosis required to predict symptom recurrence was 34.3% in this study.restrictio

Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach

OBJECTIVES: To evaluate the diagnostic performance of magnetic resonance (MR) radiomics-based machine-learning algorithms in differentiating primary central nervous system lymphoma (PCNSL) from non-necrotic atypical glioblastoma (GBM). METHODS: Seventy-seven patients (54 individuals with PCNSL and 23 with non-necrotic atypical GBM), diagnosed from January 2009 to April 2017, were enrolled in this retrospective study. A total of 6,366 radiomics features, including shape, volume, first-order, texture, and wavelet-transformed features, were extracted from multi-parametric (post-contrast T1- and T2-weighted, and fluid attenuation inversion recovery images) and multiregional (enhanced and non-enhanced) tumour volumes. These features were subjected to recursive feature elimination and random forest (RF) analysis with nested cross-validation. The diagnostic abilities of a radiomics machine-learning classifier, apparent diffusion coefficient (ADC), and three readers, who independently classified the tumours based on conventional MR sequences, were evaluated using receiver operating characteristic (ROC) analysis. Areas under the ROC curves (AUC) of the radiomics classifier, ADC value, and the radiologists were compared. RESULTS: The mean AUC of the radiomics classifier was 0.921 (95 % CI 0.825-0.990). The AUCs of the three readers and ADC were 0.707 (95 % CI 0.622-0.793), 0.759 (95 %CI 0.656-0.861), 0.695 (95 % CI 0.590-0.800) and 0.684 (95 % CI0.560-0.809), respectively. The AUC of the radiomics-based classifier was significantly higher than those of the three readers and ADC (p< 0.001 for all). CONCLUSIONS: Large-scale radiomics with a machine-learning algorithm can be useful for differentiating PCNSL from atypical GBM, and yields a better diagnostic performance than human radiologists and ADC values.restrictio