Postoperative delirium is associated with grey matter brain volume loss.

Delirium is associated with long-term cognitive dysfunction and with increased brain atrophy. However, it is unclear whether these problems result from or predisposes to delirium. We aimed to investigate preoperative to postoperative brain changes, as well as the role of delirium in these changes over time. We investigated the effects of surgery and postoperative delirium with brain MRIs made before and 3 months after major elective surgery in 299 elderly patients, and an MRI with a 3 months follow-up MRI in 48 non-surgical control participants. To study the effects of surgery and delirium, we compared brain volumes, white matter hyperintensities and brain infarcts between baseline and follow-up MRIs, using multiple regression analyses adjusting for possible confounders. Within the patients group, 37 persons (12%) developed postoperative delirium. Surgical patients showed a greater decrease in grey matter volume than non-surgical control participants [linear regression: B (95% confidence interval) = -0.65% of intracranial volume (-1.01 to -0.29, P < 0.005)]. Within the surgery group, delirium was associated with a greater decrease in grey matter volume [B (95% confidence interval): -0.44% of intracranial volume (-0.82 to -0.06, P = 0.02)]. Furthermore, within the patients, delirium was associated with a non-significantly increased risk of a new postoperative brain infarct [logistic regression: odds ratio (95% confidence interval): 2.8 (0.7-11.1), P = 0.14]. Our study was the first to investigate the association between delirium and preoperative to postoperative brain volume changes, suggesting that delirium is associated with increased progression of grey matter volume loss.

Conventional MRI Criteria to Differentiate Progressive Disease From Treatment-Induced Effects in High-Grade (WHO Grade 3-4) Gliomas.

BACKGROUND AND OBJECTIVES: Posttreatment radiologic deterioration of an irradiated high-grade (WHO grade 3-4) glioma (HGG) may be the result of true progressive disease or treatment-induced effects (TIE). Differentiation between these entities is of great importance but remains a diagnostic challenge. This study assesses the diagnostic value of conventional MRI characteristics to differentiate progressive disease from TIE in HGGs. METHODS: In this single-center, retrospective, consecutive cohort study, we included adults with a HGG who were treated with (chemo-)radiotherapy and subsequently developed a new or increasing contrast-enhancing lesion on conventional follow-up MRI. TIE and progressive disease were defined radiologically as stable/decreased for ≥6 weeks or Response Assessment in Neuro-Oncology progression and histologically as TIE without viable tumor or progressive disease. Two neuroradiologists assessed 21 preselected MRI characteristics of the progressive lesions. The statistical analysis included logistic regression to develop a full multivariable model, a diagnostic model with model reduction, and a Cohen kappa interrater reliability (IRR) coefficient. RESULTS: A total of 210 patients (median age 61 years, interquartile range 54-68, 189 male) with 284 lesions were included, of whom 141 (50%) had progressive disease. Median time to progressive disease was 2 (0.7-6.1) and to TIE 0.9 (0.7-3.5) months after radiotherapy. After multivariable modeling and model reduction, the following determinants prevailed: radiation dose (odds ratio [OR] 0.68, 95% CI 0.49-0.93), longer time to progression (TTP; OR 3.56, 95% CI 1.84-6.88), marginal enhancement (OR 2.04, 95% CI 1.09-3.83), soap bubble enhancement (OR 2.63, 95% CI 1.39-4.98), and isointense apparent diffusion coefficient (ADC) signal (OR 2.11, 95% CI 1.05-4.24). ORs >1 indicate higher odds of progressive disease. The Hosmer & Lemeshow test showed good calibration (p = 0.947) and the area under the receiver operating characteristic curve was 0.722 (95% CI 0.66-0.78). In the glioblastoma subgroup, TTP, marginal enhancement, and ADC signal were significant. IRR analysis between neuroradiologists revealed moderate to near perfect agreement for the predictive items but poor agreement for others. DISCUSSION: Several characteristics from conventional MRI are significant predictors for the discrimination between progressive disease and TIE. However, IRR was variable. Conventional MRI characteristics from this study should be incorporated into a multimodal diagnostic model with advanced imaging techniques. CLASSIFICATION OF EVIDENCE: This study provides Class II evidence that in patients with irradiated HGGs, radiation dose, longer TTP, marginal enhancement, soap bubble enhancement, and isointense ADC signal distinguish progressive disease from TIE.