Evaluating the capability of ChatGPT in predicting drug-drug interactions: Real-world evidence using hospitalized patient data.

Drug-drug interactions (DDIs) present a significant health burden, compounded by clinician time constraints and poor patient health literacy. We assessed the ability of ChatGPT (generative artificial intelligence-based large language model) to predict DDIs in a real-world setting. Demographics, diagnoses and prescribed medicines for 120 hospitalized patients were input through three standardized prompts to ChatGPT version 3.5 and compared against pharmacist DDI evaluation to estimate diagnostic accuracy. Area under receiver operating characteristic and inter-rater reliability (Cohen's and Fleiss' kappa coefficients) were calculated. ChatGPT's responses differed based on prompt wording style, with higher sensitivity for prompts mentioning 'drug interaction'. Confusion matrices displayed low true positive and high true negative rates, and there was minimal agreement between ChatGPT and pharmacists (Cohen's kappa values 0.077-0.143). Low sensitivity values suggest a lack of success in identifying DDIs by ChatGPT, and further development is required before it can reliably assess potential DDIs in real-world scenarios.

Integrative MR Imaging Interpretation in Cognitive Impairment with Alzheimer's Disease, Small Vessel Disease, and Glymphatic Function-Related MR Parameters.

RATIONALE AND OBJECTIVES: The role of MR imaging in patients with cognitive impairment is to evaluate each component of Alzheimer's disease (AD), small vessel disease (SVD), and glymphatic function. We want to validate the diagnostic performance of the comprehensive interpretation of these parameters to predict the cognitive impairment stage. MATERIALS AND METHODS: This retrospective single-center study included 359 patients with cognitive impairment who had undergone MRI (FLAIR, T2WI, 3D-T1WI, susceptibility-weighted imaging, and diffusion tensor imaging [DTI]) and a neuropsychological screening battery between January 2020 and July 2022. Each AD and SVD-related MR parameter was visually evaluated, and DTI analysis along the perivascular space (ALPS) index was calculated. Volumetry analysis was performed using Neurophet AQUA AI-based software. Using logistic regression analysis, four types of models were developed and compared by adding the components in the following order: (1) clinical factors and AD, (2) SVD, (3) glymphatic function-related MR parameters, and (4) volumetric data. Chi-square automatic interaction detection algorithm was used to develop diagnostic tree analysis (DTA) model to predict late-stage cognitive impairment. RESULTS: APOE4 status, years of education, medial temporal lobe atrophy score, Fazekas scale score, DTI-ALPS index, and white matter hyperintensity were significant predictors of late-stage cognitive impairment. The performance of the prediction model increased from Model 1 to Model 4 (AUC: 0.880, 0.899, 0.914, and 0.945, respectively). The overall accuracy of the DTA model was 87.47%. CONCLUSION: Integrative brain MRI assessments in patients with cognitive impairment, AD, SVD, and glymphatic function-related MR parameters, improve the prediction of late-stage cognitive impairment.

Differentiation of Acute Internal Carotid Artery Occlusion Etiology on Computed Tomography Angiography: Diagnostic Tree for Preparing Endovascular Treatment.

BACKGROUND AND PURPOSE: This study aimed to identify the imaging characteristics and discriminate the etiology of acute internal carotid artery occlusion (ICAO) on computed tomography angiography (CTA) in patients with acute ischemic stroke. MATERIALS AND METHODS: We retrospectively evaluated consecutive patients who underwent endovascular thrombectomy for acute ICAO. Contrast filling of the extracranial ICA in preprocedural CTA was considered apparent ICAO. Non-contrast filling of the extracranial ICA was evaluated according to the contrast-filled lumen configuration, lumen margin and location, Hounsfield units of the non-attenuating segment, and presence of calcification or an intimal flap. Digital subtraction angiography findings were the reference standard for ICAO etiology and the occlusion site. A diagnostic tree was derived using significant variables according to pseudo-occlusion, atherosclerotic vascular disease (ASVD), thrombotic occlusion, and dissection. RESULTS: A total of 114 patients showed apparent ICAO (n = 21), pseudo-occlusion (n = 51), ASVD (n = 27), thrombotic occlusion (n = 9), or dissection (n = 6). Most pseudo-occlusions (50/51, 98.0%) showed dependent locations with ill-defined contrast column margins and classic flame or beak shapes. The most common occlusion site of pseudo-occlusion was the petro-cavernous ICA (n = 32, 62.7%). Apparent ICAO mainly appeared in cases with occlusion distal to the posterior communicating artery orifice. ASVD showed beak or blunt shapes in the presence of low-density plaques or dense calcifications. Dissection revealed flame- or beak-shaped appearances with circumscribed margins. Thrombotic occlusions tended to appear blunt-shaped. The decision-tree model showed a 92.5% overall accuracy. CONCLUSIONS: CTA characteristics may help diagnose ICAO etiology. We provide a simple and easy decision-making model to inform endovascular thrombectomy.

Synthetic temporal bone CT generation from UTE-MRI using a cycleGAN-based deep learning model: advancing beyond CT-MR imaging fusion.

OBJECTIVES: The aim of this study is to develop a deep-learning model to create synthetic temporal bone computed tomography (CT) images from ultrashort echo-time magnetic resonance imaging (MRI) scans, thereby addressing the intrinsic limitations of MRI in localizing anatomic landmarks in temporal bone CT. MATERIALS AND METHODS: This retrospective study included patients who underwent temporal MRI and temporal bone CT within one month between April 2020 and March 2023. These patients were randomly divided into training and validation datasets. A CycleGAN model for generating synthetic temporal bone CT images was developed using temporal bone CT and pointwise encoding-time reduction with radial acquisition (PETRA). To assess the model's performance, the pixel count in mastoid air cells was measured. Two neuroradiologists evaluated the successful generation rates of 11 anatomical landmarks. RESULTS: A total of 102 patients were included in this study (training dataset, n = 54, mean age 58 ± 14, 34 females (63%); validation dataset, n = 48, mean age 61 ± 13, 29 females (60%)). In the pixel count of mastoid air cells, no difference was observed between synthetic and real images (679 ± 342 vs 738 ± 342, p = 0.13). For the six major anatomical sites, the positive generation rates were 97-100%, whereas those of the five major anatomical structures ranged from 24% to 83%. CONCLUSION: We developed a model to generate synthetic temporal bone CT images using PETRA MRI. This model can provide information regarding the major anatomic sites of the temporal bone using MRI. CLINICAL RELEVANCE STATEMENT: The proposed algorithm addresses the primary limitations of MRI in localizing anatomic sites within the temporal bone. KEY POINTS: CT is preferred for imaging the temporal bone, but has limitations in differentiating pathology there. The model achieved a high success rate in generating synthetic images of six anatomic sites. This can overcome the limitations of MRI in visualizing key anatomic sites in the temporal skull.

Deep Learning-Based High-Resolution Magnetic Resonance Angiography (MRA) Generation Model for 4D Time-Resolved Angiography with Interleaved Stochastic Trajectories (TWIST) MRA in Fast Stroke Imaging.

PURPOSE: The purpose of this study is to improve the qualitative and quantitative image quality of the time-resolved angiography with interleaved stochastic trajectories technique (4D-TWIST-MRA) using deep neural network (DNN)-based MR image reconstruction software. MATERIALS AND METHODS: A total of 520 consecutive patients underwent 4D-TWIST-MRA for ischemic stroke or intracranial vessel stenosis evaluation. Four-dimensional DNN-reconstructed MRA (4D-DNR) was generated using commercially available software (SwiftMR v.3.0.0.0, AIRS Medical, Seoul, Republic of Korea). Among those evaluated, 397 (76.3%) patients received concurrent time-of-flight MRA (TOF-MRA) to compare the signal-to-noise ratio (SNR), image quality, noise, sharpness, vascular conspicuity, and degree of venous contamination with a 5-point Likert scale. Two radiologists independently evaluated the detection rate of intracranial aneurysm in TOF-MRA, 4D-TWIST-MRA, and 4D-DNR in separate sessions. The other 123 (23.7%) patients received 4D-TWIST-MRA due to a suspicion of acute ischemic stroke. The confidence level and decision time for large vessel occlusion were evaluated in these patients. RESULTS: In qualitative analysis, 4D-DNR demonstrated better overall image quality, sharpness, vascular conspicuity, and noise reduction compared to 4D-TWIST-MRA. Moreover, 4D-DNR exhibited a higher SNR than 4D-TWIST-MRA. The venous contamination and aneurysm detection rates were not significantly different between the two MRA images. When compared to TOF-MRA, 4D-CE-MRA underestimated the aneurysm size (2.66 ± 0.51 vs. 1.75 ± 0.62, p = 0.029); however, 4D-DNR showed no significant difference in size compared to TOF-MRA (2.66 ± 0.51 vs. 2.10 ± 0.41, p = 0.327). In the diagnosis of large vessel occlusion, 4D-DNR showed a better confidence level and shorter decision time than 4D-TWIST-MRA. CONCLUSION: DNN reconstruction may improve the qualitative and quantitative image quality of 4D-TWIST-MRA, and also enhance diagnostic performance for intracranial aneurysm and large vessel occlusion.

Four-hour-delayed 3D-FLAIR MRIs in patients with acute unilateral peripheral vestibulopathy.

OBJECTIVE: Conventionally, MRI aids in differentiating acute unilateral peripheral vestibulopathy/vestibular neuritis (AUPV/VN) from mimickers. Meanwhile, the diagnostic utility of MRIs dedicated to the inner ear remains to be elucidated for diagnosing AUPV/VN. METHODS: We prospectively recruited 53 patients with AUPV/VN (mean age ± SD = 60 ± 15 years, 29 men). Initial MRIs were performed with a standard protocol, and an additional axial 3D-fluid-attenuated inversion recovery (3D-FLAIR) sequence was obtained 4 h after intravenous injection of gadoterate meglumine. Abnormal enhancement was defined as a signal intensity that exceeded the mean + 2SD value on the healthy side. The findings of neurotologic evaluation and MRIs were compared. RESULTS: Overall, the inter-rater agreement for gadolinium enhancement was 0.886 (Cohen's kappa coefficient). Enhancement was observed in 26 patients (49%), most frequently in the vestibule (n = 20), followed by the anterior (n = 12), horizontal (HC, n = 8), posterior canal (n = 5), and superior (n = 3) and inferior (n = 1) vestibular nerves. In multivariable logistic regression analysis, the enhancement was associated with decreased HC gain in video head-impulse tests (p = 0.036), increased interaural difference in ocular vestibular-evoked myogenic potentials (p = 0.001), and a longer onset-to-MRI time span (p = 0.024). The sensitivity and specificity were 92.3% and 81.5%, respectively, with an area under the curve of 0.90 for predicting gadolinium enhancement. INTERPRETATION: Robust gadolinium enhancement was observed on 4-hour-delayed 3D-FLAIR images in nearly half of the patients with AUPV/VN, with a good correlation with the results of neurotologic evaluation. The positivity may be determined by the extent of vestibular deficit, timing of imaging acquisition, and possibly by the underlying etiology causing AUPV/VN. MRIs may aid in delineating the involved structures in AUPV/VN.

Mapping recurrent mosaic copy number variation in human neurons.

When somatic cells acquire complex karyotypes, they often are removed by the immune system. Mutant somatic cells that evade immune surveillance can lead to cancer. Neurons with complex karyotypes arise during neurotypical brain development, but neurons are almost never the origin of brain cancers. Instead, somatic mutations in neurons can bring about neurodevelopmental disorders, and contribute to the polygenic landscape of neuropsychiatric and neurodegenerative disease. A subset of human neurons harbors idiosyncratic copy number variants (CNVs, "CNV neurons"), but previous analyses of CNV neurons are limited by relatively small sample sizes. Here, we develop an allele-based validation approach, SCOVAL, to corroborate or reject read-depth based CNV calls in single human neurons. We apply this approach to 2,125 frontal cortical neurons from a neurotypical human brain. SCOVAL identifies 226 CNV neurons, which include a subclass of 65 CNV neurons with highly aberrant karyotypes containing whole or substantial losses on multiple chromosomes. Moreover, we find that CNV location appears to be nonrandom. Recurrent regions of neuronal genome rearrangement contain fewer, but longer, genes.

Early therapy evaluation of intra-arterial trastuzumab injection in a human breast cancer xenograft model using multiparametric MR imaging.

PURPOSE: To investigate the treatment efficacy of intra-arterial (IA) trastuzumab treatment using multiparametric magnetic resonance imaging (MRI) in a human breast cancer xenograft model. MATERIALS AND METHODS: Human breast cancer cells (BT474) were stereotaxically injected into the brains of nude mice to obtain a xenograft model. The mice were divided into four groups and subjected to different treatments (IA treatment [IA-T], intravenous treatment [IV-T], IA saline injection [IA-S], and the sham control group). MRI was performed before and at 7 and 14 d after treatment to assess the efficacy of the treatment. The tumor volume, apparent diffusion coefficient (ADC), and dynamic contrast-enhanced (DCE) MRI parameters (Ktrans, Kep, Ve, and Vp) were measured. RESULTS: Tumor volumes in the IA-T group at 14 d after treatment were significantly lower than those in the IV-T group (13.1 mm3 [interquartile range 8.48-16.05] vs. 25.69 mm3 [IQR 20.39-30.29], p = 0.005), control group (IA-S, 33.83 mm3 [IQR 32.00-36.30], p<0.01), and sham control (39.71 mm3 [IQR 26.60-48.26], p <0.001). The ADC value in the IA-T group was higher than that in the control groups (IA-T, 7.62 [IQR 7.23-8.20] vs. IA-S, 6.77 [IQR 6.48-6.87], p = 0.044 and vs. sham control, 6.89 [IQR 4.93-7.48], p = 0.004). Ktrans was significantly decreased following the treatment compared to that in the control groups (p = 0.002 and p<0.001 for vs. IA-S and sham control, respectively). Tumor growth was decreased in the IV-T group compared to that in the sham control group (25.69 mm3 [IQR 20.39-30.29] vs. 39.71 mm3 [IQR 26.60-48.26], p = 0.27); there was no significant change in the MRI parameters. CONCLUSION: IA treatment with trastuzumab potentially affects the early response to treatment, including decreased tumor growth and decrease of Ktrans, in a preclinical brain tumor model.

Differentiation of salivary gland tumours using diffusion-weighted image-based virtual MR elastography: a pilot study.

OBJECTIVES: Differentiation among benign salivary gland tumours, Warthin tumours (WTs), and malignant salivary gland tumours is crucial to treatment planning and predicting patient prognosis. However, differentiation of those tumours using imaging findings remains difficult. This study evaluated the usefulness of elasticity determined from diffusion-weighted image (DWI)-based virtual MR elastography (MRE) compared with conventional magnetic resonance imaging (MRI) findings in differentiating the tumours. METHODS: This study included 17 benign salivary gland tumours, 6 WTs, and 11 malignant salivary gland tumours scanned on neck MRI. The long and short diameters, T1 and T2 signal intensities, tumour margins, apparent diffusion coefficient (ADC) values, and elasticity from DWI-based virtual MRE of the tumours were evaluated. The interobserver agreement in measuring tumour elasticity and the receiver operating characteristic (ROC) curves were also assessed. RESULTS: The long and short diameters and the T1 and T2 signal intensities showed no significant difference among the 3 tumour groups. Tumour margins and the mean ADC values showed significant differences among some tumour groups. The elasticity from virtual MRE showed significant differences among all 3 tumour groups and the interobserver agreement was excellent. The area under the ROC curves of the elasticity were higher than those of tumour margins and mean ADC values. CONCLUSION: Elasticity values based on DWI-based virtual MRE of benign salivary gland tumours, WTs, and malignant salivary gland tumours were significantly different. The elasticity of WTs was the highest and that of benign tumours was the lowest. The elasticity from DWI-based virtual MRE may aid in the differential diagnosis of salivary gland tumours.

Bright diffusion sign: A sensitive and specific radiologic biomarker for multinodular and vacuolating neuronal tumor.

BACKGROUND AND PURPOSE: Accurate differentiation between multinodular and vacuolating neuronal tumor (MVNT) and dysembryoplastic neuroepithelial tumor (DNET) is important for treatment decision-making. We aimed to develop an accurate radiologic diagnostic model for differentiating MVNT from DNET using T2WI and diffusion-weighted imaging (DWI). MATERIALS AND METHODS: A total of 56 patients (mean age, 47.48±17.78 years; 31 women) diagnosed with MVNT (n = 37) or DNET (n = 19) who underwent brain MRI, including T2WI and DWI, were included. Two board-certified neuroradiologists performed qualitative (bubble appearance, cortical involvement, bright diffusion sign, and bright apparent diffusion coefficient [ADC] sign) and quantitative (nDWI and nADC) assessments. A diagnostic tree model was developed with significant and reliable imaging findings using an exhaustive chi-squared Automatic Interaction Detector (CHAID) algorithm. RESULTS: In visual assessment, the imaging features that showed high diagnostic accuracy and interobserver reliability were the bright diffusion sign and absence of cortical involvement (bright diffusion sign: accuracy, 94.64 %; sensitivity, 91.89 %; specificity, 100.00 %; interobserver agreement, 1.00; absence of cortical involvement: accuracy, 92.86 %; sensitivity, 89.19 %; specificity, 100.00 %; interobserver agreement, 1.00). In quantitative analysis, nDWI was significantly higher in MVNT than in DENT (1.52 ± 0.34 vs. 0.91 ± 0.27, p < 0.001), but the interobserver agreement was fair (intraclass correlation coefficient = 0.321). The overall diagnostic accuracy of the tree model with visual assessment parameters was 98.21 % (55/56). CONCLUSION: The bright diffusion sign and absence of cortical involvement are accurate and reliable imaging findings for differentiating MVNT from DNET. By using simple, intuitive, and reliable imaging findings, such as the bright diffusion sign, MVNT can be accurately differentiated from DNET.

Low- or standard-dose edoxaban versus antiplatelet therapy for leaflet thrombus and cerebral thromboembolism after TAVR: A prespecified analysis of randomized ADAPT-TAVR trial.

BACKGROUND: The risks of leaflet thrombosis and the associated cerebral thromboembolism are unknown according to different anticoagulation dosing after transcatheter aortic valve replacement (TAVR). The aim was to evaluate the incidence of leaflet thrombosis and cerebral thromboembolism between low-dose (30 mg) or standard-dose (60 mg) edoxaban and dual antiplatelet therapy (DAPT) after TAVR. METHODS: In this prespecified subgroup analysis of the ADAPT-TAVR trial, the primary endpoint was the incidence of leaflet thrombosis on 4-dimensional computed tomography at 6-months. Key secondary endpoints were new cerebral lesions on brain magnetic resonance imaging and neurological and neurocognitive dysfunction. RESULTS: Of 229 patients enrolled in this study, 118 patients were DAPT group and 111 were edoxaban group (43 [39.1%] 60 mg vs 68 [61.3%] 30 mg). There was a significantly lower incidence of leaflet thrombosis in the standard-dose edoxaban group than in the DAPT group (2.4% vs 18.3%; odds ratio [OR] 0.11; 95% confidence interval [CI], 0.01-0.55; P = .03). However, no significant difference was observed between low-dose edoxaban and DAPT (15.0% vs 18.3%; OR 0.79; 95% CI, 0.32-1.81; P = .58). Irrespective of different antithrombotic regiments, the percentages of patients with new cerebral lesions on brain MRI and worsening neurological or neurocognitive function were not significantly different. CONCLUSIONS: In patients without an indication for anticoagulation after TAVR, the incidence of leaflet thrombosis was significantly lower with standard-dose edoxaban but not with low-dose edoxaban, as compared with DAPT. However, this differential effect of edoxaban on leaflet thrombosis was not associated with a reduction of new cerebral thromboembolism and neurological dysfunction.

The effect of inflammation markers on cortical thinning in major depressive disorder: A possible mediator of depression and cortical changes.

BACKGROUND: Major depressive disorder (MDD) is a prevalent mental health condition with significant societal impact. Owing to the intricate biological diversity of MDD, treatment efficacy remains limited. Immune biomarkers have emerged as potential predictors of treatment response, underscoring the interaction between the immune system and the brain. This study investigated the relationship between cytokine levels and cortical thickness in patients with MDD, focusing on the corticolimbic circuit, to elucidate the influence of neuroinflammation on structural brain changes and contribute to a deeper understanding of the pathophysiology of MDD. METHOD: A total of 114 patients with MDD and 101 healthy controls (HC) matched for age, sex, and body mass index (BMI) were recruited. All participants were assessed for depression severity using the Hamilton Depression Rating Scale (HDRS), and 3.0 T T1 weighted brain MRI data were acquired. Additionally, cytokine levels were measured using a highly sensitive bead-based multiplex immunosorbent assay. RESULTS: Patients diagnosed with MDD exhibited notably elevated levels of interleukin-6 (p = 0.005) and interleukin-8 (p = 0.005), alongside significant cortical thinning in the left anterior cingulate gyrus and left superior frontal gyrus, with these findings maintaining significance even after applying Bonferroni correction. Furthermore, increased interleukin-6 and interleukin-8 levels in patients with MDD are associated with alterations in the left frontomarginal gyrus and right anterior cingulate cortex (ACC). CONCLUSIONS: This suggests a potential influence of neuroinflammation on right ACC function in MDD patients, warranting longitudinal research to explore interleukin-6 and interleukin-8 mediated neurotoxicity in MDD vulnerability and brain morphology changes.

Deep Learning-Based Synthetic TOF-MRA Generation Using Time-Resolved MRA in Fast Stroke Imaging.

BACKGROUND AND PURPOSE: Time-resolved MRA enables collateral evaluation in acute ischemic stroke with large-vessel occlusion; however, a low SNR and spatial resolution impede the diagnosis of vascular occlusion. We developed a CycleGAN-based deep learning model to generate high-resolution synthetic TOF-MRA images using time-resolved MRA and evaluated its image quality and clinical efficacy. MATERIALS AND METHODS: This retrospective, single-center study included 397 patients who underwent both TOF- and time-resolved MRA between April 2021 and January 2022. Patients were divided into 2 groups for model development and image-quality validation. Image quality was evaluated qualitatively and quantitatively with 3 sequences. A multireader diagnostic optimality evaluation was performed by 16 radiologists. For clinical validation, we evaluated 123 patients who underwent fast stroke MR imaging to assess acute ischemic stroke. The diagnostic confidence level and decision time for large-vessel occlusion were also evaluated. RESULTS: Median values of overall image quality, noise, sharpness, venous contamination, and SNR for M1, M2, the basilar artery, and posterior cerebral artery are better with synthetic TOF than with time-resolved MRA. However, with respect to real TOF, synthetic TOF presents worse median values of overall image quality, sharpness, vascular conspicuity, and SNR for M3, the basilar artery, and the posterior cerebral artery. During the multireader evaluation, radiologists could not discriminate synthetic TOF images from TOF images. During clinical validation, both readers demonstrated increases in diagnostic confidence levels and decreases in decision time. CONCLUSIONS: A CycleGAN-based deep learning model was developed to generate synthetic TOF from time-resolved MRA. Synthetic TOF can potentially assist in the detection of large-vessel occlusion in stroke centers using time-resolved MRA.

Frequency, Predictors, and Clinical Impact of Valvular and Perivalvular Thrombus After Transcatheter Aortic Valve Replacement.

BACKGROUND: Subclinical aortic valve complex (valvular and perivalvular) thrombus is not rare after transcatheter aortic valve replacement (TAVR). The risk factors and clinical implications of these findings remain uncertain. OBJECTIVES: This study sought to evaluate the frequency, predictors, and clinical outcome of aortic valve complex thrombus after TAVR. METHODS: In the ADAPT-TAVR (Anticoagulation Versus Dual Antiplatelet Therapy for Prevention of Leaflet Thrombosis and Cerebral Embolization After Transcatheter Aortic Valve Replacement) trial comparing edoxaban vs dual antiplatelet therapy in TAVR patients without an indication for chronic anticoagulation, the frequency of valvular (subclinical leaflet thrombus) and perivalvular (supravalvular, subvalvular, and sinus of Valsalva) thrombus was evaluated by 4-dimensional computed tomography at 6 months. The association of these phenomena with new cerebral thromboembolism on brain magnetic resonance imaging, neurologic and neurocognitive dysfunction, and clinical outcomes was assessed. RESULTS: Among 211 patients with 6-month computed tomography evaluations, 91 patients (43.1%) had thrombus at any aortic valve complex, 30 (14.2%) patients had leaflet thrombus, and 78 (37.0%) patients had perivalvular thrombus. A small maximum diameter of the stent at the valve level and low body surface area were independent predictors of aortic valve complex and perivalvular thrombus, and decreased renal function was an independent predictor of leaflet thrombus. No significant differences were observed in new cerebral lesions, neurologic or neurocognitive functions, or clinical outcomes among patients with or without valvular or perivalvular thrombus. CONCLUSIONS: Subclinical aortic valve complex (valvular and perivalvular) thrombus was common in patients who had undergone successful TAVR. However, these imaging phenomena were not associated with new cerebral thromboembolism, neurologic or neurocognitive dysfunction, or adverse clinical outcomes. (Anticoagulation Versus Dual Antiplatelet Therapy for Prevention of Leaflet Thrombosis and Cerebral Embolization After Transcatheter Aortic Valve Replacement [ADAPT-TAVR]; NCT03284827).

Proposed Protocols for Artificial Intelligence Imaging Database in Acute Stroke Imaging.

PURPOSE: To propose standardized and feasible imaging protocols for constructing artificial intelligence (AI) database in acute stroke by assessing the current practice at tertiary hospitals in South Korea and reviewing evolving AI models. MATERIALS AND METHODS: A nationwide survey on acute stroke imaging protocols was conducted using an electronic questionnaire sent to 43 registered tertiary hospitals between April and May 2021. Imaging protocols for endovascular thrombectomy (EVT) in the early and late time windows and during follow-up were assessed. Clinical applications of AI techniques in stroke imaging and required sequences for developing AI models were reviewed. Standardized and feasible imaging protocols for data curation in acute stroke were proposed. RESULTS: There was considerable heterogeneity in the imaging protocols for EVT candidates in the early and late time windows and posterior circulation stroke. Computed tomography (CT)-based protocols were adopted by 70% (30/43), and acquisition of noncontrast CT, CT angiography and CT perfusion in a single session was most commonly performed (47%, 14/30) with the preference of multiphase (70%, 21/30) over single phase CT angiography. More hospitals performed magnetic resonance imaging (MRI)-based protocols or additional MRI sequences in a late time window and posterior circulation stroke. Diffusion-weighted imaging (DWI) and fluid-attenuated inversion recovery (FLAIR) were most commonly performed MRI sequences with considerable variation in performing other MRI sequences. AI models for diagnostic purposes required noncontrast CT, CT angiography and DWI while FLAIR, dynamic susceptibility contrast perfusion, and T1-weighted imaging (T1WI) were additionally required for prognostic AI models. CONCLUSION: Given considerable heterogeneity in acute stroke imaging protocols at tertiary hospitals in South Korea, standardized and feasible imaging protocols are required for constructing AI database in acute stroke. The essential sequences may be noncontrast CT, DWI, CT/MR angiography and CT/MR perfusion while FLAIR and T1WI may be additionally required.

Ultrasound assessment of medial crural cutaneous nerve and infrapatellar branch and of the saphenous nerve: establishing a safety zone for preventing nerve injury in knee surgery and injections.

PURPOSE: Our study aimed to illustrate the positional relationship of the two branches of the saphenous nerve: the infrapatellar branch of the saphenous nerve (IPBSN) and medial crural cutaneous nerve (MCCN), as well as the anatomical landmarks using high-resolution ultrasound (HRUS) to help prevent iatrogenic nerve injury. METHODS: We used HRUS to explore the positional relationships among the anatomical landmarks, IPBSN, and MCCN in 40 knees of 20 participants. The distances from these branches to key reference points were recorded. Using the ultrasound caliper mode, we measured the depth from the skin surface to the nerves at four distinct points. RESULTS: The average distances between IPBSN and medial border of patella (MBP) and IPBSN and medial border of patellar ligament (MBPL) were 47 ± 7 mm and 42 ± 9 mm, respectively. MCCN showed mean distances of 94 ± 9 mm and 96 ± 9 mm to MBP and MBPL, respectively. The mean distance from the upper edge of pes anserine to IPBSN at the patellar apex (PA) level was 24 ± 10 mm and to MCCN was 34 ± 9 mm. CONCLUSION: We used high-resolution ultrasound to evaluate IPBSN and MCCN and their positions relative to anatomical landmarks. The study results offer valuable insights into the course of these nerves, which can help establish a safety zone to prevent accidental nerve injuries during knee surgeries and injections.

Clinical Features and Neurotologic Findings in Patients With Acute Unilateral Peripheral Vestibulopathy Associated With Antiganglioside Antibody.

BACKGROUND AND OBJECTIVES: Anecdotal studies have reported the presence of antiganglioside antibodies in acute unilateral peripheral vestibulopathy (AUPV). This study aimed to determine the prevalence, clinical characteristics, and neurotologic findings of AUPV associated with antiganglioside antibodies. METHODS: Serum antigangliosides were measured in consecutive patients with AUPV according to the Bárány Society criteria during the acute and recovery phases in a referral-based university hospital in South Korea from September 2019 to January 2023. Clinical characteristics and neurotologic findings were compared between those with and without antiganglioside antibodies. The results of video-oculography, video head impulse and bithermal caloric tests, and other neurotologic evaluations including ocular and cervical vestibular-evoked myogenic potentials and subjective visual vertical were compared between the 2. MRIs dedicated to the inner ear were also conducted when considered necessary. RESULTS: One hundred five patients (mean age ± SD = 60 ± 13 years, 57 male) were included for analyses. During the acute phase, 12 patients (12/105, 11%) were tested positive for serum antiganglioside antibodies, including anti-GQ1b immunoglobulin (Ig) G (n = 5) or IgM (n = 4), anti-GM1 IgM (n = 3), and anti-GD1a IgG (n = 1, including 1 patient with a positive anti-GQ1b antibody). Patients with antiganglioside antibodies showed lesser intensity of spontaneous nystagmus (median [interquartile range] = 1.8 [1.2-2.1] vs 3.4 [1.5-9.5], p = 0.003) and a lesser degree of canal paresis (30 [17-47] vs 58 [34-79], p = 0.028) and gain asymmetry of the vestibulo-ocular reflex for the horizontal semicircular canal during head impulse tests (0.07 [-0.04 to 0.61] vs 0.36 [0.18-0.47], p = 0.032) than those without antibodies. Negative conversion of antibodies and vestibular recovery were observed in most patients (6/8, 75%). Among 30 patients with AUPV with 4-hour delayed 3D fluid-attenuated inversion recovery dedicated to the inner ear, gadolinium enhancement was observed in 18 (18/30, 60%), either in the vestibule (n = 9), semicircular canal (n = 6), or vestibular nerve (n = 5). The positivity rates based on specific antibodies could not be determined due to limited sample sizes. DISCUSSION: The association between antiganglioside antibodies and AUPV suggests an immune-mediated mechanism in acute vestibular failure and extends the clinical spectrum of antiganglioside antibody syndrome.

Joint semiparametric kernel network regression.

Variable selection and graphical modeling play essential roles in highly correlated and high-dimensional (HCHD) data analysis. Variable selection methods have been developed under both parametric and nonparametric model settings. However, variable selection for nonadditive, nonparametric regression with high-dimensional variables is challenging due to complications in modeling unknown dependence structures among HCHD variables. Gaussian graphical models are a popular and useful tool for investigating the conditional dependence between variables via estimating sparse precision matrices. For a given class of interest, the estimated precision matrices can be mapped onto networks for visualization. However, the limitation of Gaussian graphical models is that they are only applicable to discretized response variables and for the case when p log ( p ) ≪ n $$ p\log (p)\ll n $$ , where p $$ p $$ is the number of variables and n $$ n $$ is the sample size. They are necessary to develop a joint method for variable selection and graphical modeling. To the best of our knowledge, the methods for simultaneously selecting variable selection and estimating networks among variables in the semiparametric regression settings are quite limited. Hence, in this paper, we develop a joint semiparametric kernel network regression method to solve this limitation and to provide a connection between them. Our approach is a unified and integrated method that can simultaneously identify important variables and build a network among those variables. We developed our approach under a semiparametric kernel machine regression framework, which can allow for nonlinear or nonadditive associations and complicated interactions among the variables. The advantages of our approach are that it can (1) simultaneously select variables and build a network among HCHD variables under a regression setting; (2) model unknown and complicated interactions among the variables and estimate the network among these variables; (3) allow for any form of semiparametric model, including non-additive, nonparametric model; and (4) provide an interpretable network that considers important variables and a response variable. We demonstrate our approach using a simulation study and real application on genetic pathway-based analysis.

The Korean Speech Recognition Sentences: A Large Corpus for Evaluating Semantic Context and Language Experience in Speech Perception.

PURPOSE: The aim of this study was to develop and validate a large Korean sentence set with varying degrees of semantic predictability that can be used for testing speech recognition and lexical processing. METHOD: Sentences differing in the degree of final-word predictability (predictable, neutral, and anomalous) were created with words selected to be suitable for both native and nonnative speakers of Korean. Semantic predictability was evaluated through a series of cloze tests in which native (n = 56) and nonnative (n = 19) speakers of Korean participated. This study also used a computer language model to evaluate final-word predictabilities; this is a novel approach that the current study adopted to reduce human effort in validating a large number of sentences, which produced results comparable to those of the cloze tests. In a speech recognition task, the sentences were presented to native (n = 23) and nonnative (n = 21) speakers of Korean in speech-shaped noise at two levels of noise. RESULTS: The results of the speech-in-noise experiment demonstrated that the intelligibility of the sentences was similar to that of related English corpora. That is, intelligibility was significantly different depending on the semantic condition, and the sentences had the right degree of difficulty for assessing intelligibility differences depending on noise levels and language experience. CONCLUSIONS: This corpus (1,021 sentences in total) adds to the target languages available in speech research and will allow researchers to investigate a range of issues in speech perception in Korean. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.24045582.

Impact of leaflet thrombosis on valve haemodynamic status after transcatheter aortic valve replacement.

OBJECTIVES: The effect of subclinical leaflet thrombosis, characterised by hypoattenuated leaflet thickening (HALT), on the valve haemodynamic function and durability of the bioprosthetic valve, is not yet determined. We determined the impact of HALT on valve haemodynamics after transcatheter aortic valve replacement (TAVR) and the predictors of haemodynamic structural valve deterioration (SVD). METHODS: The Anticoagulation vs Dual Antiplatelet Therapy for Prevention of Leaflet Thrombosis and Cerebral Embolization after Transcatheter Aortic Valve Replacement(ADAPT-TAVR) trial is a multicenter, randomised trial that compared edoxaban and dual antiplatelet therapy in patients who had undergone successful TAVR. The presence of HALT was evaluated by four-dimensional CT at 6 months and serial echocardiography performed at baseline, immediately post-TAVR and after 6 months. SVD was defined as at least one of the following: (1) mean transprosthetic gradient ≥20 mm Hg, (2) change in the mean gradient ≥10 mm Hg from baseline, or (3) new or increase in intraprosthetic aortic regurgitation of at least ≥1 grade, resulting in moderate or greater regurgitation. RESULTS: At 6 months, HALT was found in 30 of 211 (14.2%) patients. The presence of HALT did not significantly affect aortic valve mean gradients (with vs without HALT; 14.0±4.8 mm Hg vs 13.7±5.5 mm Hg; p=0.74) at 6 months. SVD was reported in 30 of 206 patients (14.6%) at 6-month follow-up echocardiography. Older age (OR: 1.138; 95% CI: 1.019 to 1.293; p=0.033), use of aortic valve size ≤23 mm (OR: 6.254; 95% CI: 2.230 to 20.569; p=0.001) and mean post-TAVR pressure gradient (OR: 1.233; 95% CI: 1.123 to 1.371; p<0.001) were independent predictors of haemodynamic SVD; however, the presence of HALT was not identified as a predictor of SVD. CONCLUSIONS: In patients who had undergone successful TAVR, aortic valve haemodynamic status was not influenced by the presence of HALT. Although HALT was not a predictor of haemodynamic SVD at 6 months, it warrants further longer-term follow-up to evaluate the effect on long-term valve durability. TRIAL REGISTRATION NUMBER: NCT03284827 (https://www. CLINICALTRIALS: gov).