Optimization of deep learning methods for visualization of tumor heterogeneity and brain tumor grading through digital pathology

Background: Variations in prognosis and treatment options for gliomas are dependent on tumor grading. When tissue is available for analysis, grade is established based on histological criteria. However, histopathological diagnosis is not always reliable or straight-forward due to tumor heterogeneity, sampling error, and subjectivity, and hence there is great interobserver variability in readings. Methods: We trained convolutional neural network models to classify digital whole-slide histopathology images from The Cancer Genome Atlas. We tested a number of optimization parameters. Results: Data augmentation did not improve model training, while a smaller batch size helped to prevent overfitting and led to improved model performance. There was no significant difference in performance between a modular 2-class model and a single 3-class model system. The best models trained achieved a mean accuracy of 73% in classifying glioblastoma from other grades and 53% between WHO grade II and III gliomas. A visualization method was developed to convey the model output in a clinically relevant manner by overlaying color-coded predictions over the original whole-slide image. Conclusions: Our developed visualization method reflects the clinical decision-making process by highlighting the intratumor heterogeneity and may be used in a clinical setting to aid diagnosis. Explainable artificial intelligence techniques may allow further evaluation of the model and underline areas for improvements such as biases. Due to intratumor heterogeneity, data annotation for training was imprecise, and hence performance was lower than expected. The models may be further improved by employing advanced data augmentation strategies and using more precise semiautomatic or manually labeled training data

Stability and reproducibility of co-electrospun brain-mimicking phantoms for quality assurance of diffusion MRI sequences

Grey and white matter mimicking phantoms are important for assessing variations in diffusion MR measures at a single time point and over an extended period of time. This work investigates the stability of brain-mimicking microfibre phantoms and reproducibility of their MR derived diffusion parameters. The microfibres were produced by co-electrospinning and characterized by scanning electron microscopy (SEM). Grey matter and white matter phantoms were constructed from random and aligned microfibres, respectively. MR data were acquired from these phantoms over a period of 33 months. SEM images revealed that only small changes in fibre microstructure occurred over 30 months. The coefficient of variation in MR measurements across all time-points was between 1.6% and 3.4% for MD across all phantoms and FA in white matter phantoms. This was within the limits expected for intra-scanner variability, thereby confirming phantom stability over 33 months. These specialised diffusion phantoms may be used in a clinical environment for intra and inter-site quality assurance purposes, and for validation of quantitative diffusion biomarkers

A predictive model using the mesoscopic architecture of the living brain to detect Alzheimer’s disease

Background: Alzheimer’s disease, the most common cause of dementia, causes a progressive and irreversible deterioration of cognition that can sometimes be difficult to diagnose, leading to suboptimal patient care. Methods: We developed a predictive model that computes multi-regional statistical morpho-functional mesoscopic traits from T1-weighted MRI scans, with or without cognitive scores. For each patient, a biomarker called “Alzheimer’s Predictive Vector” (ApV) was derived using a two-stage least absolute shrinkage and selection operator (LASSO). Results: The ApV reliably discriminates between people with (ADrp) and without (nADrp) Alzheimer’s related pathologies (98% and 81% accuracy between ADrp - including the early form, mild cognitive impairment - and nADrp in internal and external hold-out test sets, respectively), without any a priori assumptions or need for neuroradiology reads. The new test is superior to standard hippocampal atrophy (26% accuracy) and cerebrospinal fluid beta amyloid measure (62% accuracy). A multiparametric analysis compared DTI-MRI derived fractional anisotropy, whose readout of neuronal loss agrees with ADrp phenotype, and SNPrs2075650 is significantly altered in patients with ADrp-like phenotype. Conclusions: This new data analytic method demonstrates potential for increasing accuracy of Alzheimer diagnosis

Bench to Bedside Development of [18F]Fluoromethyl-(1,2-2H4)choline ([18F]D4-FCH)

malignant transformation is characterised by aberrant phospholipid metabolism of cancers, associated with the upregulation of choline kinase alpha (CHK alpha). due to the metabolic instability of choline radiotracers and the increasing use of late-imaging protocols, we developed a more stable choline radiotracer, [F-18]fluoromethyl-[1,2-H-2(4)]choline ([F-18]D4-FCH). [F-18]D4-FCH has improved protection against choline oxidase, the key choline catabolic enzyme, via a H-1/D-2 isotope effect, together with fluorine substitution. Due to the promising mechanistic and safety profiles of [F-18]D4-FCH in vitro and preclinically, the radiotracer has transitioned to clinical development. [F-18]D4-FCH is a safe positron emission tomography (PET) tracer, with a favourable radiation dosimetry profile for clinical imaging. [F-18]D4-FCH PET/CT in lung and prostate cancers has shown highly heterogeneous intratumoral distribution and large lesion variability. treatment with abiraterone or enzalutamide in metastatic castrate-resistant prostate cancer patients elicited mixed responses on PET at 12-16 weeks despite predominantly stable radiological appearances. the sum of the weighted tumour-to-background ratios (TBRs-wsum) was associated with the duration of survival

Bench to Bedside Development of [18F]Fluoromethyl-(1,2-2H4)choline ([18F]D4-FCH)

Malignant transformation is characterised by aberrant phospholipid metabolism of cancers, associated with the upregulation of choline kinase alpha (CHKα). Due to the metabolic instability of choline radiotracers and the increasing use of late-imaging protocols, we developed a more stable choline radiotracer, [18F]fluoromethyl-[1,2-2H4]choline ([18F]D4-FCH). [18F]D4-FCH has improved protection against choline oxidase, the key choline catabolic enzyme, via a 1H/2D isotope effect, together with fluorine substitution. Due to the promising mechanistic and safety profiles of [18F]D4-FCH in vitro and preclinically, the radiotracer has transitioned to clinical development. [18F]D4-FCH is a safe positron emission tomography (PET) tracer, with a favourable radiation dosimetry profile for clinical imaging. [18F]D4-FCH PET/CT in lung and prostate cancers has shown highly heterogeneous intratumoral distribution and large lesion variability. Treatment with abiraterone or enzalutamide in metastatic castrate-resistant prostate cancer patients elicited mixed responses on PET at 12–16 weeks despite predominantly stable radiological appearances. The sum of the weighted tumour-to-background ratios (TBRs-wsum) was associated with the duration of survival

Steps on the Path to Clinical Translation: A workshop by the British and Irish Chapter of the ISMRM

The British and Irish Chapter of the International Society for Magnetic Resonance in Medicine (BIC-ISMRM) held a workshop entitled "Steps on the path to clinical translation" in Cardiff, UK, on 7th September 2022. The aim of the workshop was to promote discussion within the MR community about the problems and potential solutions for translating quantitative MR (qMR) imaging and spectroscopic biomarkers into clinical application and drug studies. Invited speakers presented the perspectives of radiologists, radiographers, clinical physicists, vendors, imaging Contract/Clinical Research Organizations (CROs), open science networks, metrologists, imaging networks, and those developing consensus methods. A round-table discussion was held in which workshop participants discussed a range of questions pertinent to clinical translation of qMR imaging and spectroscopic biomarkers. Each group summarized their findings via three main conclusions and three further questions. These questions were used as the basis of an online survey of the broader UK MR community

Steps on the Path to Clinical Translation: A workshop by the British and Irish Chapter of the ISMRM

The British and Irish Chapter of the International Society for Magnetic Resonance in Medicine (BIC‐ISMRM) held a workshop entitled “Steps on the path to clinical translation” in Cardiff, UK, on 7th September 2022. The aim of the workshop was to promote discussion within the MR community about the problems and potential solutions for translating quantitative MR (qMR) imaging and spectroscopic biomarkers into clinical application and drug studies. Invited speakers presented the perspectives of radiologists, radiographers, clinical physicists, vendors, imaging Contract/Clinical Research Organizations (CROs), open science networks, metrologists, imaging networks, and those developing consensus methods. A round‐table discussion was held in which workshop participants discussed a range of questions pertinent to clinical translation of qMR imaging and spectroscopic biomarkers. Each group summarized their findings via three main conclusions and three further questions. These questions were used as the basis of an online survey of the broader UK MR community

Imaging and Tissue Biomarkers of Choline Metabolism in Diffuse Adult Glioma: 18F-Fluoromethylcholine PET/CT, Magnetic Resonance Spectroscopy, and Choline Kinase α

The cellular and molecular basis of choline uptake on PET imaging and MRS-visible choline containing compounds is not well understood. Choline kinase alpha (ChoKa) is an enzyme that phosphorylates choline, an essential step in membrane synthesis. We investigate choline metabolism through 18F-fluoromethylcholine (18F-FMC) PET, MRS and tissue ChoKa in human glioma. 14 patients with suspected diffuse glioma underwent multimodal 3T MRI and dynamic 18F FMC PET/CT prior to surgery. Co-registered PET and MRI data were used to target biopsies to regions of high and low choline signal, and immunohistochemistry for ChoKa expression was performed. 18F-FMC/PET differentiated WHO grade IV from grade II and III tumours, whereas MRS differentiated grade III/IV from grade II tumours. Tumoural 18F-FMC/PET uptake was higher than in normal-appearing white matter across all grades and markedly elevated within regions of contrast enhancement. 18F-FMC/PET correlated weakly with MRS Cho ratios. ChoKa expression on IHC was negative or weak in all but one GBM sample, and did not correlate with tumour grade or imaging choline markers. MRS and 18F-FMC/PET provide complimentary information on glioma choline metabolism. Tracer uptake is, however, potentially confounded by blood-brain barrier permeability. ChoKa overexpression does not appear to be a common feature in diffuse glioma