Stacked in-plane histology for quantitative validation of non-invasive imaging biomarkers: Application to an infiltrative brain tumour model.

BACKGROUND: While it is generally agreed that histopathology is the gold standard for assessing non-invasive imaging biomarkers, most validation has been by qualitative visual comparison. To date, the difficulties involved in accurately co-registering histology sections with imaging slices have prevented a voxel-by-voxel assessment of imaging modalities. By contrast with previous studies, which focus on improving the registration algorithms, we have taken the approach of improving the quality of the histological processing and analysis. NEW METHOD: To account for imaging slice orientation and thickness, multiple histology sections were cut in the MR imaging plane and averaged to produce stacked in-plane histology (SIH) maps. When combined with intensity sensitive staining this approach gives histopathology maps, which can be used as the gold standard to validate imaging biomarkers. RESULTS: We applied this pipeline to a patient-derived mouse model of glioblastoma multiforme (GBM). Increasing the number of stacked histology sections significantly increased SIH measured tumour volume. The SIH technique proposed here resulted in reduced variability of volume measurements and this allowed significant improvements in the quantitative volumetric assessment of multiple MRI modalities. Further, high quality registration enabled a voxel-wise comparison between MRI and histopathology maps. Previous approaches to the validation of imaging biomarkers with histology, have been either qualitative or of limited accuracy. Here we propose a pipeline that allows for a more accurate validation via co-registration with SIH maps, potentially allowing validation in a voxel-wise mode. CONCLUSION: This work demonstrates that methodically produced SIH maps facilitate the quantitative histopathologic assessment of imaging biomarkers.

Quantitative histopathologic assessment of perfusion MRI as a marker of glioblastoma cell infiltration in and beyond the peritumoral edema region.

BACKGROUND: Conventional MRI fails to detect regions of glioblastoma cell infiltration beyond the contrast-enhanced T1 solid tumor region, with infiltrating tumor cells often migrating along host blood vessels. PURPOSE: To quantitatively and qualitatively analyze the correlation between perfusion MRI signal and tumor cell density in order to assess whether local perfusion perturbation could provide a useful biomarker of glioblastoma cell infiltration. STUDY TYPE: Animal model. SUBJECTS: Mice bearing orthotopic glioblastoma xenografts generated from a patient-derived glioblastoma cell line. FIELD STRENGTH/SEQUENCES: 7T perfusion images acquired using a high signal-to-noise ratio (SNR) multiple boli arterial spin labeling sequence were compared with conventional MRI (T1 /T2 weighted, contrast-enhanced T1 , diffusion-weighted, and apparent diffusion coefficient). ASSESSMENT: Immunohistochemistry sections were stained for human leukocyte antigen (probing human-derived tumor cells). To achieve quantitative MRI-tissue comparison, multiple histological slices cut in the MRI plane were stacked to produce tumor cell density maps acting as a "ground truth." STATISTICAL TESTS: Sensitivity, specificity, accuracy, and Dice similarity indices were calculated and a two-tailed, paired t-test used for statistical analysis. RESULTS: High comparison test results (Dice 0.62-0.72, Accuracy 0.86-0.88, Sensitivity 0.51-0.7, and Specificity 0.92-0.97) indicate a good segmentation for all imaging modalities and highlight the quality of the MRI tissue assessment protocol. Perfusion imaging exhibits higher sensitivity (0.7) than conventional MRI (0.51-0.61). MRI/histology voxel-to-voxel comparison revealed a negative correlation between tumor cell infiltration and perfusion at the tumor margins (P = 0.0004). DATA CONCLUSION: These results demonstrate the ability of perfusion imaging to probe regions of low tumor cell infiltration while confirming the sensitivity limitations of conventional imaging modalities. The quantitative relationship between tumor cell density and perfusion identified in and beyond the edematous T2 hyperintensity region surrounding macroscopic tumor could be used to detect marginal tumor cell infiltration with greater accuracy. LEVEL OF EVIDENCE: 1 Technical stage: 2 J. Magn. Reson. Imaging 2019;50:529-540.

Gastrooesophageal reflux disease in preterm infants: current management and diagnostic dilemmas.

Gastrooesophageal reflux disease (GORD) provides a diagnostic and therapeutic challenge to many neonatologists. Reflux of gastric contents is common in preterm infants but usually not pathological. GORD is frequently diagnosed despite the lack of a fully identified clinical syndrome and of a truly valid diagnostic test. Treatment modalities, for which there is little convincing evidence regarding efficacy, are commonly instigated for troublesome symptoms attributed to GORD. Diagnosis is so problematic in preterm infants that GORD is starting to be described as the clinical syndrome that responds to anti-reflux treatment. We discuss the dilemmas facing us when dealing with this condition, summarise the best available evidence regarding diagnosis and management, and use it to inform a suggested treatment pathway. We introduce the concept of a clinical scoring system to aid the diagnosis and monitoring of GORD in preterm infants and highlight areas where further research would be beneficial.