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Abstract Background The cholinergic neurotransmitter system is crucial to cognitive function, with the basal forebrain (BF) being particularly susceptible to Alzheimer’s disease (AD) pathology. However, the interaction of white matter hyperintensities (WMH) in cholinergic pathways and BF atrophy without amyloid pathology remains poorly understood. Methods We enrolled patients who underwent neuropsychological tests, magnetic resonance imaging, and 18F-florbetaben positron emission tomography due to cognitive impairment at the teaching university hospital from 2015 to 2022. Among these, we selected patients with negative amyloid scans and additionally excluded those with Parkinson’s dementia that may be accompanied by BF atrophy. The WMH burden of cholinergic pathways was quantified by the Cholinergic Pathways Hyperintensities Scale (CHIPS) score, and categorized into tertile groups because the CHIPS score did not meet normal distribution. Segmentation of the BF on volumetric T1-weighted MRI was performed using FreeSurfer, then was normalized for total intracranial volume. Multivariable regression analysis was performed to investigate the association between BF volumes and CHIPS scores. Results A total of 187 patients were enrolled. The median CHIPS score was 12 [IQR 5.0; 24.0]. The BF volume of the highest CHIPS tertile group (mean ± SD, 3.51 ± 0.49, CHIPSt3) was significantly decreased than those of the lower CHIPS tertile groups (3.75 ± 0.53, CHIPSt2; 3.83 ± 0.53, CHIPSt1; P = 0.02). In the univariable regression analysis, factors showing significant associations with the BF volume were the CHIPSt3 group, age, female, education, diabetes mellitus, smoking, previous stroke history, periventricular WMH, and cerebral microbleeds. In multivariable regression analysis, the CHIPSt3 group (standardized beta [β std] = -0.25, P = 0.01), female (β std = 0.20, P = 0.04), and diabetes mellitus (β std = -0.22, P

ObjectivesWe aim to assess the pooled incidence of immune effector cell-associated neurotoxicity syndrome (ICANS) in clinical trials and real-world studies of chimeric antigen receptor (CAR) T-cell therapy for hematologic malignancy and compare the incidences among different agents.MethodsThe PubMed, Embase, and Web of Science databases were searched for clinical trials and real-world studies. An inverse-variance weighting model was used to calculate pooled incidences and subgroup analyses. Multivariable analysis was conducted using binomial-normal modeling.ResultsSeventy-five trials comprising 3,184 patients were included. The overall pooled incidence was 26.9% (95% CI, 21.7–32.7%) for all-grade and 10.5% (95% CI, 8.1–13.6%) for high-grade ICANS. In subgroup analysis, cohorts with anti-CD19 drugs had significantly higher ICANS incidences than cohorts with other agents. The multivariable analysis demonstrated higher odds of ICANS in anti-CD19 drug studies for high-grade (OR, 4.6) compared to anti-BCMA drug studies. In 12 real-world studies, studies used axicabtagene ciloleucel with CD28 (54.0% all-grade, 26.4% high-grade) exhibited significantly higher rates of all-grade and high-grade ICANS than studies using tisagenlecleucel with 4-1BB (17.2% all-grade, 6.1% high-grade).ConclusionsThe overall incidences of ICANS with CAR T-cell therapy were 26.9% for all-grade and 10.5% for high-grade. Compared with other agents, patients with anti-CD19 drugs had a significantly increased risk of developing high-grade ICANS. Therefore, careful monitoring of ICANS should be considered for patients undergoing CAR T-cell therapy.

IntroductionAlthough white matter hyperintensity (WMH) shares similar vascular risk and pathology with small vessel occlusion (SVO) stroke, there were few studies to evaluate the impact of the burden of WMH volume on early and delayed stroke outcomes in SVO stroke.Materials and methodsUsing a multicenter registry database, we enrolled SVO stroke patients between August 2013 and November 2022. The WMH volume was estimated by automated methods using deep learning (VUNO Med-DeepBrain, Seoul, South Korea), which was a commercially available segmentation model. After propensity score matching (PSM), we evaluated the impact of WMH volume on early neurological deterioration (END) and poor functional outcomes at 3-month modified Ranking Scale (mRS), defined as mRS score >2 at 3 months, after an SVO stroke.ResultsAmong 1,718 SVO stroke cases, the prevalence of subjects with severe WMH (Fazekas score ≥ 3) was 68.9%. After PSM, END and poor functional outcomes at 3-month mRS (mRS > 2) were higher in the severe WMH group (END: 6.9 vs. 13.5%, p < 0.001; 3-month mRS > 2: 11.4 vs. 24.7%, p < 0.001). The logistic regression analysis using the PSM cohort showed that total WMH volume increased the risk of END [odd ratio [OR], 95% confidence interval [CI]; 1.01, 1.00–1.02, p = 0.048] and 3-month mRS > 2 (OR, 95% CI; 1.02, 1.01–1.03, p < 0.001). Deep WMH was associated with both END and 3-month mRS > 2, but periventricular WMH was associated with 3-month mRS > 2 only.ConclusionThis study used automated methods using a deep learning segmentation model to assess the impact of WMH burden on outcomes in SVO stroke. Our findings emphasize the significance of WMH burden in SVO stroke prognosis, encouraging tailored interventions for better patient care.

Abstract Quantification of diffusion restriction lesions in sporadic Creutzfeldt-Jakob disease (sCJD) may provide information of the disease burden. We aim to develop an automatic segmentation model for sCJD and to evaluate the volume of disease extent as a prognostic marker for overall survival. Fifty-six patients (mean age ± SD, 61.2 ± 9.9 years) were included from February 2000 to July 2020. A threshold-based segmentation was used to obtain abnormal signal intensity masks. Segmented volumes were compared with the visual grade. The Dice similarity coefficient was calculated to measure the similarity between the automatic vs. manual segmentation. Cox proportional hazards regression analysis was performed to evaluate the volume of disease extent as a prognostic marker. The automatic segmentation showed good correlation with the visual grading. The cortical lesion volumes significantly increased as the visual grade aggravated (extensive: 112.9 ± 73.2; moderate: 45.4 ± 30.4; minimal involvement: 29.6 ± 18.1 mm3) (P

Abstract We aimed to investigate the detection rate of brain MR and MR angiography for neuroimaging abnormality in newly diagnosed left-sided infective endocarditis patients with/without neurological symptoms. This retrospective study included consecutive patients with definite or possible left-sided infective endocarditis according to the modified Duke criteria who underwent brain MRI and MR angiography between March 2015 and October 2020. The detection rate for neuroimaging abnormality on MRI was defined as the number of patients with positive brain MRI findings divided by the number of patients with left-sided infective endocarditis. Positive imaging findings included acute ischemic lesions, cerebral microbleeds, hemorrhagic lesions, and infectious aneurysms. In addition, aneurysm rupture rate and median period to aneurysm rupture were evaluated on follow-up studies. A total 115 patients (mean age: 55 years ± 19; 65 men) were included. The detection rate for neuroimaging abnormality was 77% (89/115). The detection rate in patients without neurological symptoms was 70% (56/80). Acute ischemic lesions, cerebral microbleeds, and hemorrhagic lesions including superficial siderosis and intracranial hemorrhage were detected on MRI in 56% (64/115), 57% (66/115), and 20% (23/115) of patients, respectively. In particular, infectious aneurysms were detected on MR angiography in 3% of patients (4/115), but MR angiography in 5 patients (4.3%) was insignificant for infectious aneurysm, which were detected using CT angiography (n = 3) and digital subtraction angiography (n = 2) during follow-up. Among the 9 infectious aneurysm patients, aneurysm rupture occurred in 4 (44%), with a median period of aneurysm rupture of 5 days. The detection rate of brain MRI for neuroimaging abnormality in newly diagnosed left-sided infective endocarditis patients was high (77%), even without neurological symptoms (70%).

Abstract The aim of the present study was to predict amyloid-beta positivity using a conventional T1-weighted image, radiomics, and a diffusion-tensor image obtained by magnetic resonance imaging (MRI). We included 186 patients with mild cognitive impairment (MCI) who underwent Florbetaben positron emission tomography (PET), MRI (three-dimensional T1-weighted and diffusion-tensor images), and neuropsychological tests at the Asan Medical Center. We developed a stepwise machine learning algorithm using demographics, T1 MRI features (volume, cortical thickness and radiomics), and diffusion-tensor image to distinguish amyloid-beta positivity on Florbetaben PET. We compared the performance of each algorithm based on the MRI features used. The study population included 72 patients with MCI in the amyloid-beta-negative group and 114 patients with MCI in the amyloid-beta-positive group. The machine learning algorithm using T1 volume performed better than that using only clinical information (mean area under the curve [AUC]: 0.73 vs. 0.69, p

Background and purposeTo develop and validate a deep learning-based automatic segmentation model for assessing intracranial volume (ICV) and to compare the accuracy determined by NeuroQuant (NQ), FreeSurfer (FS), and SynthSeg.Materials and methodsThis retrospective study included 60 subjects [30 Alzheimer’s disease (AD), 21 mild cognitive impairment (MCI), 9 cognitively normal (CN)] from a single tertiary hospital for the training and validation group (50:10). The test group included 40 subjects (20 AD, 10 MCI, 10 CN) from the ADNI dataset. We propose a robust ICV segmentation model based on the foundational 2D UNet architecture trained with four types of input images (both single and multimodality using scaled or unscaled T1-weighted and T2-FLAIR MR images). To compare with our model, NQ, FS, and SynthSeg were also utilized in the test group. We evaluated the model performance by measuring the Dice similarity coefficient (DSC) and average volume difference.ResultsThe single-modality model trained with scaled T1-weighted images showed excellent performance with a DSC of 0.989 ± 0.002 and an average volume difference of 0.46% ± 0.38%. Our multimodality model trained with both unscaled T1-weighted and T2-FLAIR images showed similar performance with a DSC of 0.988 ± 0.002 and an average volume difference of 0.47% ± 0.35%. The overall average volume difference with our model showed relatively higher accuracy than NQ (2.15% ± 1.72%), FS (3.69% ± 2.93%), and SynthSeg (1.88% ± 1.18%). Furthermore, our model outperformed the three others in each subgroup of patients with AD, MCI, and CN subjects.ConclusionOur deep learning-based automatic ICV segmentation model showed excellent performance for the automatic evaluation of ICV.

Abstract The limited accessibility of medical specialists for Alzheimer’s disease (AD) can make obtaining an accurate diagnosis in a timely manner challenging and may influence prognosis. We investigated whether VUNO Med-DeepBrain AD (DBAD) using a deep learning algorithm can be employed as a decision support service for the diagnosis of AD. This study included 98 elderly participants aged 60 years or older who visited the Seoul Asan Medical Center and the Korea Veterans Health Service. We administered a standard diagnostic assessment for diagnosing AD. DBAD and three panels of medical experts (ME) diagnosed participants with normal cognition (NC) or AD using T1-weighted magnetic resonance imaging. The accuracy (87.1% for DBAD and 84.3% for ME), sensitivity (93.3% for DBAD and 80.0% for ME), and specificity (85.5% for DBAD and 85.5% for ME) of both DBAD and ME for diagnosing AD were comparable; however, DBAD showed a higher trend in every analysis than ME diagnosis. DBAD may support the clinical decisions of physicians who are not specialized in AD; this may enhance the accessibility of AD diagnosis and treatment.

The incidence of neurodegenerative diseases in the older population has increased in recent years. A considerable number of studies have been performed to characterize these diseases. Imaging analysis is an important biomarker for the diagnosis of neurodegenerative disease. Objective and reliable assessment and precise detection are important for the early diagnosis of neurodegenerative diseases. Artificial intelligence (AI) using brain MRI applied to the study of neurodegenerative diseases could promote early diagnosis and optimal decisions for treatment plans. MRI-based AI software have been developed and studied worldwide. Representatively, there are MRI-based volumetry and segmentation software. In this review, we present the development process of brain volumetry analysis software in neurodegenerative diseases, currently used and developed AI software for neurodegenerative disease in the Republic of Korea, probable uses of AI in the future, and AI software limitations.

ObjectivesThe role of three-dimensional (3D) TOF-MRA in patients with cognitive impairment is not well established. We evaluated the diagnostic yield of 3D TOF-MRA for detecting incidental extra- or intracranial artery stenosis and intracranial aneurysm in this patient group.MethodsThis retrospective study included patients with cognitive impairment undergoing our brain MRI protocol from January 2013 to February 2020. The diagnostic yield of TOF-MRA for detecting incidental vascular lesions was calculated. Patients with positive TOF-MRA results were reviewed to find whether additional treatment was performed. Logistic regression analysis was conducted to identify the clinical risk factors for positive TOF-MRA findings.ResultsIn total, 1,753 patients (mean age, 70.2 ± 10.6 years; 1,044 women) were included; 199 intracranial aneurysms were detected among 162 patients (9.2%, 162/1,753). A 3D TOF-MRA revealed significant artery stenoses (>50% stenosis) in 162 patients (9.2%, 162/1,753). The overall diagnostic yield of TOF-MRA was 16.8% (294/1,753). Among them, 92 patients (31.3%, 92/294) underwent either medical therapy, endovascular intervention, or surgery. In total, eighty-one patients with stenosis were prescribed with either antiplatelet medications or lipid-lowering agent. In total, fifteen patients (aneurysm: 11 patients, stenosis: 4 patients) were further treated with endovascular intervention or surgery. Thus, the “number needed to scan” was 19 for identifying one patient requiring treatment. Multivariate logistic regression analysis showed that being female (odds ratio [OR] 2.05) and old age (OR 1.04) were the independent risk factors for intracranial aneurysm; being male (OR 1.52), old age (OR 1.06), hypertension (OR 1.78), and ischemic heart disease history (OR 2.65) were the independent risk factors for significant artery stenosis.ConclusionsOur study demonstrated the potential benefit of 3D TOF-MRA, given that it showed high diagnostic yield for detecting vascular lesions in patients with cognitive impairment and the considerable number of these lesions required further treatment. A 3D TOF-MRA may be included in the routine MR protocol for the work-up of this patient population, especially in older patients and patients with vascular risk factors.

Purpose The diagnostic performance of thyroid biopsy is influenced by several factors, including differences in the Bethesda categorization for malignancy, the inclusion or exclusion of non-diagnostic results, the definition used for the final diagnosis, and the definition of an inconclusive diagnosis. The purpose of this study was to provide an understanding of the factors influencing the diagnostic performance of thyroid biopsy. Methods We collected data retrospectively between January and December 2013 from a cohort of 6,762 thyroid nodules from 6,493 consecutive patients who underwent biopsy. In total, 4,822 nodules from 4,553 patients were included. We calculated the biopsy sensitivity according to the inclusion of different Bethesda categories in the numerator and the exclusion of non-diagnostic results, as well as the diagnostic accuracy according to different definitions of a benign diagnosis. We obtained the conclusive and inconclusive diagnosis rates. Results The sensitivity increased when more Bethesda categories were included in the numerator and when non-diagnostic results were excluded. When a benign thyroid nodule diagnosis was defined as benign findings on surgical resection, concordant benign results on at least two occasions, or an initial benign biopsy result and follow-up for more than 12 months, the accuracy was higher than when the diagnosis was based on surgical resection alone (91.1% vs. 68.7%). A higher conclusive diagnosis rate was obtained when Bethesda categories I and III were considered inconclusive than when Bethesda categories I, III and IV were considered inconclusive (78.3% vs. 72.8%, P

Purpose Thermal ablation is a novel treatment alternative for benign thyroid nodules, and one of the most promising thermal ablation techniques is radiofrequency ablation (RFA). Considering the increasing use of thyroid RFA, some scientific societies have proposed clinical practice guidelines. We systemically reviewed and compared these guidelines for thyroid RFA to identify a standard treatment strategy that represents the positions of most societies. Methods We searched the MEDLINE and EMBASE databases for studies with human participants that were published in English between January 1, 2000 and August 2, 2019. Studies containing clinical practice guidelines for the RFA of benign thyroid nodules were included. We extracted data regarding indications, pre- and post-procedural evaluations, treatment techniques, and the need to obtain informed consent. Results Of the 83 studies found, four studies were included, and one study was added after searching the bibliographies of those articles. The five included studies were guidelines developed by the Korean Society of Thyroid Radiology, a group of experts from Italian scientific societies, the Italian Working Group on Minimally Invasive Treatments of the Thyroid, the United Kingdom’s National Institute for Health and Clinical Excellence, and a group of four professional Austrian thyroid associations. Indications, pre- and post-procedural evaluations, and techniques were similar across studies; however, differences in each of these categories were found. Conclusion While the reviewed guidelines are similar with regard to major categories, international guidelines for the RFA of benign thyroid nodules should be established in the future.

BackgroundChimeric antigen receptor (CAR) T-cell therapy is a promising treatment option for patients with refractory hematological malignancies. However, its efficacy in glioblastoma remains unclear. Here, we performed a systematic review to summarize the safety and efficacy of CAR T-cell therapy in glioblastoma.MethodsThe PubMed, EMBASE, and Cochrane databases were searched to identify articles published before June 30, 2021 describing the use of CAR T-cell therapy in glioblastoma. Information on the toxicity of CAR T-cell therapy was summarized. The pooled objective response rate (ORR) and overall survival (OS) of patients who underwent CAR T-cell therapy were estimated using a random-effects model with an inverse-variance weighting model and quantile estimation method, respectively.ResultsOf 397 articles identified, eight studies including 63 patients with recurrent glioblastoma treated with various CAR T-cell regimens were included in the analysis. Six (9.5%) patients developed cytokine release syndrome (grade ≤2), and 16 (25.4%) experienced non-critical neurological events. The pooled ORR was 5.1% (95% confidence interval [CI], 0.0–10.4; I2 = 0.05%), and the pooled median OS was 8.1 months (95% CI, 6.7–9.5; I2 = 0.00%).ConclusionAlthough CAR T-cell therapy is a relatively safe therapeutic option in patients with glioblastoma, it shows marginal efficacy, suggesting that further research is necessary for its translation into clinical practice for the treatment of recurrent glioblastoma.

Doppler ultrasonography (US) is widely used for the differential diagnosis of thyroid nodules, metastatic cervical lymph nodes in patients with thyroid cancer, and diffuse parenchymal disease, as well as for guidance in various US-guided procedures, including biopsy and ablation. However, controversies remain regarding the appropriate use and interpretation of Doppler US. Therefore, the Korean Society of Thyroid Radiology organized a taskforce to develop a consensus statement on the clinical use of Doppler US for thyroid disease. The review and recommendations in this article are based on a comprehensive analysis of the current literature and the consensus of experts.

Purpose To validate the diagnostic performance of commercially available, deep learning-based automatic white matter hyperintensity (WMH) segmentation algorithm for classifying the grades of the Fazekas scale and differentiating subcortical vascular dementia. Methods This retrospective, observational, single-institution study investigated the diagnostic performance of a deep learning-based automatic WMH volume segmentation to classify the grades of the Fazekas scale and differentiate subcortical vascular dementia. The VUNO Med-DeepBrain was used for the WMH segmentation system. The system for segmentation of WMH was designed with convolutional neural networks, in which the input image was comprised of a pre-processed axial FLAIR image, and the output was a segmented WMH mask and its volume. Patients presented with memory complaint between March 2017 and June 2018 were included and were split into training (March 2017–March 2018, n = 596) and internal validation test set (April 2018–June 2018, n = 204). Results Optimal cut-off values to categorize WMH volume as normal vs. mild/moderate/severe, normal/mild vs. moderate/severe, and normal/mild/moderate vs. severe were 3.4 mL, 9.6 mL, and 17.1 mL, respectively, and the AUC were 0.921, 0.956 and 0.960, respectively. When differentiating normal/mild vs. moderate/severe using WMH volume in the test set, sensitivity, specificity, and accuracy were 96.4%, 89.9%, and 91.7%, respectively. For distinguishing subcortical vascular dementia from others using WMH volume, sensitivity, specificity, and accuracy were 83.3%, 84.3%, and 84.3%, respectively. Conclusion Deep learning-based automatic WMH segmentation may be an accurate and promising method for classifying the grades of the Fazekas scale and differentiating subcortical vascular dementia.

ObjectiveThere is a paucity of large cohort-based evidence regarding the need and added value of diffusion-weighted imaging (DWI) in patients attending outpatient clinic for cognitive impairment. We aimed to evaluate the diagnostic yield of DWI in patients attending outpatient clinic for cognitive impairment.Materials and methodsThis retrospective, observational, single-institution study included 3,298 consecutive patients (mean age ± SD, 71 years ± 10; 1,976 women) attending outpatient clinic for cognitive impairment with clinical dementia rating ≥ 0.5 who underwent brain MRI with DWI from January 2010 to February 2020. Diagnostic yield was defined as the proportion of patients in whom DWI supported the diagnosis that underlies cognitive impairment among all patients. Subgroup analyses were performed by age group and sex, and the Chi-square test was performed to compare the diagnostic yields between groups.ResultsThe overall diagnostic yield of DWI in patients with cognitive impairment was 3.2% (106/3,298; 95% CI, 2.6-3.9%). The diagnostic yield was 2.5% (83/3,298) for acute or subacute infarct, which included recent small subcortical infarct for which the diagnostic yield was 1.6% (54/3,298). The diagnostic yield was 0.33% (11/3,298) for Creutzfeldt-Jakob disease (CJD), 0.15% (5/3,298) for transient global amnesia (TGA), 0.12% (4/3,298) for encephalitis and 0.09% (3/3,298) for lymphoma. There was a trend towards a higher diagnostic yield in the older age group with age ≥ 70 years old (3.6% vs 2.6%, P = .12). There was an incremental increase in the diagnostic yield from the age group 60-69 years (2.6%; 20/773) to 90-99 years (8.0%; 2/25).ConclusionDespite its low overall diagnostic yield, DWI supported the diagnosis of acute or subacute infarct, CJD, TGA, encephalitis and lymphoma that underlie cognitive impairment, and there was a trend towards a higher diagnostic yield in the older age group.

Neuroimaging plays a key role in assessing the detection of acute hemorrhage, diagnosis of infarct core, detection of steno-occlusive arteries, mismatch between infarct core and penumbra, and collateral circulation in patients with acute cerebral ischemic stroke. The recent announcement of randomized clinical trials that demonstrated the usefulness of intra-arterial mechanical thrombectomy and the guidelines of 2018 Guidelines for the Early Management of Patients with Acute Ischemic Stroke from American Heart Association/American Stroke Association led to a larger role of neuroimaging and required new neuroimaging strategy for acute cerebral ischemic stroke. In this review, we summarize the recommendation on neuroimaging from the 2018 Guidelines, and review pros and cons between CT and MR and fast scanned stroke MR. Based on the new guidelines and recent research, we discuss the appropriate neuroimaging strategy for acute cerebral ischemic stroke patients.

Purpose Hereditary hemorrhagic telangiectasia (HHT), a rare genetic vascular disorder, has been rarely reported in South Korea. We investigated the current prevalence and presenting patterns of genetically confirmed HHT in South Korea. Materials and Methods We defined HHT patients as those with proven mutations on known HHT-related genes (ENG, ACVRL1, SMAD4, and GDF2) or those fulfilling 3 or 4 of the Curaçao criteria. A computerized systematic search was performed in PubMed and KoreaMed using the following search term: (“hereditary hemorrhagic telangiectasia” AND “Korea”) OR (“Osler-Weber-Rendu” AND “Korea”). We also collected government health insurance data. HHT genetic testing results were collected from three tertiary hospitals in which the genetic tests were performed. We integrated patient data by analyzing each case to obtain the prevalence and presenting pattern of HHT in South Korea. Results We extracted 90 cases from 52 relevant articles from PubMed and KoreaMed. An additional 22 cases were identified from the three Korean tertiary hospitals after excluding seven cases that overlapped with those in the published articles. Finally, 112 HHT patients were identified (41 males and 71 females, aged 4–82 years [mean±standard deviation, 45.3±20.6 years]). The prevalence of HHT in South Korea is about 1 in 500,000, with an almost equal prevalence among men and women. Forty-nine patients underwent genetic testing, of whom 28 had HHT1 (ENG mutation) and 19 had HHT2 (ACVRL1 mutation); the other two patients were negative for ENG, ACVRL1, and SMAD4 mutations. Conclusion The prevalence of HHT is underestimated in Korea. The rate of phenotypic presentation seems to be similar to that found worldwide. Korean health insurance coverage is limited to representative genetic analysis to detect ENG and ACVRL1 mutations. Further genetic analyses to detect HHT3, HHT4, and other forms of HHT should be implemented.

Progressive supranuclear palsy (PSP) and Parkinson’s disease (PD) are difficult to differentiate especially in the early stages. We aimed to investigate the diagnostic performance of the magnetic resonance parkinsonism index (MRPI) in differentiating PSP from PD. A systematic literature search of PubMed-MEDLINE and EMBASE was performed to identify original articles evaluating the diagnostic performance of the MRPI in differentiating PSP from PD published up to 20 February 2021. The pooled sensitivity, specificity, and 95% CI were calculated using the bivariate random-effects model. The area under the curve (AUC) was calculated using a hierarchical summary receiver operating characteristic (HSROC) model. Meta-regression was performed to explain the effects of heterogeneity. A total of 14 original articles involving 484 PSP patients and 1243 PD patients were included. In all studies, T1-weighted images were used to calculate the MRPI. Among the 14 studies, nine studies used 3D T1-weighted images. The pooled sensitivity and specificity for the diagnostic performance of the MRPI in differentiating PSP from PD were 96% (95% CI, 87–99%) and 98% (95% CI, 91–100%), respectively. The area under the HSROC curve was 0.99 (95% CI, 0.98–1.00). Heterogeneity was present (sensitivity: I2 = 97.29%; specificity: I2 = 98.82%). Meta-regression showed the association of the magnet field strength with heterogeneity. Studies using 3 T MRI showed significantly higher sensitivity (100%) and specificity (100%) than those of studies using 1.5 T MRI (sensitivity of 98% and specificity of 97%) (p < 0.01). Thus, the MRPI could accurately differentiate PSP from PD and support the implementation of appropriate management strategies for patients with PSP.

Abstract We compared the efficacy and complications of core-needle biopsy (CNB) with those of fine-needle aspiration (FNA) in a large population of patients with initially detected thyroid nodules via a propensity score analysis. Outpatients with initially detected thyroid nodules, who had undergone CNB or FNA between January 2013 and December 2013, were selected. This study included 4,822 thyroid nodules from 4,553 consecutive patients. Adjustments for significant differences in patients’ baseline characteristics were facilitated via propensity score analysis. Subgroup analyses were performed according to nodule sizes ≥ 1 cm. The non-diagnostic result rate, malignancy rate, complication rate, and diagnostic accuracy were compared. A 1:1 matching of 1,615 patients yielded no significant differences between two groups for any covariate. The non-diagnostic result rate was significantly lower in the core-needle biopsy group than in the fine-needle aspiration group (5.2% vs. 12.1%), while the malignancy rate (23.7% vs. 11.8%) and sensitivity (75.9% vs. 55.6%) were significantly higher. However, the specificities were similar (100% and 99.9%, respectively). Propensity score and subgroup analyses showed similar results. The complication rate was similar between groups in matched cohorts. CNB is a promising and safe diagnostic tool for patients with initially detected thyroid nodules.

BackgroundThe black-blood (BB) technique was developed to suppress the signal from blood and cerebrospinal fluid (CSF) to provide improved depiction of vessel walls.PurposeThe aim was to compare three-dimensional turbo spin echo T1-weighted imaging (3D TSE T1WI) with or without two BB techniques (delay alternating with nutation for tailored excitation [DANTE], and improved motion-sensitized driven equilibrium [iMSDE]) for high-resolution magnetic resonance imaging (HR-MRI) of the vessel walls of intracranial arteries.Study typeProspective.PopulationFourteen healthy volunteers who underwent 3D T1WI for examination of intracranial vessel walls.Field strength/sequence3 Tesla, 3D TSE T1WI (SPACE and BrainVIEW) and BB (DANTE and iMSDE).AssessmentSPACE with or without DANTE, and BrainVIEW with or without iMSDE, were acquired in each subject. Two neuroradiologists independently assessed image quality, vessel wall delineation, BB effect, CSF, and acceptability using visual scoring systems, and measured signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in vessel walls, lumen, and CSF, while blinded to the presence and type of BB technique used.Statistical testsRepeated measures ANOVA or Friedman tests were performed for the comparisons, followed by Bonferroni correction.ResultsThe 3T T1WI sequences without BB are significantly superior in vessel wall delineation (P = 0.001). Black CSF scores were lower in SPACE with DANTE than SPACE without DANTE, and in BrainVIEW without iMSDE than SPACE without DANTE (P < 0.001). However, there were no significant differences in BB effect, image quality, and acceptability between the four 3D T1WI sequences (p > .05). The SNRVessel wall, CNRWall-Lumen, and CNRWall-CSF were higher (all p < .001) on SPACE with and without DANTE than on BrainVIEW with and without iMSDE. SNRLumen were higher (all p < .001) on BrainVIEW with and without iMSDE than on SPACE with and without DANTE. SNRCSF was higher (all p < .001) on BrainVIEW with iMSDE than on SPACE with DANTE.Data conclusionBoth 3D TSE T1WI sequences were acceptable for intracranial vessel wall evaluation, with or without BB techniques. Therefore, BB techniques may not necessarily be required with 3D TSE T1WI with a long ETL and TR (below 1160 ms).

ObjectiveTo investigate the accuracy and precision of ultrasound shear wave elasticity measurements as a function of target elasticity and acquisition depth.Materials and methodsUsing five ultrasound systems (VTQ, VTIQ, EPIQ 5, Aixplorer, and Aplio 500), two operators independently measured shear wave elasticities in two phantoms containing five different target elasticities (8±3, 14±4, 25±6, 45±8, and 80±12 kPa) at depths of 15, 30, 35, and 60 mm. Accuracy was assessed by evaluating measurement errors and the proportions of outliers, while factors affecting accuracy were assessed using logistic regression analysis. Measurement errors were defined as differences between the measured values and 1) the margins of the target elasticity, and 2) the median values of the target elasticity. Outliers were defined as measured values outside the margins of the target elasticity. Precision was assessed by calculating the reproducibility of measurements using the within-subject coefficient of variation (wCV).ResultsMean measurement errors and the proportions of outliers were higher for high than for low target elasticities (p0.05) did not. The wCV for the 80±12 kPa target (31.33%) was significantly higher than that for lower elasticity targets (6.96-10.43 kPa; pConclusionsTargets with high elasticity showed lower accuracy and lower precision than targets with low elasticity, while acquisition depth did not show consistent patterns in either accuracy or precision.

This study aimed to evaluate the radiologic response and adverse event rates of immune checkpoint inhibitor (ICI) therapy with or without radiotherapy for the treatment of non-small cell lung cancer (NSCLC) brain metastases. A systematic literature search was performed up to January 3, 2020. Studies evaluating the intracranial objective response rates (ORR) and/or disease control rates (DCR) of ICI with or without radiotherapy for treating NSCLC brain metastases were included. Consequently, twelve studies satisfied inclusion criteria. ICI combined with radiotherapy (pooled ORR, 95%; DCR, 97%) showed better local efficacy compared to ICI monotherapy (pooled ORR, 24%; DCR, 44%; p < 0.01 for both ORR and DCR). Grade 3 or 4 central nervous system (CNS)-related adverse event rates were not different (5% vs. 4%; p = 0.93). In conclusion, ICI combined with radiotherapy showed better intracranial efficacy than ICI monotherapy for treating NSCLC brain metastases. CNS-related grade 3 or 4 adverse event rate was not statistically different between the two groups. Several prospective trials are needed to compare the efficacy of ICI combined with radiotherapy and ICI monotherapy.

According to the increasing need for accurate staging of hepatic fibrosis, the ultrasound (US) elastography techniques have evolved significantly over the past two decades. Currently, US elastography is increasingly used in clinical practice. Previously published studies have demonstrated the excellent diagnostic performance of US elastography for the detection and staging of liver fibrosis. Although US elastography may seem easy to perform and interpret, there are many technical and clinical factors which can affect the results of US elastography. Therefore, clinicians who are involved with US elastography should be aware of these factors. The purpose of this article is to present a brief overview of US techniques with the relevant technology, the clinical indications, diagnostic performance, and technical and biological factors which should be considered in order to avoid misinterpretation of US elastography results.

Introduction: Although white matter hyperintensity (WMH) shares similar vascular risk and pathology with small vessel occlusion (SVO) stroke, there were few studies to evaluate the impact of the burden of WMH volume on early and delayed stroke outcomes in SVO stroke. Materials and methods: Using a multicenter registry database, we enrolled SVO stroke patients between August 2013 and November 2022. The WMH volume was estimated by automated methods using deep learning (VUNO Med-DeepBrain, Seoul, South Korea), which was a commercially available segmentation model. After propensity score matching (PSM), we evaluated the impact of WMH volume on early neurological deterioration (END) and poor functional outcomes at 3-month modified Ranking Scale (mRS), defined as mRS score >2 at 3 months, after an SVO stroke. Results: Among 1,718 SVO stroke cases, the prevalence of subjects with severe WMH (Fazekas score ≥ 3) was 68.9%. After PSM, END and poor functional outcomes at 3-month mRS (mRS > 2) were higher in the severe WMH group (END: 6.9 vs. 13.5%, p < 0.001; 3-month mRS > 2: 11.4 vs. 24.7%, p < 0.001). The logistic regression analysis using the PSM cohort showed that total WMH volume increased the risk of END [odd ratio [OR], 95% confidence interval [CI]; 1.01, 1.00-1.02, p = 0.048] and 3-month mRS > 2 (OR, 95% CI; 1.02, 1.01-1.03, p < 0.001). Deep WMH was associated with both END and 3-month mRS > 2, but periventricular WMH was associated with 3-month mRS > 2 only. Conclusion: This study used automated methods using a deep learning segmentation model to assess the impact of WMH burden on outcomes in SVO stroke. Our findings emphasize the significance of WMH burden in SVO stroke prognosis, encouraging tailored interventions for better patient care. [ABSTRACT FROM AUTHOR]