Decoding the best automated segmentation tools for vascular white matter hyperintensities in the aging brain: a clinician's guide to precision and purpose.

White matter hyperintensities of vascular origin (WMH) are commonly found in individuals over 60 and increase in prevalence with age. The significance of WMH is well-documented, with strong associations with cognitive impairment, risk of stroke, mental health, and brain structure deterioration. Consequently, careful monitoring is crucial for the early identification and management of individuals at risk. Luckily, WMH are detectable and quantifiable on standard MRI through visual assessment scales, but it is time-consuming and has high rater variability. Addressing this issue, the main aim of our study is to decipher the utility of quantitative measures of WMH, assessed with automatic tools, in establishing risk profiles for cerebrovascular deterioration. For this purpose, first, we work to determine the most precise WMH segmentation open access tool compared to clinician manual segmentations (LST-LPA, LST-LGA, SAMSEG, and BIANCA), offering insights into methodology and usability to balance clinical precision with practical application. The results indicated that supervised algorithms (LST-LPA and BIANCA) were superior, particularly in detecting small WMH, and can improve their consistency when used in parallel with unsupervised tools (LST-LGA and SAMSEG). Additionally, to investigate the behavior and real clinical utility of these tools, we tested them in a real-world scenario (N = 300; age > 50 y.o. and MMSE > 26), proposing an imaging biomarker for moderate vascular damage. The results confirmed its capacity to effectively identify individuals at risk comparing the cognitive and brain structural profiles of cognitively healthy adults above and below the resulted threshold.

Decoding the Best Automated Segmentation Tools for Vascular White Matter Hyperintensities in the Aging Brain: A Clinician's Guide to Precision and Purpose.

Cerebrovascular damage from small vessel disease (SVD) occurs in healthy and pathological aging. SVD markers, such as white matter hyperintensities (WMH), are commonly found in individuals over 60 and increase in prevalence with age. WMHs are detectable on standard MRI by adhering to the STRIVE criteria. Currently, visual assessment scales are used in clinical and research scenarios but is time-consuming and has rater variability, limiting its practicality. Addressing this issue, our study aimed to determine the most precise WMH segmentation software, offering insights into methodology and usability to balance clinical precision with practical application. This study employed a dataset comprising T1, FLAIR, and DWI images from 300 cognitively healthy older adults. WMHs in this cohort were evaluated using four automated neuroimaging tools: Lesion Prediction Algorithm (LPA) and Lesion Growth Algorithm (LGA) from Lesion Segmentation Tool (LST), Sequence Adaptive Multimodal Segmentation (SAMSEG), and Brain Intensity Abnormalities Classification Algorithm (BIANCA). Additionally, clinicians manually segmented WMHs in a subsample of 45 participants to establish a gold standard. The study assessed correlations with the Fazekas scale, algorithm performance, and the influence of WMH volume on reliability. Results indicated that supervised algorithms were superior, particularly in detecting small WMHs, and can improve their consistency when used in parallel with unsupervised tools. The research also proposed a biomarker for moderate vascular damage, derived from the top 95th percentile of WMH volume in healthy individuals aged 50 to 60. This biomarker effectively differentiated subgroups within the cohort, correlating with variations in brain structure and behavior.

Coronary microvascular dysfunction is associated with impaired cognitive function: the Cerebral-Coronary Connection study (C3 study).

BACKGROUND: It remains unknown whether the presence of coronary microcirculatory dysfunction (CMD) correlates with its equivalent condition in the brain, cerebral small vessel disease (CSVD). The cerebral-coronary connection (C3), a prospective blinded study, investigated the prevalence of CMD in patients with coronary artery disease (CAD) and its association with CSVD and cognitive function. METHODS AND RESULTS: Patients with documented CAD fulfilling inclusion criteria underwent physiological assessment of epicardial vessels and the microcirculation using intracoronary pressure and Doppler. Coronary microcirculation-related indices included coronary flow reserve (CFR) and hyperaemic microvascular resistance. Brain magnetic resonance imaging, transcranial Doppler (TCD), and neurocognitive examination were performed. Overall, 67 patients were included in the study (mean age 66 years, 73% female). Patients with abnormal CFR (<2.0) (55.2%) showed higher burden of white-matter hyperintensities: 43.2 vs. 20.0% (P = 0.044). After statistical adjustment, low CFR was associated with lower grey matter volume (P = 0.024) and with parameters of white-matter microstructural damage in diffusion-tensor imaging (lower fractional anisotropy and higher mean diffusivity, P = 0.029 and P = 0.032, respectively). Low CFR was associated with higher resistive (P = 0.027) and pulsatility (P = 0.043) values on TCD, and worse neurocognitive test scores (lower mini mental state examination, P = 0.025, and slower Trail Making Test A, P = 0.034). CONCLUSIONS: Coronary microcirculatory dysfunction is frequent in patients with CAD and correlates with CSVD, abnormal cerebral flow haemodynamics, and significant cognitive impairment. These findings support the hypothesis that microvascular dysfunction in the heart and the brain are part of a single pathological process affecting microcirculation in patients with CAD. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT04131075.

The relationship between retinal layers and brain areas in asymptomatic first-degree relatives of sporadic forms of Alzheimer's disease: an exploratory analysis.

BACKGROUND: Two main genetic risks for sporadic Alzheimer's disease (AD) are a family history and ɛ4 allele of apolipoprotein E. The brain and retina are part of the central nervous system and share pathophysiological mechanisms in AD. METHODS: We performed a cross-sectional study with 30 participants without a family history of sporadic AD (FH-) and noncarriers of ApoE ɛ4 (ApoE ɛ4-) as a control group and 34 participants with a family history of sporadic AD (FH+) and carriers of at least one ɛ4 allele (ApoE ɛ4+). We analyzed the correlations between macular volumes of retinal layers and thickness of the peripapillary retinal nerve fiber layer (pRNFL) measured by optical coherence tomography (OCT) with the brain area parameters measured by magnetic resonance imaging (MRI) in participants at high genetic risk of developing AD (FH+ ApoE ɛ4+). RESULTS: We observed a significant volume reduction in the FH+ ApoE ɛ4+ group compared with the control group in some macular areas of (i) macular RNFL (mRNFL), (ii) inner plexiform layer (IPL), (iii) inner nuclear layer (INL), and (iv) outer plexiform layer (OPL). Furthermore, in the FH+ ApoE ɛ4+ group, the retinal sectors that showed statistically significant volume decrease correlated with brain areas that are affected in the early stages of AD. In the same group, the peripapillary retinal nerve fiber layer (pRNFL) did not show statistically significant changes in thickness compared with the control group. However, correlations of these sectors with the brain areas involved in this disease were also found. CONCLUSIONS: In cognitively healthy participants at high genetic risk of developing sporadic forms of AD, there are significant correlations between retinal changes and brain areas closely related to AD such as the entorhinal cortex, the lingual gyrus, and the hippocampus.

Lesson of the month: Severe leukoencephalopathy by SARS-CoV-2.

Neurological manifestations associated with SARS-CoV-2 infection as well as its pathogenesis are insufficiently explained. We present two cases of severe COVID-19 who required hospitalisation in the intensive care unit with persistently depressed mental status and severe leukoencephalopathy. We discuss the clinical and radiological findings and also propose the possible pathogenesis involved.

Idiopathic stenosis of foramina of Monro in an asymptomatic adult patient: a rare entity radiologists should be aware of.

Bilateral Adult Idiopathic Oclussion of Foramen of Monro is a rare entity, with less than 22 cases published in the literature so far, all of them symptomatic.1 When the symptoms require it, the current first-line treatment is endoscopic foraminoplasty, sometimes associated with septum pellucidum fenestration, although some authors consider that a more conservative treatment in paucisymptomatic patients.2 We report the case of an idiopathic biventricular hydrocephalus found incidentally in an asymptomatic 42-year-old female with temporomandibular joint disfunction. The fact that some patients with Monro foraminal stenosis may be asymptomatic increases the possibility of underdiagnosis, so we consider it a condition that radiologists should be aware of, mainly taking into account the fact that the diagnosis of this entity is usually radiologic3 and the potential complications associated with treatment.

Diffusion Tensor Imaging Measures of Brain Connectivity for the Early Diagnosis of Alzheimer's Disease.

The prognostic capacity of the diffusion tensor imaging measures fractional anisotropy (FA) and mean diffusivity (MD) to detect mild cognitive impairment (MCI) progression to Alzheimer's disease (AD) was assessed in 135 MCI patients and 72 healthy subjects over a median follow-up of 40 months. Forty-nine MCI patients (36.3%) developed AD. The factors MD left hippocampus, FA left cingulate, and FA left hippocampus emerged as predictors of progression. Age (hazard ratio [HR] 1.21), delayed text recall (HR 0.89), FA left uncinate (HR 1.90), FA left hippocampus (HR 2.21), and carrying at least one ApoE4 allele (HR 2.86) were associated with a high conversion rate. FA measures revealed the greatest discriminative capacity (Harrell's C = 0.73 versus 0.65 without FA; p = 0.034). The inclusion of FA structural connectivity data in our model improved discrimination between subjects with MCI progressing or not to dementia.

Predictive value of PET-CT for pathological response in stages II and III breast cancer patients following neoadjuvant chemotherapy with docetaxel / Valor predictivo de la PET-TC en la respuesta a la quimioterapia neoadyuvante en el cáncer de mama en estadios II y III

Purpose. To prospectively study the value of PET-CT with fluorine-18 fluorodeoxyglucose (FDG) to predict neoadjuvant chemotherapy (NAC) response of locoregional disease of stages II and III breast cancer patients. Material and methods. A written informed consent and approval were obtained from the Ethics Committee. PET-CT accuracy in the prediction of pathologic complete response (pCR) after NAC was studied in primary tumors and lymph node metastasis in 43 women (mean age: 50 years: range: 27-71 years) with histologically proven breast cancer between December 2009 and January 2011. PET-CT was performed at baseline and after NAC. SUVmax percentage changes (ΔSUVmax) were compared with pathology findings at surgery. Receiver-operator characteristic (ROC) analysis was used to discriminate between locoregional pCR and non-pCR. In patients not achieving pCR, it was investigated if ΔSUVmax could accurately identify the residual cancer burden (RCB) classes: RCB-I (minimal residual disease (MRD)), RCB-II (moderate RD), and RCB-III (extensive RD). Results. pCR was obtained in 11 patients (25.6%). Residual disease was found in 32 patients (74.4%): 16 (37.2%) RCB-I, 15 (35.6%) RCB-II and 2 (4.7%) RCB-III. Sensitivity, specificity, and accuracy to predict pCR were 90.9%, 90.6%, and 90.7%, respectively. Specificity was 94.1% in the identification of a subset of patients who had either pCR or MRD. Conclusion. Accuracy of ΔSUVmax in the locoregional disease of stages II and III breast cancer patients after NAC is high for the identification of pCR cases. Its specificity is potentially sufficient to identify a subgroup of patients who could be managed with conservative surgery (AU)

Objetivo. Estudiar de forma prospectiva el valor de la PET-TC con fluor-18-desoxiglucosa (FDG) para predecir la respuesta a la quimioterapia neoadyuvante (NAC) de la enfermedad locoregional en pacientes con cáncer de mama en estadios II y III.Material y métodos. Se obtuvo un consentimiento informado por escrito y la aprobación del Comité Ético. Se estudió la precisión de la PET-TC para predecir la respuesta completa patológica (pCR) tras la NAC en los tumores y en los ganglios de 43 mujeres (edad media: 50 años; rango: 27-71 años) que presentaban cáncer de mama diagnosticado por histología entre diciembre del 2009 y Enero del 2011. Los estudios PET-TC se realizaron al diagnóstico y tras la NAC. Los cambios en el porcentaje del SUVmax (delta-SUVmax) se compararon con los hallazgos de la anatomía patológica de la pieza quirúrgica. Se realizaron análisis de Característica Operativa del Receptor (ROC) para discriminar entre pCR y no-pCR en la enfermedad locoregional. En las pacientes que no alcanzaron la pCR, se investigó si el delta-SUVmax podía identificar de forma precisa las siguientes categorías de carga tumoral residual: RCB-I (enfermedad mínima residual (MRD)), RCB-II (moderada RD), y RCB-III (extensa RD).Resultados. Se obtuvo pCR en 11 pacientes (25,6%). Se encontró enfermedad residual en 32 pacientes (74,4%): 16 (37,2%) RCB-I, 15 (35,6%) RCB-II y 2 (4,7%) RCB-III. La sensibilidad, especificidad y precisión para predecir la pCR fueron 90,9%, 90,6%, y 90,7%, respectivamente. En la identificación del subgrupo de pacientes con pCR o MRD la especificidad fue del 94,1%.Conclusión. El delta-SUVmax identifica con elevada precisión la pCR en la enfermedad locoregional de las pacientes con cáncer de mama en estadios II y III tras la NAC. La especificidad es potencialmente suficiente para identificar un subgrupo de pacientes que podrían ser candidatas a cirugía conservadora (AU)

Predictive value of PET-CT for pathological response in stages II and III breast cancer patients following neoadjuvant chemotherapy with docetaxel.

PURPOSE: To prospectively study the value of PET-CT with fluorine-18 fluorodeoxyglucose (FDG) to predict neoadjuvant chemotherapy (NAC) response of locoregional disease of stages II and III breast cancer patients. MATERIAL AND METHODS: A written informed consent and approval were obtained from the Ethics Committee. PET-CT accuracy in the prediction of pathologic complete response (pCR) after NAC was studied in primary tumors and lymph node metastasis in 43 women (mean age: 50 years: range: 27-71 years) with histologically proven breast cancer between December 2009 and January 2011. PET-CT was performed at baseline and after NAC. SUV(max) percentage changes (ΔSUV(max)) were compared with pathology findings at surgery. Receiver-operator characteristic (ROC) analysis was used to discriminate between locoregional pCR and non-pCR. In patients not achieving pCR, it was investigated if ΔSUV(max) could accurately identify the residual cancer burden (RCB) classes: RCB-I (minimal residual disease (MRD)), RCB-II (moderate RD), and RCB-III (extensive RD). RESULTS: pCR was obtained in 11 patients (25.6%). Residual disease was found in 32 patients (74.4%): 16 (37.2%) RCB-I, 15 (35.6%) RCB-II and 2 (4.7%) RCB-III. Sensitivity, specificity, and accuracy to predict pCR were 90.9%, 90.6%, and 90.7%, respectively. Specificity was 94.1% in the identification of a subset of patients who had either pCR or MRD. CONCLUSION: Accuracy of ΔSUV(max) in the locoregional disease of stages II and III breast cancer patients after NAC is high for the identification of pCR cases. Its specificity is potentially sufficient to identify a subgroup of patients who could be managed with conservative surgery.