Magnetic resonance radiomics-derived sphericity correlates with seizure in brain arteriovenous malformations.

OBJECTIVES: Angioarchitectural analysis of brain arteriovenous malformations (BAVMs) is qualitative and subject to interpretation. This study quantified the morphology of and signal changes in the nidal and perinidal areas by using MR radiomics and compared the performance of MR radiomics and angioarchitectural analysis in detecting epileptic BAVMs. MATERIALS AND METHODS: From 2010 to 2020, a total of 111 patients with supratentorial BAVMs were retrospectively included and grouped in accordance with the initial presentation of seizure. Patients' angiograms and MR imaging results were analyzed to determine the corresponding angioarchitecture. The BAVM nidus was contoured on time-of-flight MR angiography images. The perinidal brain parenchyma was contoured on T2-weighted images, followed by radiomic analysis. Logistic regression analysis was performed to determine the independent risk factors for seizure. ROC curve analysis, decision curve analysis (DCA), and calibration curve were performed to compare the performance of angioarchitecture-based and radiomics-based models in diagnosing epileptic BAVMs. RESULTS: In multivariate analyses, low sphericity (OR: 2012.07, p = .04) and angiogenesis (OR: 5.30, p = .01) were independently associated with a high risk of seizure after adjustment for age, sex, temporal location, and nidal volume. The AUC for the angioarchitecture-based, MR radiomics-based, and combined models was 0.672, 0.817, and 0.794, respectively. DCA confirmed the clinical utility of the MR radiomics-based and combined models. CONCLUSIONS: Low nidal sphericity and angiogenesis were associated with high seizure risk in patients with BAVMs. MR radiomics-derived tools may be used for noninvasive and objective measurement for evaluating the risk of seizure due to BAVM. CLINICAL RELEVANCE STATEMENT: Low nidal sphericity was associated with high seizure risk in patients with brain arteriovenous malformation and MR radiomics may be used as a noninvasive and objective measurement method for evaluating seizure risk in patients with brain arteriovenous malformation. KEY POINTS: • Low nidal sphericity was associated with high seizure risk in patients with brain arteriovenous malformation. • The performance of MR radiomics in detecting epileptic brain arteriovenous malformations was more satisfactory than that of angioarchitectural analysis. • MR radiomics may be used as a noninvasive and objective measurement method for evaluating seizure risk in patients with brain arteriovenous malformation.

Feasibility of Auto-Quantified Epicardial Adipose Tissue in Predicting Atrial Fibrillation Recurrence After Catheter Ablation.

BACKGROUND: The aim of this study was to build an auto-segmented artificial intelligence model of the atria and epicardial adipose tissue (EAT) on computed tomography (CT) images, and examine the prognostic significance of auto-quantified left atrium (LA) and EAT volumes for AF. METHODS AND RESULTS: This retrospective study included 334 patients with AF who were referred for catheter ablation (CA) between 2015 and 2017. Atria and EAT volumes were auto-quantified using a pre-trained 3-dimensional (3D) U-Net model from pre-ablation CT images. After adjusting for factors associated with AF, Cox regression analysis was used to examine predictors of AF recurrence. The mean (±SD) age of patients was 56±11 years; 251 (75%) were men, and 79 (24%) had non-paroxysmal AF. Over 2 years of follow-up, 139 (42%) patients experienced recurrence. Diabetes, non-paroxysmal AF, non-pulmonary vein triggers, mitral line ablation, and larger LA, right atrium, and EAT volume indices were linked to increased hazards of AF recurrence. After multivariate adjustment, non-paroxysmal AF (hazard ratio [HR] 0.6; 95% confidence interval [CI] 0.4-0.8; P=0.003) and larger LA-EAT volume index (HR 1.1; 95% CI 1.0-1.2; P=0.009) remained independent predictors of AF recurrence. CONCLUSIONS: LA-EAT volume measured using the auto-quantified 3D U-Net model is feasible for predicting AF recurrence after CA, regardless of AF type.

Federated Learning: A Cross-Institutional Feasibility Study of Deep Learning Based Intracranial Tumor Delineation Framework for Stereotactic Radiosurgery.

BACKGROUND: Deep learning-based segmentation algorithms usually required large or multi-institute data sets to improve the performance and ability of generalization. However, protecting patient privacy is a key concern in the multi-institutional studies when conventional centralized learning (CL) is used. PURPOSE: To explores the feasibility of a proposed lesion delineation for stereotactic radiosurgery (SRS) scheme for federated learning (FL), which can solve decentralization and privacy protection concerns. STUDY TYPE: Retrospective. SUBJECTS: 506 and 118 vestibular schwannoma patients aged 15-88 and 22-85 from two institutes, respectively; 1069 and 256 meningioma patients aged 12-91 and 23-85, respectively; 574 and 705 brain metastasis patients aged 26-92 and 28-89, respectively. FIELD STRENGTH/SEQUENCE: 1.5T, spin-echo, and gradient-echo [Correction added after first online publication on 21 August 2023. Field Strength has been changed to "1.5T" from "5T" in this sentence.]. ASSESSMENT: The proposed lesion delineation method was integrated into an FL framework, and CL models were established as the baseline. The effect of image standardization strategies was also explored. The dice coefficient was used to evaluate the segmentation between the predicted delineation and the ground truth, which was manual delineated by neurosurgeons and a neuroradiologist. STATISTICAL TESTS: The paired t-test was applied to compare the mean for the evaluated dice scores (p < 0.05). RESULTS: FL performed the comparable mean dice coefficient to CL for the testing set of Taipei Veterans General Hospital regardless of standardization and parameter; for the Taichung Veterans General Hospital data, CL significantly (p < 0.05) outperformed FL while using bi-parameter, but comparable results while using single-parameter. For the non-SRS data, FL achieved the comparable applicability to CL with mean dice 0.78 versus 0.78 (without standardization), and outperformed to the baseline models of two institutes. DATA CONCLUSION: The proposed lesion delineation successfully implemented into an FL framework. The FL models were applicable on SRS data of each participating institute, and the FL exhibited comparable mean dice coefficient to CL on non-SRS dataset. Standardization strategies would be recommended when FL is used. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 1.

Application of artificial intelligence to stereotactic radiosurgery for intracranial lesions: detection, segmentation, and outcome prediction.

BACKGROUND: Rapid evolution of artificial intelligence (AI) prompted its wide application in healthcare systems. Stereotactic radiosurgery served as a good candidate for AI model development and achieved encouraging result in recent years. This article aimed at demonstrating current AI application in radiosurgery. METHODS: Literatures published in PubMed during 2010-2022, discussing AI application in stereotactic radiosurgery were reviewed. RESULTS: AI algorithms, especially machine learning/deep learning models, have been administered to different aspect of stereotactic radiosurgery. Spontaneous tumor detection and automated lesion delineation or segmentation were two of the promising application, which could be further extended to longitudinal treatment follow-up. Outcome prediction utilized machine learning algorithms with radiomic-based analysis was another well-established application. CONCLUSIONS: Stereotactic radiosurgery has taken a lead role in AI development. Current achievement, limitation, and further investigation was summarized in this article.

Right arcuate fasciculus as outcome predictor after low-frequency repetitive transcranial magnetic stimulation in nonfluent aphasic stroke.

BACKGROUND AND PURPOSE: A reliable neuroimaging biomarker to predict language improvement after neuromodulation in post-stroke aphasia is lacking. It is hypothesized that aphasic patients with stroke injuries in the left primary language circuits but with sufficient right arcuate fasciculus (AF) integrity might respond to low-frequency repetitive transcranial magnetic stimulation (LF-rTMS), leading to language improvement. This study aimed to assess the microstructural indices of the right AF before LF-rTMS treatment and further correlate with language improvement after the treatment. METHODS: Thirty-three patients with at least 3 months after stroke in the left hemisphere and nonfluent aphasia were recruited in this randomized double-blind study. All patients received real 1-Hz LF-rTMS (n = 16) or sham stimulation (n = 17) at the right pars triangularis for 10 consecutive weekdays. Fractional anisotropy, axial diffusivity, radial diffusivity and apparent diffusion coefficient of the right AF were extracted using diffusion tensor imaging before the rTMS treatment and correlated with the measured functional improvement by the Concise Chinese Aphasia Test. RESULTS: The Concise Chinese Aphasia Test change scores revealed a stronger language improvement in auditory/reading comprehension and expression in the rTMS group than in the sham group. Regression analysis showed that the pre-treatment fractional anisotropy, axial diffusivity and apparent diffusion coefficient of the right AF significantly correlated with the expression abilities (R2 > 0.700, p < 0.044) and comprehension abilities (R2 > 0.702, p < 0.039) in the rTMS group. CONCLUSIONS: It was concluded that the right AF could be a predictor in language recovery induced by LF-rTMS after the injuries of primary language circuits.

Effects of bihemispheric transcranial direct current stimulation on motor recovery in subacute stroke patients: a double-blind, randomized sham-controlled trial.

BACKGROUND: Bihemispheric transcranial direct current stimulation (tDCS) of the primary motor cortex (M1) can simultaneously modulate bilateral corticospinal excitability and interhemispheric interaction. However, how tDCS affects subacute stroke recovery remains unclear. We investigated the effects of bihemispheric tDCS on motor recovery in subacute stroke patients. METHODS: We enrolled subacute inpatients who had first-ever ischemic stroke at subcortical regions and moderate-to-severe baseline Fugl-Meyer Assessment of Upper Extremity (FMA-UE) score 2-56. Participants between 14 and 28 days after stroke were double-blind, randomly assigned (1:1) to receive real (n = 13) or sham (n = 14) bihemispheric tDCS (with ipsilesional M1 anode and contralesional M1 cathode, 20 min, 2 mA) during task practice twice daily for 20 sessions in two weeks. Residual integrity of the ipsilesional corticospinal tract was stratified between groups. The primary efficacy outcome was the change in FMA-UE score from baseline (responder as an increase ≥ 10). The secondary measures included changes in the Action Research Arm Test (ARAT), FMA-Lower Extremity (FMA-LE) and explorative resting-state MRI functional connectivity (FC) of target regions after intervention and three months post-stroke. RESULTS: Twenty-seven participants completed the study without significant adverse effects. Nineteen patients (70%) had no recordable baseline motor-evoked potentials (MEP-negative) from the paretic forearm. Compared with the sham group, the real tDCS group showed enhanced improvement of FMA-UE after intervention (p < 0.01, effect size η2 = 0.211; responder rate: 77% vs. 36%, p = 0.031), which sustained three months post-stroke (p < 0.01), but not ARAT. Interestingly, in the MEP-negative subgroup analysis, the FMA-UE improvement remained but delayed. Additionally, the FMA-LE improvement after real tDCS was not significantly greater until three months post-stroke (p < 0.01). We found that the individual FMA-UE improvements after real tDCS were associated with bilateral intrahemispheric, rather than interhemispheric, FC strengths in the targeted cortices, while the improvements after sham tDCS were associated with predominantly ipsilesional FC changes after adjustment for age and sex (p < 0.01). CONCLUSIONS: Bihemispheric tDCS during task-oriented training may facilitate motor recovery in subacute stroke patients, even with compromised corticospinal tract integrity. Further studies are warranted for tDCS efficacy and network-specific neuromodulation. TRIAL REGISTRATION: This study is registered with ClinicalTrials.gov: (ID: NCT02731508).

Frontal asymmetry as a core feature of major depression: a functional near-infrared spectroscopy study.

BACKGROUND: Frontal asymmetry plays a major role in depression. However, patients with treatment-resistant depression (TRD) have widespread hypofrontality. We investigated whether patients with TRD have a characteristic frontal activation pattern in functional near-infrared spectroscopy (fNIRS) findings and how the frontal cortex responds to different levels of cognitive tasks. METHODS: We enrolled 27 right-handed patients with TRD, 27 patients without TRD and 27 healthy controls. We used multichannel fNIRS to evaluate activation of the bilateral dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC) and left motor area in response to 3 tasks: finger tapping, a low cognitive-load motor task; verbal fluency, a moderate cognitive-load task; and a dual task involving simultaneous finger tapping and verbal fluency, a high cognitive-load task. RESULTS: We found significant between-group differences in left DLPFC activation for all 3 tasks. The healthy controls had cortical activation in the left motor area during finger tapping and the bilateral frontal cortex during the dual task. However, patients without TRD had right VLPFC activation during finger tapping and left DLPFC activation during the dual task. Patients with TRD had bilateral DLPFC activation during finger tapping but exhibited increased bilateral VLPFC and left motor area activation during verbal fluency and increased left motor area activation during the dual task. In healthy controls and patients without TRD, we found that the right VLPFC was positively correlated with depression severity. LIMITATIONS: Our cohort included only patients with late-onset depression. CONCLUSION: We found different patterns of abnormal frontal activation between patients with and without TRD. In patients without TRD, the right prefrontal cortex (PFC) was recruited during simple motor tasks. However, in patients with TRD, the bilateral PFC was recruited during simple tasks and motor cortical resources were used compensatorily during PFC-demanding complex cognitive tasks.

Multiarea Brain Activation and Gait Deterioration During a Cognitive and Motor Dual Task in Individuals With Parkinson Disease.

BACKGROUND AND PURPOSE: In people with Parkinson disease (PD), gait performance deteriorating during dual-task walking has been noted in previous studies. However, the effects of different types of dual tasks on gait performance and brain activation are still unknown. The purpose of this study was to investigate cognitive and motor dual-task walking performance on multiarea brain activity in individuals with PD. METHODS: Twenty-eight participants with PD were recruited and performed single walking (SW), walking while performing a cognitive task (WCT), and walking while performing a motor task (WMT) at their self-selected speed. Gait performance including walking speed, stride length, stride time, swing cycle, temporal and spatial variability, and dual-task cost (DTC) was recorded. Brain activation of the prefrontal cortex (PFC), premotor cortex (PMC), and supplementary motor areas (SMA) were measured using functional near-infrared spectroscopy during walking. RESULTS: Walking performance deteriorated upon performing a secondary task, especially the cognitive task. Also, a higher and more sustained activation in the PMC and SMA during WCT, as compared with the WMT and SW, in the late phase of walking was found. During WMT, however, the SMA and PMC did not show increased activation compared with during SW. Moreover, gait performance was negatively correlated with PMC and SMA activity during different walking tasks. DISCUSSION AND CONCLUSIONS: Individuals with mild to moderate PD demonstrated gait deterioration during dual-task walking, especially during WCT. The SMA and PMC were further activated in individuals with PD when performing cognitive dual-task walking.Supplemental Digital Content is Available in the Text.Video Abstract available for more insights from the authors (see the Video, Supplemental Digital Content 1, available at: http://links.lww.com/JNPT/A383 ).

Use of Contrast Medium Volume to Guide Prophylactic Hydration to Prevent Acute Kidney Injury After Contrast Administration: A Meta-Analysis.

OBJECTIVE. The purpose of this study was to determine whether contrast medium volume and method of administration and baseline estimated glomerular filtration rate influence the efficacy of prophylactic hydration for prevention of acute kidney injury after contrast administration. MATERIALS AND METHODS. An online search of PubMed conducted on August 25, 2017, produced a total of 697 studies. After the reports were reviewed, nine were included in this study. The extracted data on all patients in these studies were separated into a group that received prophylactic hydration and a group that did not. The following three parameters were used for subgroup analysis: contrast medium volume, contrast administration method, and baseline estimated glomerular filtration rate. The t test was performed, and study-level odds ratios with 95% CIs and p values were calculated. Tests of heterogeneity were conducted. RESULTS. When the volume of contrast agent administered exceeded 100 mL, hydration was beneficial in the prevention of contrast-induced acute kidney injury (odds ratio, 0.546). If the volume was less than 100 mL, hydration had no efficacy in preventing contrast-induced acute kidney injury (odds ratio, 0.917). Administration route and baseline estimated glomerular filtration rate exerted no effect on the efficacy of prophylactic hydration. CONCLUSION. For patients who receive less than 100 mL of contrast medium, the prevalent practice for contrast-enhanced CT studies, prophylactic hydration may not be necessary, regardless of the estimated glomerular filtration rate or route of contrast administration. For patients undergoing procedures requiring administration of large volumes of contrast medium, however, hydration is recommended to prevent contrast-induced acute kidney injury.

Novel gait training alters functional brain connectivity during walking in chronic stroke patients: a randomized controlled pilot trial.

BACKGROUND: A recent study has demonstrated that a turning-based treadmill program yields greater improvements in gait speed and temporal symmetry than regular treadmill training in chronic stroke patients. However, it remains unknown how this novel and challenging gait training shapes the cortico-cortical network and cortico-spinal network during walking in chronic stroke patients. The purpose of this study was to examine how a novel type of gait training, which is an unfamiliar but effective task for people with chronic stroke, enhances brain reorganization. METHODS: Subjects in the experimental and control groups received 30 min of turning-based treadmill training and regular treadmill training, respectively. Cortico-cortical connectivity and cortico-muscular connectivity during walking and gait performance were assessed before and after completing the 12-session training. RESULTS: Eighteen subjects (n = 9 per group) with a mean age of 52.5 ± 9.7 years and an overground walking speed of 0.61 ± 0.26 m/s consented and participated in this study. There were significant group by time interactions for gait speed, temporal gait symmetry, and cortico-cortical connectivity as well as cortico-muscular connectivity in walk-related frequency (24-40 Hz) over the frontal-central-parietal areas. Compared with the regular treadmill training, the turning-based treadmill training resulted in greater improvements in these measures. Moreover, the increases in cortico-cortical connectivity and cortico-muscular connectivity while walking were associated with improvements in temporal gait symmetry. CONCLUSIONS: Our findings suggest this novel turning-based treadmill training is effective for enhancing brain functional reorganization underlying cortico-cortical and corticomuscular mechanisms and thus may result in gait improvement in people with chronic stroke. TRIAL REGISTRATION: ACTRN12617000190303 . Registered 3 February 2017, retrospectively registered.

Intra- and Inter-Modular Connectivity Alterations in the Brain Structural Network of Spinocerebellar Ataxia Type 3.

In addition to cerebellar degeneration symptoms, patients with spinocerebellar ataxia type 3 (SCA3) exhibit extensive involvements with damage in the prefrontal cortex. A network model has been proposed for investigating the structural organization and functional mechanisms of clinical brain disorders. For neural degenerative diseases, a cortical feature-based structural connectivity network can locate cortical atrophied regions and indicate how their connectivity and functions may change. The brain network of SCA3 has been minimally explored. In this study, we investigated this network by enrolling 48 patients with SCA3 and 48 healthy subjects. A novel three-dimensional fractal dimension-based network was proposed to detect differences in network parameters between the groups. Copula correlations and modular analysis were then employed to categorize and construct the structural networks. Patients with SCA3 exhibited significant lateralized atrophy in the left supratentorial regions and significantly lower modularity values. Their cerebellar regions were dissociated from higher-level brain networks, and demonstrated decreased intra-modular connectivity in all lobes, but increased inter-modular connectivity in the frontal and parietal lobes. Our results suggest that the brain networks of patients with SCA3 may be reorganized in these regions, with the introduction of certain compensatory mechanisms in the cerebral cortex to minimize their cognitive impairment syndrome.

Assessing the selective therapeutic efficacy of superparamagnetic erlotinib nanoparticles in lung cancer by using quantitative magnetic resonance imaging and a nuclear factor kappa-B reporter gene system.

Non-small-cell lung cancer (NSCLC) is the most common type of lung cancer. Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors are commonly used as the first-line treatment for advanced NSCLC; however, the efficacy of drug delivery remains unknown. Hence, we successfully developed erlotinib-conjugated iron oxide nanoparticles (FeDC-E NPs) as theranostic probe that can potentially provide a new avenue for monitoring drug delivering through noninvasive magnetic resonance imaging. MRI ΔR2* relaxivity measurements offer an opportunity to quantitatively evaluate the uptake of FeDC-E NPs at cellular and tumoral levels. Additionally, NF-κB reporter gene system provides NF-κB activation status monitoring to validate the therapeutic efficiency of FeDC-E NPs. FeDC-E NPs not only inhibit the tumor growth and NF-κB-modulated antiapoptotic mechanism but also trigger extrinsic and intrinsic apoptotic pathways. Taken together, dual functional FeDC-E NPs offer diagnostic and therapeutic benefits against lung cancers, indicating that our presented probe could be applied in clinical.

Identification of epidermal growth factor receptor-positive glioblastoma using lipid-encapsulated targeted superparamagnetic iron oxide nanoparticles in vitro.

BACKGROUND: Targeted superparamagnetic iron oxide (SPIO) nanoparticles have emerged as a promising biomarker detection tool for molecular magnetic resonance (MR) image diagnosis. To identify patients who could benefit from Epidermal growth factor receptor (EGFR)-targeted therapies, we introduce lipid-encapsulated SPIO nanoparticles and hypothesized that anti-EGFR antibody cetuximab conjugated of such nanoparticles can be used to identify EGFR-positive glioblastomas in non-invasive T2 MR image assays. The newly introduced lipid-coated SPIOs, which imitate biological cell surface and thus inherited innate nonfouling property, were utilized to reduce nonspecific binding to off-targeted cells and prevent agglomeration that commonly occurs in nanoparticles. RESULTS: The synthesized targeted EGFR-antibody-conjugated SPIO (EGFR-SPIO) nanoparticles were characterized using dynamic light scattering, zeta potential assays, gel electrophoresis mobility shift assays, transmission electron microscopy (TEM) images, and cell line affinity assays, and the results showed that the conjugation was successful. The targeting efficiency of the synthesized EGFR-SPIO nanoparticles was confirmed through Prussian blue staining and TEM images by using glioblastoma cell lines with high or low EGFR expression levels. The EGFR-SPIO nanoparticles preferentially targeted U-251 cells, which have high EGFR expression, and were internalized by cells in a prolonged incubation condition. Moreover, the T2 MR relaxation time of EGFR-SPIO nanoparticles could be used for successfully identifying glioblastoma cells with elevated EGFR expression in vitro and distinguishing U-251 cells from U-87MG cells, which have low EFGR expression. CONCLUSION: These findings reveal that the lipid-encapsulated EGFR-SPIO nanoparticles can specifically target cells with elevated EGFR expression in the three tested human glioblastoma cell lines. The results of this study can be used for noninvasive molecular MR image diagnosis in the future.

Territory-Related Functional Connectivity Changes Associated with Verbal Memory Decline in Patients with Unilateral Asymptomatic Internal Carotid Stenosis.

BACKGROUND AND PURPOSE: Verbal memory decline is a common complaint of patients with severe asymptomatic stenosis of the internal carotid artery (aICS). Previous publications explored the associations between verbal memory decline and altered functional connectivity (FC) after aICS. Patients with severe aICS may show reduced perfusion in the ipsilateral territory and redistribution of cerebral blood flow to compensate for the deficient regions, including expansion of the posterior and contralateral ICA territories via the circle of Willis. However, aICS-related FC changes in anterior and posterior territories and the impact of the sides of stenosis were less explored. This study aims to investigate the altered FC in anterior and posterior circulation territories of patients with left or right unilateral aICS and its association with verbal memory decline. MATERIALS AND METHODS: We enrolled 15 healthy controls (HCs), 22 patients with left aICS (aICSL), and 33 patients with right aICS (aICSR) to receive fMRI, Mini-Mental State Examination (MMSE), the Digit Span Test (DST), and the 12-item Chinese version of Verbal Learning Tests. We selected brain regions associated with verbal memory within anterior and posterior circulation territories. Territory-related FC alterations and verbal memory decline were identified by comparing the aICSL and aICSR groups with HC groups (P < .05, corrected for multiple comparisons), respectively. Furthermore, the association between altered FC and verbal memory decline was tested with the Pearson correlation analysis. RESULTS: Compared with HCs, patients with aICSL or aICSR had significant impairment in delayed recall of verbal memory. Decline in delayed recall of verbal memory was significantly associated with altered FC between the right cerebellum and right middle temporal pole in the posterior circulation territory (r = 0.40, P = .03) in the aICSR group and was significantly associated with altered FC between the right superior medial frontal gyrus and left lingual gyrus in the anterior circulation territory (r = 0.56, P = .01) in the aICSL group. CONCLUSIONS: Patients with aICSL and aICSR showed different patterns of FC alterations in both anterior and posterior circulation territories, which suggests that the side of aICS influences the compensatory mechanism for decline in delayed recall of verbal memory.

Anisotropy component of DTI reveals long-term neuroinflammation following repetitive mild traumatic brain injury in rats.

BACKGROUND: This study aimed to investigate the long-term effects of repetitive mild traumatic brain injury (rmTBI) with varying inter-injury intervals by measuring diffusion tensor metrics, including mean diffusivity (MD), fractional anisotropy (FA), and diffusion magnitude (L) and pure anisotropy (q). METHODS: Eighteen rats were randomly divided into three groups: short-interval rmTBI (n = 6), long-interval rmTBI (n = 6), and sham controls (n = 6). MD, FA, L, and q values were analyzed from longitudinal diffusion tensor imaging at days 50 and 90 after rmTBI. Immunohistochemical staining against neurons, astrocytes, microglia, and myelin was performed. Analysis of variance, Pearson correlation coefficient, and simple linear regression model were used. RESULTS: At day 50 post-rmTBI, lower cortical FA and q values were shown in the short-interval group (p ≤ 0.038). In contrast, higher FA and q values were shown for the long-interval group (p ≤ 0.039) in the corpus callosum. In the ipsilesional external capsule and internal capsule, no significant changes were found in FA, while lower L and q values were shown in the short-interval group (p ≤ 0.028) at day 90. The q values in the external capsule and internal capsule were negatively correlated with the number of microglial cells and the total number of astroglial cells (p ≤ 0.035). CONCLUSION: Tensor scalar measurements, such as L and q values, are sensitive to exacerbated chronic injury induced by rmTBI with shorter inter-injury intervals and reflect long-term astrogliosis induced by the cumulative injury. RELEVANCE STATEMENT: Tensor scalar measurements, including L and q values, are potential DTI metrics for detecting long-term and subtle injury following rmTBI; in particular, q values may be used for quantifying remote white matter (WM) changes following rmTBI. KEY POINTS: The alteration of L and q values was demonstrated after chronic repetitive mild traumatic brain injury. Changing q values were observed in the impact site and remote WM. The lower q values in the remote WM were associated with astrogliosis.

Prefrontal activity and heart rate variability during cognitive tasks may show different changes in young and older adults with and without mild cognitive impairment.

Background: Age-related decline in cognitive function is often linked to changed prefrontal cortex (PFC) activity and heart rate variability (HRV). Mild cognitive impairment (MCI), a transitional stage between normal aging and dementia, might have further degeneration beyond aging. This study aimed to investigate the differences between young and older adults with or without MCI in cognitive functions, task-induced PFC activation and HRV changes. Methods: Thirty-one healthy young adults (YA), 44 older adults (OA), and 28 older adults with MCI (OA-MCI) were enrolled and compared in this cross-sectional study. Each participant received a one-time assessment including cognitive and executive functions, as well as the simultaneous recording of PFC activity and HRV during a cognitive task paradigm. Results: We observed age-related decrease in global cognitive functions, executive functions, HRV, and increase in PFC activity. The MCI further deteriorated the global cognitive and executive performances, but not the HRV or the prefrontal activation. Conclusion: Older people showed lower performances in general cognitive function and executive function, compensatory increase of PFC activity, and reduced HRV. Older people with MCI had further deterioration in cognitive performance, but not in PFC activation and HRV.

Systematic review and meta-analysis of deep learning applications in computed tomography lung cancer segmentation.

BACKGROUND: Accurate segmentation of lung tumors on chest computed tomography (CT) scans is crucial for effective diagnosis and treatment planning. Deep Learning (DL) has emerged as a promising tool in medical imaging, particularly for lung cancer segmentation. However, its efficacy across different clinical settings and tumor stages remains variable. METHODS: We conducted a comprehensive search of PubMed, Embase, and Web of Science until November 7, 2023. We assessed the quality of these studies by using the Checklist for Artificial Intelligence in Medical Imaging and the Quality Assessment of Diagnostic Accuracy Studies-2 tools. This analysis included data from various clinical settings and stages of lung cancer. Key performance metrics, such as the Dice similarity coefficient, were pooled, and factors affecting algorithm performance, such as clinical setting, algorithm type, and image processing techniques, were examined. RESULTS: Our analysis of 37 studies revealed a pooled Dice score of 79 % (95 % CI: 76 %-83 %), indicating moderate accuracy. Radiotherapy studies had a slightly lower score of 78 % (95 % CI: 74 %-82 %). A temporal increase was noted, with recent studies (post-2022) showing improvement from 75 % (95 % CI: 70 %-81 %). to 82 % (95 % CI: 81 %-84 %). Key factors affecting performance included algorithm type, resolution adjustment, and image cropping. QUADAS-2 assessments identified ambiguous risks in 78 % of studies due to data interval omissions and concerns about generalizability in 8 % due to nodule size exclusions, and CLAIM criteria highlighted areas for improvement, with an average score of 27.24 out of 42. CONCLUSION: This meta-analysis demonstrates DL algorithms' promising but varied efficacy in lung cancer segmentation, particularly higher efficacy noted in early stages. The results highlight the critical need for continued development of tailored DL models to improve segmentation accuracy across diverse clinical settings, especially in advanced cancer stages with greater challenges. As recent studies demonstrate, ongoing advancements in algorithmic approaches are crucial for future applications.

Progress in Serial Imaging for Prognostic Stratification of Lung Cancer Patients Receiving Immunotherapy: A Systematic Review and Meta-Analysis.

Immunotherapy, particularly with checkpoint inhibitors, has revolutionized non-small cell lung cancer treatment. Enhancing the selection of potential responders is crucial, and researchers are exploring predictive biomarkers. Delta radiomics, a derivative of radiomics, holds promise in this regard. For this study, a meta-analysis was conducted that adhered to PRISMA guidelines, searching PubMed, Embase, Web of Science, and the Cochrane Library for studies on the use of delta radiomics in stratifying lung cancer patients receiving immunotherapy. Out of 223 initially collected studies, 10 were included for qualitative synthesis. Stratifying patients using radiomic models, the pooled analysis reveals a predictive power with an area under the curve of 0.81 (95% CI 0.76-0.86, p < 0.001) for 6-month response, a pooled hazard ratio of 4.77 (95% CI 2.70-8.43, p < 0.001) for progression-free survival, and 2.15 (95% CI 1.73-2.66, p < 0.001) for overall survival at 6 months. Radiomics emerges as a potential prognostic predictor for lung cancer, but further research is needed to compare traditional radiomics and deep-learning radiomics.

Personalized prediction of immunotherapy response in lung cancer patients using advanced radiomics and deep learning.

BACKGROUND: Lung cancer (LC) is a leading cause of cancer-related mortality, and immunotherapy (IO) has shown promise in treating advanced-stage LC. However, identifying patients likely to benefit from IO and monitoring treatment response remains challenging. This study aims to develop a predictive model for progression-free survival (PFS) in LC patients with IO based on clinical features and advanced imaging biomarkers. MATERIALS AND METHODS: A retrospective analysis was conducted on a cohort of 206 LC patients receiving IO treatment. Pre-treatment computed tomography images were used to extract advanced imaging biomarkers, including intratumoral and peritumoral-vasculature radiomics. Clinical features, including age, gene status, hematology, and staging, were also collected. Key radiomic and clinical features for predicting IO outcomes were identified using a two-step feature selection process, including univariate Cox regression and chi-squared test, followed by sequential forward selection. The DeepSurv model was constructed to predict PFS based on clinical and radiomic features. Model performance was evaluated using the area under the time-dependent receiver operating characteristic curve (AUC) and concordance index (C-index). RESULTS: Combining radiomics of intratumoral heterogeneity and peritumoral-vasculature with clinical features demonstrated a significant enhancement (p < 0.001) in predicting IO response. The proposed DeepSurv model exhibited a prediction performance with AUCs ranging from 0.76 to 0.80 and a C-index of 0.83. Furthermore, the predicted personalized PFS curves revealed a significant difference (p < 0.05) between patients with favorable and unfavorable prognoses. CONCLUSIONS: Integrating intratumoral and peritumoral-vasculature radiomics with clinical features enabled the development of a predictive model for PFS in LC patients with IO. The proposed model's capability to estimate individualized PFS probability and differentiate the prognosis status held promise to facilitate personalized medicine and improve patient outcomes in LC.

Deep learning-based workflow for automatic extraction of atria and epicardial adipose tissue on cardiac computed tomography in atrial fibrillation.

BACKGROUND: Preoperative estimation of the volume of the left atrium (LA) and epicardial adipose tissue (EAT) on computed tomography (CT) images is associated with an increased risk of atrial fibrillation (AF) recurrence. We aimed to design a deep learning-based workflow to provide reliable automatic segmentation of the atria, pericardium, and EAT for future applications in the management of AF. METHODS: This study enrolled 157 patients with AF who underwent first-time catheter ablation between January 2015 and December 2017 at Taipei Veterans General Hospital. Three-dimensional (3D) U-Net models of the LA, right atrium (RA), and pericardium were used to develop a pipeline for total, LA-EAT, and RA-EAT automatic segmentation. We defined fat within the pericardium as tissue with attenuation between -190 and -30 HU and quantified the total EAT. Regions between the dilated endocardial boundaries and endocardial walls of the LA or RA within the pericardium were used to detect voxels attributed to fat, thus estimating LA-EAT and RA-EAT. RESULTS: The LA, RA, and pericardium segmentation models achieved Dice coefficients of 0.960 ± 0.010, 0.945 ± 0.013, and 0.967 ± 0.006, respectively. The 3D segmentation models correlated well with the ground truth for the LA, RA, and pericardium ( r = 0.99 and p < 0.001 for all). The Dice coefficients of our proposed method for EAT, LA-EAT, and RA-EAT were 0.870 ± 0.027, 0.846 ± 0.057, and 0.841 ± 0.071, respectively. CONCLUSION: Our proposed workflow for automatic LA, RA, and EAT segmentation using 3D U-Nets on CT images is reliable in patients with AF.