Manual and automated tissue segmentation confirm the impact of thalamus atrophy on cognition in multiple sclerosis: A multicenter study

Background and rationale: Thalamus atrophy has been linked to cognitive decline in multiple sclerosis (MS) using various segmentation methods. We investigated the consistency of the association between thalamus volume and cognition in MS for two common automated segmentation approaches, as well as fully manual outlining. Methods: Standardized neuropsychological assessment and 3-Tesla 3D-T1-weighted brain MRI were collected (multi-center) from 57 MS patients and 17 healthy controls. Thalamus segmentations were generated manually and using five automated methods. Agreement between the algorithms and manual outlines was assessed with Bland-Altman plots; linear regression assessed the presence of proportional bias. The effect of segmentation method on the separation of cognitively impaired (CI) and preserved (CP) patients was investigated through Generalized Estimating Equations; associations with cognitive measures were investigated using linear mixed models, for each method and vendor. Results: In smaller thalami, automated methods systematically overestimated volumes compared to manual segmentations [ρ=(-0.42)-(-0.76); p-values < 0.001). All methods significantly distinguished CI from CP MS patients, except manual outlines of the left thalamus (p = 0.23). Poorer global neuropsychological test performance was significantly associated with smaller thalamus volumes bilaterally using all methods. Vendor significantly affected the findings. Conclusion: Automated and manual thalamus segmentation consistently demonstrated an association between thalamus atrophy and cognitive impairment in MS. However, a proportional bias in smaller thalami and choice of MRI acquisition system might impact the effect size of these findings

Kappa free light chains is a valid tool in the diagnostics of MS : A large multicenter study

To validate kappa free light chain (KFLC) and lambda free light chain (LFLC) indices as a diagnostic biomarker in multiple sclerosis (MS). We performed a multicenter study including 745 patients from 18 centers (219 controls and 526 clinically isolated syndrome (CIS)/MS patients) with a known oligoclonal IgG band (OCB) status. KFLC and LFLC were measured in paired cerebrospinal fluid (CSF) and serum samples. Gaussian mixture modeling was used to define a cut-off for KFLC and LFLC indexes. The cut-off for the KFLC index was 6.6 (95% confidence interval (CI) = 5.2-138.1). The cut-off for the LFLC index was 6.9 (95% CI = 4.5-22.2). For CIS/MS patients, sensitivity of the KFLC index (0.88; 95% CI = 0.85-0.90) was higher than OCB (0.82; 95%CI = 0.79-0.85; p < 0.001), but specificity (0.83; 95% CI = 0.78-0.88) was lower (OCB = 0.92; 95% CI = 0.89-0.96; p < 0.001). Both sensitivity and specificity for the LFLC index were lower than OCB. Compared with OCB, the KFLC index is more sensitive but less specific for diagnosing CIS/MS. Lacking an elevated KFLC index is more powerful for excluding MS compared with OCB but the latter is more important for ruling in a diagnosis of CIS/MS

FAM19A4/miR124-2 methylation analysis as a triage test for HPV-positive women: cross-sectional and longitudinal data from a Dutch screening cohort

Objectives: The aim was to evaluate the cross-sectional and long-term triage performance of FAM19A4/miR124-2 methylation analysis in human papillomavirus (HPV)-based cervical screening. Methods: We conducted a post hoc analysis within a Dutch population-based HPV-positive study cohort of women aged 30–60 years (n = 979). Cross-sectional cervical intraepithelial neoplasia (CIN) 3+ sensitivity, specificity, positive predictive value and negative predictive value as well as cumulative CIN3+ or cervical cancer risks after 9 and 14 years were compared for three baseline triage strategies: (1) cytology, (2) FAM19A4/miR124-2 methylation analysis and (3) combined FAM19A4/miR124-2 methylation with cytology. Results: CIN3+ sensitivity of FAM19A4/miR124-2 methylation analysis was similar to that of cytology (71.3% vs 76.0%, ratio 0.94, 95% CI 0.84 to 1.05), at a lower specificity (78.3% vs 87.0%, ratio 0.90, 95% CI 0.86 to 0.94). Combining FAM19A4/miR124-2 methylation analysis with cytology resulted in a CIN3+ sensitivity of 84.6% (95% CI 78.3 to 90.8) at a specificity of 69.6% (95% CI 66.5 to 72.7). Similar 9- and 14-year CIN3+ risks for baseline cytology-negative women and baseline FAM19A4/miR124-2 methylation-negative women were observed, with risk differences of –0.42% (95% CI –2.1 to 1.4) and –0.07% (95% CI –1.9 to 1.9), respectively. The 14-year cumulative cervical cancer incidence was significantly lower for methylation-negative women compared to cytology-negative women (risk difference 0.98%, 95% CI 0.26 to 2.0). Discussion: FAM19A4/miR124-2 methylation analysis has a good triage performance on baseline screening samples, with a cross-sectional CIN3+ sensitivity and long-term triage-negative CIN3+ risk equalling cytology triage. Therefore, FAM19A4/miR124-2 methylation analysis appears to be a good and objective alternative to cytology in triage scenarios in HPV-based cervical screening

Sleep quality trajectories from head and neck cancer diagnosis to six months after treatment

Objectives: Patients with head and neck cancer (HNC) often report disturbances in their sleep quality, impairing their quality of life. This study aims to examine the trajectories of sleep quality from diagnosis up to 6-month after treatment, as well as the pre-treatment risk factors for poor sleep trajectories. Materials and Methods: Sleep quality (Pittsburgh sleep quality index) was measured shortly after diagnosis (pre-treatment), and at 3 and 6 months after finishing treatment. Patients were categorized into 5 trajectory groups. We examined the association of sleep quality trajectories with sociodemographic and clinical characteristics, coping style, HNC symptoms, and psychological distress. Results: Among 412 included patients, about a half either had a persistent good sleep (37.6%) or an improving (16.5%) trajectory. About a third had a persistent poor sleep (21.8%) or worsening (10.9%) sleep trajectory. The remaining patients (13.1%), alternated between good and poor sleep. Using persistent good sleep as a reference outcome, persistent poor sleepers were more likely to be woman (odds ratio [OR] = 1.98, 95% confidence interval [CI] 1.01–3.90), use painkillers prior to treatment (OR = 2.52, 95% CI 1.33–4.77), and have more pre-treatment anxiety symptoms (OR = 1.26, 95% CI 1.15–1.38). Conclusion: Unfavorable sleep quality trajectories are prevalent among HNC patients from pre-treatment to 6-month after treatment. A periodic sleep evaluation starting shortly after HNC diagnosis is necessary to identify persistent sleep problems, especially among high-risk group

Collateral grading systems in retrograde percutaneous coronary intervention of chronic total occlusions.

Background: The Japanese Channel (J-Channel) score was introduced to aid in retrograde percutaneous coronary intervention (PCI) of chronic total coronary occlusions (CTOs). The predictive value of the J-Channel score has not been compared with established collateral grading systems such as the Rentrop classification and Werner grade. Aims: To investigate the predictive value of the J-Channel score, Rentrop classification and Werner grade for successful collateral channel (CC) guidewire crossing and technical CTO PCI success. Methods: A total of 600 prospectively recruited patients underwent CTO PCI. All grading systems were assessed under dual catheter injection. CC guidewire crossing was considered successful if the guidewire reached the distal segment of the CTO vessel through a retrograde approach. Technical CTO PCI success was defined as thrombolysis in myocardial infarction flow grade 3 and residual stenosis &lt;30%. Results: Of 600 patients, 257 (43%) underwent CTO PCI through a retrograde approach. Successful CC guidewire crossing was achieved in 208 (81%) patients. The predictive value of the J-Channel score for CC guidewire crossing (area under curve 0.743) was comparable with the Rentrop classification (0.699, p = 0.094) and superior to the Werner grade (0.663, p = 0.002). Technical CTO PCI success was reported in 232 (90%) patients. The Rentrop classification exhibited a numerically higher discriminatory ability (0.676) compared to the J-Channel score (0.664) and Werner grade (0.589). Conclusions: The J-channel score might aid in strategic collateral channel selection during retrograde CTO PCI. However, the J-Channel score, Rentrop classification, and Werner grade have limited value in predicting technical CTO PCI success