Hippocampal iron overload and spatial reference memory impairment: Insights from a rat model.

BACKGROUND: Brain iron overload may induce neuronal death and lead to cognitive impairment. The hippocampus is a critical limbic structure involved in memory. This study aimed to investigate iron overload and its role in hippocampal damage and memory impairment using a rat model. METHODS: Young rats (2 weeks old) received intraperitoneal injections of high-dose iron solution (Group H, n = 10), low-dose iron solution (Group L, n = 10) and normal saline as control (Group D, n = 5). The Morris water maze (MWM) test was performed on all rats to evaluate their spatial reference memory by assessing their escape latency time and number of platform crossing. The iron content and neuronal damage in hippocampal tissue sections of the rats were assessed semi-quantitatively using diaminobenzidine (DAB)-enhanced Perl's Prussian blue (PPB) staining, and their correlation with spatial reference memory performance was evaluated. RESULTS: The escape latency in Group H was significantly longer compared to Groups L and D (P < 0.05). The number of platform crossings was significantly lower in Group H than in Group L or D (P < 0.001). The neuronal cells in Group H had more brown iron deposits than those of Groups L and D. There were significant correlations between the severity of structural damage in the hippocampal tissue and the number of platform crossings (P1 = 0.001 for Group H; P2 = 0.043 for Group L). CONCLUSION: This study showed an association between hippocampal iron-induced structural damage and spatial reference memory impairment in a rat model. This work should advance our understanding of hippocampal iron overload on cognitive functioning.

Ensemble learning-based pretreatment MRI radiomic model for distinguishing intracranial extraventricular ependymoma from glioblastoma multiforme.

This study aims to develop an ensemble learning (EL) method based on magnetic resonance (MR) radiomic features to preoperatively differentiate intracranial extraventricular ependymoma (IEE) from glioblastoma (GBM). This retrospective study enrolled patients with histopathologically confirmed IEE and GBM from June 2016 to June 2021. Radiomics features were extracted from T1-weighted imaging (T1WI) and T2-weighted imaging (T2WI) sequence images, and classification models were constructed using EL methods and logistic regression (LR). The efficiency of the models was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis. The combined EL model, based on clinical parameters and radiomic features from T1WI and T2WI images, demonstrated good discriminative ability, achieving an area under the receiver operating characteristics curve (AUC) of 0.96 (95% CI 0.94-0.98), a specificity of 0.84, an accuracy of 0.92, and a sensitivity of 0.95 in the training set, and an AUC of 0.89 (95% CI 0.83-0.94), a specificity of 0.83, an accuracy of 0.81, and a sensitivity of 0.74 in the validation set. The discriminative efficacy of the EL model was significantly higher than that of the LR model. Favorable calibration performance and clinical applicability for the EL model were observed. The EL model combining preoperative MR-based tumor radiomics and clinical data showed high accuracy and sensitivity in differentiating IEE from GBM preoperatively, which may potentially assist in clinical management of these brain tumors.

Altered gyrification in chemotherapy-treated older long-term breast cancer survivors.

PURPOSE: The purpose of this prospective longitudinal study was to evaluate the changes in brain surface gyrification in older long-term breast cancer survivors 5-15 years after chemotherapy treatment. METHODS: Older breast cancer survivors aged ≥ 65 years treated with chemotherapy (C+) or without chemotherapy (C-) 5-15 years prior and age- and sex-matched healthy controls (HC) were recruited (time point 1 (TP1)) and followed up for 2 years (time point 2 (TP2)). Study assessments for both time points included neuropsychological (NP) testing with the NIH Toolbox cognition battery and cortical gyrification analysis based on brain MRI. RESULTS: The study cohort with data for both TP1 and TP2 consisted of the following: 10 participants for the C+ group, 12 participants for the C- group, and 13 participants for the HC group. The C+ group had increased gyrification in six local gyral regions including the right fusiform, paracentral, precuneus, superior, middle temporal gyri and left pars opercularis gyrus, and it had decreased gyrification in two local gyral regions from TP1 to TP2 (p < .05, Bonferroni corrected). The C- and HC groups showed decreased gyrification only (p < .05, Bonferroni corrected). In the C+ group, changes in right paracentral gyrification and crystalized composite scores were negatively correlated (R = -0.76, p = .01). CONCLUSIONS: Altered gyrification could be the neural correlate of cognitive changes in older chemotherapy-treated long-term breast cancer survivors.

Neuroimaging in the diagnosis and treatment of cerebral toxoplasmosis in children with severe ß-thalassemia after allo-HSCT.

Children with severe ß-thalassemia major (ß-TM) are at high risk of developing toxoplasmosis after allogeneic hematopoietic stem cell transplantation (allo-HSCT). The aim of this study was to identify the neuroimaging findings of cerebral toxoplasmosis in pediatric patients with ß-TM for early diagnosis and treatment of cerebral toxoplasmosis. We performed a retrospective assessment of clinical and neuroimaging data of children with severe ß-TM who had cerebral toxoplasmosis after allo-HSCT. Additionally, we reviewed and summarized the literature on cerebral toxoplasmosis in patients with other underlying conditions. This case series identified three children who had severe ß-TM and had subsequent cerebral toxoplasmosis after allo-HSCT. In addition, we identified 23 patients from literature who had toxoplasmosis and had underlying conditions other than ß-TM. We found that the most common clinical symptom among the patients from our series and the patients from literature was fever upon presentation. We identified the typical neuroimaging findings including brain lesions with ring enhancement and eccentric/central nuclear target-like enhancement, which should facilitate early diagnosis and treatment of cerebral toxoplasmosis.

Spatial iTME analysis of KRAS mutant NSCLC and immunotherapy outcome.

We conducted spatial immune tumor microenvironment (iTME) profiling using formalin-fixed paraffin-embedded (FFPE) samples of 25 KRAS-mutated non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), including 12 responders and 13 non-responders. An eleven-marker panel (CD3, CD4, CD8, FOXP3, CD68, arginase-1, CD33, HLA-DR, pan-keratin (PanCK), PD-1, and PD-L1) was used to study the tumor and immune cell compositions. Spatial features at single cell level with cellular neighborhoods and fractal analysis were determined. Spatial features and different subgroups of CD68+ cells and FOXP3+ cells being associated with response or resistance to ICIs were also identified. In particular, CD68+ cells, CD33+ and FOXP3+ cells were found to be associated with resistance. Interestingly, there was also significant association between non-nuclear expression of FOXP3 being resistant to ICIs. We identified CD68dim cells in the lung cancer tissues being associated with improved responses, which should be insightful for future studies of tumor immunity.

Nomogram for prediction of hearing rehabilitation outcome in children with congenital sensorineural hearing loss after cochlear implantation.

Background: Reliable predictors for rehabilitation outcomes in patients with congenital sensorineural hearing loss (CSNHL) after cochlear implantation (CI) are lacking. The purchase of this study was to develop a nomogram based on clinical characteristics and neuroimaging features to predict the outcome in children with CSNHL after CI. Methods: Children with CSNHL prior to CI surgery and children with normal hearing were enrolled into the study. Clinical data, high resolution computed tomography (HRCT) for ototemporal bone, conventional brain MRI for structural analysis and brain resting-state fMRI (rs-fMRI) for the power spectrum assessment were assessed. A nomogram combining both clinical and imaging data was constructed using multivariate logistic regression analysis. Model performance was evaluated and validated using bootstrap resampling. Results: The final cohort consisted of 72 children with CSNHL (41 children with poor outcome and 31 children with good outcome) and 32 healthy controls. The white matter lesion from structural assessment and six power spectrum parameters from rs-fMRI, including Power4, Power13, Power14, Power19, Power23 and Power25 were used to build the nomogram. The area under the receiver operating characteristic (ROC) curve of the nomogram obtained using the bootstrapping method was 0.812 (95 % CI = 0.772-0.836). The calibration curve showed no statistical difference between the predicted value and the actual value, indicating a robust performance of the nomogram. The clinical decision analysis curve showed a high clinical value of this model. Conclusions: The nomogram constructed with clinical data, and neuroimaging features encompassing ototemporal bone measurements, white matter lesion values from structural brain MRI and power spectrum data from rs-fMRI showed a robust performance in predicting outcome of hearing rehabilitation in children with CSNHL after CI.

Structural and practical identifiability of contrast transport models for DCE-MRI.

Contrast transport models are widely used to quantify blood flow and transport in dynamic contrast-enhanced magnetic resonance imaging. These models analyze the time course of the contrast agent concentration, providing diagnostic and prognostic value for many biological systems. Thus, ensuring accuracy and repeatability of the model parameter estimation is a fundamental concern. In this work, we analyze the structural and practical identifiability of a class of nested compartment models pervasively used in analysis of MRI data. We combine artificial and real data to study the role of noise in model parameter estimation. We observe that although all the models are structurally identifiable, practical identifiability strongly depends on the data characteristics. We analyze the impact of increasing data noise on parameter identifiability and show how the latter can be recovered with increased data quality. To complete the analysis, we show that the results do not depend on specific tissue characteristics or the type of enhancement patterns of contrast agent signal.

Association Between 18F-FDG PET Activity and HER2 Status in Breast Cancer Brain Metastases.

Purpose: The objective of this study was to evaluate whether uptake on 18F-fluorodeoxyglucose (18F-FDG) PET could help differentiate HER2-positive from HER2-negative breast cancer brain metastases. Methods: In this retrospective, cross-sectional study of a cohort of 14 histologically proven breast cancer brain metastases, we analyzed both preoperative 18F-FDG PET/CT and HER2 status of the resected/biopsied brain specimens. The maximum standardized uptake values (SUVmax) of the lesions were normalized to contralateral normal white matter and compared using Mann-Whitney U tests. Results: The study cohort was comprised of 12 women with breast cancer with a mean age of 59 years (range: 43-76 years) with a total of 14 distinct brain metastatic lesions. The SUVmax ratio of HER2-positive breast cancer brain metastases was significantly greater than that of HER2-negative lesions (3.98 vs 1.79, U = 38.00, p = 0.008). Conclusion: The SUVmax ratio may help to identify the HER2 status of breast cancer brain metastases, if validated prospectively.

Alteration of prefrontal cortex and its associations with emotional and cognitive dysfunctions in adolescent borderline personality disorder.

The neurobiological mechanism of borderline personality disorder (BPD) in adolescents remains unclear. The study aimed to assess the alterations in neural activity within prefrontal cortex in adolescents with BPD and investigate the relationship of prefrontal activity with emotional regulation and cognitive function. This study enrolled 50 adolescents aged 12-17 years with BPD and 21 gender and age-matched healthy control (HC) participants. Study assessment for each participant included a brain resting-state functional MRI (rs-fMRI), clinical assessment questionnaires such as Borderline Personality Features Scale (BPFS), Difficulties in Emotion Regulation Scale (DERS), Ottawa Self-Injury Inventory and Childhood Trauma Questionnaire (CTQ) and cognitive testing with Stroop Color-Word Test (SCWT). Fractional amplitude of low-frequency fluctuations (fALFF) and seed-based functional connectivity (FC) were obtained from rs-fMRI analysis. Correlation analysis was also performed to evaluate the associations of the neuroimaging metrics such as fALFF and FC with clinical assessment questionnaire and cognitive testing scores. Adolescents with BPD showed increased fALFF values in the right inferior frontal gyrus and decreased activity in the left middle frontal gyrus as compared to the HC group (p < 0.05, cluster size ≥ 100, FWE correction). In adolescents with BPD, increased fALFF in the right inferior frontal gyrus was related to the BPFS (emotional dysregulation), DERS-F (lacking of emotional regulation strategies) and Ottawa Self-Injury Inventory-4 C scores (internal emotional regulation function of self-injurious behavior). The reduced fALFF in the left middle frontal gyrus was associated with the SCWT-A (reading characters) and the SCWT-B (reading color) scores. Additionally, the fALFF values in the left middle frontal gyrus and the right inferior frontal gyrus were related to the CTQ-D (emotional neglect) (p < 0.05). The left middle frontal gyrus exhibited increased FC with the right hippocampus, left inferior temporal gyrus and right inferior frontal gyrus (voxel p < 0.001, cluster p < 0.05, FWE correction). The increased FC between the left middle frontal gyrus and the right hippocampus was related to the SCWT-C (cognitive flexibility) score. We observed diverging changes in intrinsic brain activity in prefrontal cortex, and neural compensatory changes to maintain function in adolescents with BPD. In addition, decreased neural function was closely associated with emotional dysregulation, while increased neural function as indicated by brain activity and FC was associated with cognitive dysfunction. These results indicated that alterations of intrinsic brain activity may be one of the underlying neurobiological markers for clinical symptoms in adolescents with BPD.

Artificial intelligence-assisted measurements of coronary computed tomography angiography parameters such as stenosis, flow reserve, and fat attenuation for predicting major adverse cardiac events in patients with coronary arterial disease.

Advancements in artificial intelligence (AI) offer promising tools for improving diagnostic accuracy and patient outcomes in cardiovascular medicine. This study explores the potential of AI-assisted measurements in enhancing the prediction of major adverse cardiac events (MACE) in patients with coronary artery disease (CAD). We conducted a retrospective cohort study involving patients diagnosed with CAD who underwent coronary computed tomography angiography (CCTA). Participants were classified into MACE and non-MACE groups based on their clinical outcomes. Clinical characteristics and AI-assisted measurements of CCTA parameters, including CT-derived fractional flow reserve (CT-FFR) and fat attenuation index (FAI), were collected. Both univariate and multivariable logistic regression analyses were performed to identify independent predictors of MACE, which were used to build predictive models. Statistical analyses revealed three independent predictors of MACE: severe stenosis, CT-FFR ≤ 0.8, and mean FAI (P < 0.05). Seven predictive models incorporating various combinations of these predictors were developed. The model combining all three predictors demonstrated superior performance, as evidenced by the receiver operating characteristic (ROC) curve, with an area under the curve (AUC) of 0.811 (95% confidence interval [CI] 0.774 - 0.847), a sensitivity of 0.776, and a specificity of 0.726. Our findings suggest that AI-assisted CCTA analysis, particularly using fractional flow reserve (FFR) and FAI, could significantly improve the prediction of MACE in patients with CAD, thereby potentially aiding clinical decision making.

Nomogram incorporating preoperative MRI-VASARI features for differentiating intracranial extraventricular ependymoma from glioblastoma.

Background: Intracranial extraventricular ependymoma (IEE) and glioblastoma (GBM) may have similar imaging findings but different prognosis. This study aimed to develop and validate a nomogram based on magnetic resonance imaging (MRI) Visually AcceSAble Rembrandt Images (VASARI) features for preoperatively differentiating IEE from GBM. Methods: The clinical data and the MRI-VASARI features of patients with confirmed IEE (n=114) and confirmed GBM (n=258) in a multicenter cohort were retrospectively analyzed. Predictive models for differentiating IEE from GBM were built using a multivariate logistic regression method. A nomogram was generated and the performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness. Results: The predictors identified in this study consisted of six VASARI features and four clinical features. Compared with the individual models, the combined model incorporating clinical and VASARI features had the highest area under the curve (AUC) value [training set: 0.99, 95% confidence interval (CI): 0.98-1.00; validation set: 0.97, 95% CI: 0.94-1.00] in comparison to the clinical model. The nomogram was well calibrated with significant clinical benefit according to the calibration curve and decision curve analyses. Conclusions: The nomogram combining clinical and MRI-VASARI characteristics was robust for differentiating IEE from GBM preoperatively and may potentially assist in diagnosis and treatment of brain tumors.

Effect of chemotherapy on hippocampal volume and shape in older long-term breast cancer survivors.

Purpose: The objective of this study was to assess changes in hippocampal volume and shape in older long-term breast cancer survivors who were exposed to chemotherapy 5-15 years prior. Methods: This study recruited female long-term breast cancer survivors aged 65 years or older with a history of chemotherapy (C+), age-matched breast cancer survivors who did not receive chemotherapy (C-), and healthy controls (HC). The participants were recruited 5-15 years after chemotherapy at time point 1 (TP1) and were followed up for 2 years at time point 2 (TP2). Assessments included hippocampal volume and shape from brain MRI scans and neuropsychological (NP) tests. Results: At TP1, each of the three groups was comprised of 20 participants. The C+ group exhibited a hippocampal volume loss estimated in proportion with total intracranial volume (ICV) in both the left and right hemispheres from TP1 to TP2. Regarding the hippocampal shape at TP1, the C+ group displayed inward changes compared to the control groups. Within the C+ group, changes in right hippocampal volume adjusted with ICV were positively correlated with crystalized composite scores (R = 0.450, p = 0.044). Additionally, in C+ groups, chronological age was negatively correlated with right hippocampal volume adjusted with ICV (R = -0.585, p = 0.007). Conclusion: The observed hippocampal volume reduction and inward shape deformation within the C+ group may serve as neural basis for cognitive changes in older long-term breast cancer survivors with history of chemotherapy treatment.

Glofitamab stimulates immune cell infiltration of CNS tumors and induces clinical responses in secondary CNS lymphoma.

ABSTRACT: Although CD20×CD3 bispecific antibodies are effective against systemic B-cell lymphomas, their efficacy in central nervous system (CNS) lymphoma is unknown. Here, we report the CD20×CD3 bispecific glofitamab penetrates the blood-brain barrier, stimulates immune-cell infiltration of CNS tumors, and induces clinical responses in patients with secondary CNS.

Neuroimaging features of primary central nervous system post-transplantation lymphoproliferative disorder following hematopoietic stem cell transplant in patients with ß-thalassemia: a case series and review of literature.

PURPOSE: Primary central nervous system post-transplantation lymphoproliferative disorder (PCNS-PTLD) is a rare but serious complication of hematopoietic stem cell transplantation (HSCT) in patients with severe ß-thalassemia. This study aimed to assess the clinical presentation, pathological characteristics, neuroimaging findings, and treatment strategies in patients with ß-thalassemia who developed PCNS-PTLD and to compare a case series from our transplant center to reported cases from literature. METHODS: We retrospectively reviewed our hospital database and identified four cases of pathologically confirmed PCNS-PTLD without a history of systemic PTLD in patients with severe ß-thalassemia after HSCT. We also performed a relevant literature review on PCNS-PTLD. RESULTS: The median time from transplantation to diagnosis of PCNS-PTLD was 5.5 months. Intracerebral lesions were usually multiple involving both supratentorial and infratentorial regions with homogeneous or rim enhancement. All patients had pathologically confirmed PCNS-PTLD with three patients having diffuse large B-cell lymphoma and the fourth patient having plasmacytic hyperplasia. There was low response to treatment with a median survival of 83 days. CONCLUSION: PCNS-PTLD should be considered in the differential diagnosis of patients with ß-thalassemia who had an intracranial lesion on neuroimaging after HSCT. CRITICAL RELEVANCE STATEMENT: This case series with a comprehensive review of neuroimaging and clinical characteristics of children with primary central nervous system post-transplantation lymphoproliferative disorder should advance our understanding and improve management of this rare yet severe complication following transplant for ß-thalassemia. KEY POINTS: • We assessed clinical presentation, treatment strategies, and neuroimaging characteristics of PCNS-PTLD in patients with ß-thalassemia after transplantation. • Patients with ß-thalassemia may have post-transplantation lymphoproliferative disorder presenting as brain lesions on neuroimaging. • Neuroimaging findings of the brain lesions are helpful for prompt diagnosis and proper management.

Altered gray matter volume and functional connectivity in adolescent borderline personality disorder with non-suicidal self-injury behavior.

BACKGROUND AND OBJECTIVES: Non-suicidal self-injury (NSSI) behavior is one of the characteristics of borderline personality disorder (BPD) in adolescents. Prior studies have shown that adolescents with BPD may have a unique pattern of brain alterations. The purpose of this study was to investigate the alterations in brain structure and function including gray matter volume and resting-state functional connectivity in adolescents with BPD, and to assess the association between NSSI behavior and brain changes on neuroimaging in adolescents with BPD. METHODS: 53 adolescents with BPD aged 12-17 years and 39 age-gender matched healthy controls (HCs) were enrolled into this study. Brain magnetic resonance imaging (MRI) was acquired with both 3D-T1 weighted structural imaging and resting-state functional imaging. Voxel-based morphometry (VBM) analysis for gray matter volume and seed-based functional connectivity (FC) analysis were performed for assessing gray matter volume and FC. Clinical assessment for NSSI, mood, and depression was also obtained. Correlative analysis of gray matter alterations with self-injury or mood scales were performed. RESULTS: There were reductions of gray matter volume in the limbic-cortical circuit and default mode network in adolescents with BPD as compared to HCs (FWE P < 0.05, cluster size ≥ 1000). The diminished gray matter volumes in the left putamen and left middle occipital gyrus were negatively correlated with NSSI in adolescents with BPD (r = - 0.277 and P = 0.045, r = - 0.422 and P = 0.002, respectively). Furthermore, there were alterations of FC in these two regions with diminished gray matter volumes (voxel P < 0.001, cluster P < 0.05, FWE corrected). CONCLUSIONS: Our results suggest that diminished gray matter volume of the limbic-cortical circuit and default mode network may be an important neural correlate in adolescent BPD. In addition, the reduced gray matter volume and the altered functional connectivity may be associated with NSSI behavior in adolescents with BPD.

Altered brain activity and cognitive impairment in patients with psoriasis.

BACKGROUND: Patients with psoriasis may have cognitive impairment. However, there is limited information regarding intrinsic brain activity and cognitive function in patients with psoriasis. OBJECTIVES: This study aim to assess alterations of intrinsic brain activity and its association with cognitive function in patients with psoriasis. METHODS: A total of 222 patients with psoriasis aged 18-70 years and 144 age and gender-matched healthy controls (HCs) were enrolled into this study. All subjects underwent brain resting-state functional magnetic resonance imaging (rs-fMRI) and neuropsychological testing. The rs-fMRI data were analysed for both intrinsic brain activity as indicated by amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity (FC). Correlative analysis of brain activity with cognitive assessment was performed. RESULTS: Compared with the HCs, patients with psoriasis had worse cognitive performance in the Trail Making Test, Digit Span Test and Stroop Color-Word Test (p < 0.05). Patients with psoriasis showed decreased ALFF in the left superior frontal gyrus, the left medial superior frontal gyrus and the right precuneus gyrus; as well as enhanced ALFF in the left paracentral lobule (pFWE < 0.05). Significant correlations were noted between the altered ALFF in the four brain regions and cognitive assessment (p < 0.05). Moreover, patients with psoriasis had increased FC between the four brain regions with altered ALFF (seeds) and the left prefrontal gyrus, the left anterior cingulate gyrus, left superior parietal lobule and default mode network (DMN) regions such as the right precuneus gyrus, left inferior parietal lobule, right angular gyrus and bilateral inferior temporal gyrus (pFWE < 0.05). CONCLUSIONS: Patients with psoriasis had altered brain activity and connectivity in the key brain areas within the DMN-prefrontal circuit. These brain changes may be the underlying neural correlates for cognitive functioning in patients with psoriasis.

Association of white matter microstructural alteration with non-suicidal self-injury behavior and visual working memory in adolescents with borderline personality disorder.

BACKGROUND: Non-suicidal self-injurious behavior (NSSI) is the core characteristic of adolescent borderline personality disorder (BPD) and visual working memory is involved in the pathological processes of BPD. This study aimed to investigate alterations in white matter microstructure and their association with NSSI and visual working memory in adolescents with BPD. METHODS: 53 adolescents diagnosed with BPD and 39 healthy controls (HCs) were enrolled. White matter microstructure was assessed with the fractional anisotropy (FA) and mean diffusivity (MD) from diffusion tensor imaging (DTI). Correlation analysis was performed to assess the association between FA/MD and core features of BPD. A mediation analysis was performed to test whether the effects of white matter alterations on NSSI could be mediated by visual working memory. RESULTS: Adolescents with BPD showed a reduced FA and an increased MD in the cortical-limbic and cortical-thalamus circuit when compared to the HCs (p < 0.05). Increased MD was positively correlated with NSSI, impulse control and identity disturbance (p < 0.05), and was negatively correlated with the score of visual reproduction. Reserved visual working memory masked the effects of white matter microstructural alterations on NSSI behavior. CONCLUSIONS: White matter microstructural deficits in the cortical-limbic and cortical-thalamus circuits may be associated with NSSI and visual working memory in adolescents with BPD. Reserved visual working memory may protect against NSSI.

Ensemble Machine Learning Model Incorporating Radiomics and Body Composition for Predicting Intraoperative HDI in PPGL.

CONTEXT: Intraoperative hemodynamic instability (HDI) can lead to cardiovascular and cerebrovascular complications during surgery for pheochromocytoma/paraganglioma (PPGL). OBJECTIVES: We aimed to assess the risk of intraoperative HDI in patients with PPGL to improve surgical outcome. METHODS: A total of 199 consecutive patients with PPGL confirmed by surgical pathology were retrospectively included in this study. This cohort was separated into 2 groups according to intraoperative systolic blood pressure, the HDI group (n = 101) and the hemodynamic stability (HDS) group (n = 98). It was also divided into 2 subcohorts for predictive modeling: the training cohort (n = 140) and the validation cohort (n = 59). Prediction models were developed with both the ensemble machine learning method (EL model) and the multivariate logistic regression model using body composition parameters on computed tomography, tumor radiomics, and clinical data. The efficiency of the models was evaluated with discrimination, calibration, and decision curves. RESULTS: The EL model showed good discrimination between the HDI group and HDS group, with an area under the curve of (AUC) of 96.2% (95% CI, 93.5%-99.0%) in the training cohort, and an AUC of 93.7% (95% CI, 88.0%-99.4%) in the validation cohort. The AUC values from the EL model were significantly higher than the logistic regression model, which had an AUC of 74.4% (95% CI, 66.1%-82.6%) in the training cohort and an AUC of 74.2% (95% CI, 61.1%-87.3%) in the validation cohort. Favorable calibration performance and clinical applicability of the EL model were observed. CONCLUSION: The EL model combining preoperative computed tomography-based body composition, tumor radiomics, and clinical data could potentially help predict intraoperative HDI in patients with PPGL.

Brain white matter microstructural changes in chemotherapy-treated older long-term breast cancer survivors.

PURPOSE: To assess white matter microstructural changes in older long-term breast cancer survivors 5-15 years post-chemotherapy treatment. METHODS: Breast cancer survivors aged 65 years or older who underwent chemotherapy (C+) and who did not undergo chemotherapy (C-) and age- and sex-matched healthy controls (HC) were enrolled at time point 1 (TP1) and followed for 2 years for time point 2 (TP2). All participants underwent brain MRI with diffusion tensor images and neuropsychological (NP) testing with the NIH Toolbox Cognition Battery. Tract-based spatial statistics (TBSS) analysis was performed on the diffusion tensor images to assess white matter microstructural changes with the fractional anisotropy (FA) parameter. RESULTS: There were significant longitudinal alterations in FA within the C+ group over time. The C+ group showed diminished FA in the body and genu of corpus callosum, anterior corona radiate, and external capsule on both the whole brain and region of interest (ROI) based analyses after p < 0.05 family-wise error (FWE) correction. However, there were no significant group differences between the groups at TP1. Additionally, at TP1, a positive correlation (R = 0.58, p = 0.04) was observed between the FA value of the anterior corona radiata and the crystallized composite score in the C+ group. CONCLUSIONS: Brain white matter microstructural alterations may be the underlying neural correlates of cognitive changes in older breast cancer survivors who had chemotherapy treatment years ago.