Acetazolamide-augmented BOLD MRI to Assess Whole-Brain Cerebrovascular Reactivity in Chronic Steno-occlusive Disease Using Principal Component Analysis.

Background Exhaustion of cerebrovascular reactivity (CVR) portends increased stroke risk. Acetazolamide-augmented blood oxygenation level-dependent (BOLD) MRI has been used to estimate CVR, but low signal-to-noise conditions relegate its use to terminal CVR (CVRend) measurements that neglect dynamic features of CVR. Purpose To demonstrate comprehensive characterization of acetazolamide-augmented BOLD MRI response in chronic steno-occlusive disease using a computational framework to precondition signal time courses for dynamic whole-brain CVR analysis. Materials and Methods This study focused on retrospective analysis of consecutive patients with unilateral chronic steno-occlusive disease who underwent acetazolamide-augmented BOLD imaging for recurrent minor stroke or transient ischemic attack at an academic medical center between May 2017 and October 2020. A custom principal component analysis-based denoising pipeline was used to correct spatially varying non-signal-bearing contributions obtained by a local principal component analysis of the MRI time series. Standard voxelwise CVRend maps representing terminal responses were produced and compared with maximal CVR (CVRmax) as isolated from binned (per-repetition time) denoised BOLD time course. A linear mixed-effects model was used to compare CVRmax and CVRend in healthy and diseased hemispheres. Results A total of 23 patients (median age, 51 years; IQR, 42-61, 13 men) who underwent 32 BOLD examinations were included. Processed MRI data showed twofold improvement in signal-to-noise ratio, allowing improved isolation of dynamic characteristics in signal time course for sliding window CVRmax analysis to the level of each BOLD repetition time (approximately 2 seconds). Mean CVRmax was significantly higher than mean CVRend in diseased (5.2% vs 3.8%, P < .01) and healthy (5.5% vs 4.0%, P < .01) hemispheres. Several distinct time-signal signatures were observed, including nonresponsive; delayed/blunted; brisk; and occasionally nonmonotonic time courses with paradoxical features in normal and abnormal tissues (ie, steal and reverse-steal patterns). Conclusion A principal component analysis-based computational framework for analysis of acetazolamide-augmented BOLD imaging can be used to measure unsustained CVRmax through twofold improvements in signal-to-noise ratio. © RSNA, 2023 Supplemental material is available for this article.

Diaschisis Profiles in the Cerebellar Response to Hemodynamic Stimuli: Insights From Dynamic Measurement of Cerebrovascular Reactivity to Identify Occult and Transient Maxima.

BACKGROUND: Crossed cerebellar diaschisis (CCD) refers to depressions in perfusion and metabolism within the cerebellar hemisphere contralateral to supratentorial disease. Prior investigation into CCD in cerebrovascular reactivity (CVR) has been limited to terminal CVR estimations (CVRend ). We recently have demonstrated the presence of unsustained CVR maxima (CVRmax ) using dynamic CVR analysis, offering a fully dynamic characterization of CVR to hemodynamic stimuli. PURPOSE: To investigate CCD in CVRmax from dynamic blood oxygen level-dependent (BOLD) MRI, by comparison with conventional CVRend estimation. STUDY TYPE: Retrospective. POPULATION: A total of 23 patients (median age: 51 years, 10 females) with unilateral chronic steno-occlusive cerebrovascular disease, without prior knowledge of CCD status. FIELD STRENGTH/SEQUENCE: A 3-T, T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) and acetazolamide-augmented BOLD imaging performed with a gradient-echo echo-planar imaging (EPI) sequence. ASSESSMENT: A custom denoising pipeline was used to generate BOLD-CVR time signals. CVRend was established using the last minute of the BOLD response relative to the first-minute baseline. Following classification of healthy versus diseased cerebral hemispheres, CVRmax and CVRend were calculated for bilateral cerebral and cerebellar hemispheres. Three independent observers evaluated all data for the presence of CCD. STATISTICAL TESTS: Pearson correlations for comparing CVR across hemispheres, two-proportion Z-tests for comparing CCD prevalence, and Wilcoxon signed-rank tests for comparing median CVR. The level of statistical significance was set at P ≤ 0.05. RESULTS: CCD-related changes were observed on both CVRend and CVRmax maps, with all CCD+ cases identifiable by inspection of either map. Diseased cerebral and contralateral cerebellar hemispheric CVR correlations in CCD+ patients were stronger when using CVRend (r = 0.728) as compared to CVRmax (r = 0.676). CVR correlations between healthy cerebral hemispheres and contralateral cerebellar hemispheres were stronger for CVRmax (r = 0.739) than for CVRend (r = 0.705). DATA CONCLUSION: CCD-related alterations could be observed in CVR examinations. Conventional CVRend may underestimate CVR and could exaggerate CCD. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 3.

Optofluidic real-time cell sorter for longitudinal CTC studies in mouse models of cancer.

Circulating tumor cells (CTCs) play a fundamental role in cancer progression. However, in mice, limited blood volume and the rarity of CTCs in the bloodstream preclude longitudinal, in-depth studies of these cells using existing liquid biopsy techniques. Here, we present an optofluidic system that continuously collects fluorescently labeled CTCs from a genetically engineered mouse model (GEMM) for several hours per day over multiple days or weeks. The system is based on a microfluidic cell sorting chip connected serially to an unanesthetized mouse via an implanted arteriovenous shunt. Pneumatically controlled microfluidic valves capture CTCs as they flow through the device, and CTC-depleted blood is returned back to the mouse via the shunt. To demonstrate the utility of our system, we profile CTCs isolated longitudinally from animals over 4 days of treatment with the BET inhibitor JQ1 using single-cell RNA sequencing (scRNA-Seq) and show that our approach eliminates potential biases driven by intermouse heterogeneity that can occur when CTCs are collected across different mice. The CTC isolation and sorting technology presented here provides a research tool to help reveal details of how CTCs evolve over time, allowing studies to credential changes in CTCs as biomarkers of drug response and facilitating future studies to understand the role of CTCs in metastasis.

Mutation and cell state compatibility is required and targetable in Ph+ acute lymphoblastic leukemia minimal residual disease.

Efforts to cure BCR::ABL1 B cell acute lymphoblastic leukemia (Ph+ ALL) solely through inhibition of ABL1 kinase activity have thus far been insufficient despite the availability of tyrosine kinase inhibitors (TKIs) with broad activity against resistance mutants. The mechanisms that drive persistence within minimal residual disease (MRD) remain poorly understood and therefore untargeted. Utilizing 13 patient-derived xenograft (PDX) models and clinical trial specimens of Ph+ ALL, we examined how genetic and transcriptional features co-evolve to drive progression during prolonged TKI response. Our work reveals a landscape of cooperative mutational and transcriptional escape mechanisms that differ from those causing resistance to first generation TKIs. By analyzing MRD during remission, we show that the same resistance mutation can either increase or decrease cellular fitness depending on transcriptional state. We further demonstrate that directly targeting transcriptional state-associated vulnerabilities at MRD can overcome BCR::ABL1 independence, suggesting a new paradigm for rationally eradicating MRD prior to relapse. Finally, we illustrate how cell mass measurements of leukemia cells can be used to rapidly monitor dominant transcriptional features of Ph+ ALL to help rationally guide therapeutic selection from low-input samples.

Linking single-cell measurements of mass, growth rate, and gene expression.

Mass and growth rate are highly integrative measures of cell physiology not discernable via genomic measurements. Here, we introduce a microfluidic platform enabling direct measurement of single-cell mass and growth rate upstream of highly multiplexed single-cell profiling such as single-cell RNA sequencing. We resolve transcriptional signatures associated with single-cell mass and growth rate in L1210 and FL5.12 cell lines and activated CD8+ T cells. Further, we demonstrate a framework using these linked measurements to characterize biophysical heterogeneity in a patient-derived glioblastoma cell line with and without drug treatment. Our results highlight the value of coupled phenotypic metrics in guiding single-cell genomics.