Brain Microstructural Changes Associated With Neurocognitive Outcome in Intracranial Germ Cell Tumor Survivors.

BACKGROUND: Childhood intracranial germ cell tumor (GCT) survivors are prone to radiotherapy-related neurotoxicity, which can lead to neurocognitive dysfunctions. Diffusion kurtosis imaging (DKI) is a diffusion MRI technique that is sensitive to brain microstructural changes. This study aimed to investigate the association between DKI metrics versus cognitive and functional outcomes of childhood intracranial GCT survivors. METHODS: DKI was performed on childhood intracranial GCT survivors (n = 20) who had received cranial radiotherapy, and age and gender-matched healthy control subjects (n = 14). Neurocognitive assessment was performed using the Hong Kong Wechsler Intelligence Scales, and functional assessment was performed using the Lansky/Karnofsky performance scales (KPS). Survivors and healthy controls were compared using mixed effects model. Multiple regression analyses were performed to determine the effects of microstructural brain changes of the whole brain as well as the association between IQ and Karnofsky scores and the thereof. RESULTS: The mean Intelligence Quotient (IQ) of GCT survivors was 91.7 (95% CI 84.5 - 98.8), which was below the age-specific normative expected mean IQ (P = 0.013). The mean KPS score of GCT survivors was 85.5, which was significantly lower than that of controls (P < 0.001). Cognitive impairments were significantly associated with the presence of microstructural changes in white and grey matter, whereas functional impairments were mostly associated with microstructural changes in white matter. There were significant correlations between IQ versus the mean diffusivity (MD) and mean kurtosis (MK) of specific white matter regions. The IQ scores were negatively correlated with the MD of extensive grey matter regions. CONCLUSION: Our study identified vulnerable brain regions whose microstructural changes in white and grey matter were significantly associated with impaired cognitive and physical functioning in survivors of pediatric intracranial GCT.

Clinical utility of serial analysis of circulating tumour cells for detection of minimal residual disease of metastatic nasopharyngeal carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) is an important cancer in Hong Kong. We aim to utilise liquid biopsies for serial monitoring of disseminated NPC in patients to compare with PET-CT imaging in detection of minimal residual disease. METHOD: Prospective serial monitoring of liquid biopsies was performed for 21 metastatic patients. Circulating tumour cell (CTC) enrichment and characterisation was performed using a sized-based microfluidics CTC chip, enumerating by immunofluorescence staining, and using target-capture sequencing to determine blood mutation load. PET-CT scans were used to monitor NPC patients throughout their treatment according to EORTC guidelines. RESULTS: The longitudinal molecular analysis of CTCs by enumeration or NGS mutational profiling findings provide supplementary information to the plasma EBV assay for disease progression for good responders. Strikingly, post-treatment CTC findings detected positive findings in 75% (6/8) of metastatic NPC patients showing complete response by imaging, thereby demonstrating more sensitive CTC detection of minimal residual disease. Positive baseline, post-treatment CTC, and longitudinal change of CTCs significantly associated with poorer progression-free survival by the Kaplan-Meier analysis. CONCLUSIONS: We show the potential usefulness of application of serial analysis in metastatic NPC of liquid biopsy CTCs, as a novel more sensitive biomarker for minimal residual disease, when compared with imaging.

Development of fast deep learning quantification for magnetic resonance fingerprinting in vivo.

PURPOSE: A deep neural network was developed for magnetic resonance fingerprinting (MRF) quantification. This study aimed at extending previous studies of deep learning MRF to in vivo applications, allowing sub-second computation time for large-scale data. METHODS: We applied the deep learning methodology based on our previously published multi-layer perceptron. The number of layers was four, which was optimized to balance the model capacity and noise robustness. The training sets were obtained from MRF dictionaries with 9000 to 28,000 atoms, depending on the desired T1 and T2 ranges. The simulated MRF undersampling artifact based on the k-space acquisition scheme and noise were both added to the training data to reduce the error in estimates. RESULTS: The neural network achieved high fidelity (R2 _ 0.98) as compared to the T1 and T2 values of the ISMRM standardized phantom. In brain MRF experiment, the model trained with simulated artifacts and noise showed less error compared to that without. The in vivo application of our neural network for liver and prostate were also demonstrated. For an MRF slice with 256 _ 256 image resolution, the computation time of our neural network was 0.12 s, compared with the _ 28 s-pre-slice for the conventional dictionary matching method. CONCLUSION: Our neural network achieved fast computation speed for MRF quantification. The model trained with simulated artifacts and noise showed less error and achieved optimal performance for phantom experiment and in vivo normal brain and liver, and prostate cancer patient.

Intravoxel incoherent motion MRI assessment of chemoradiation-induced pelvic bone marrow changes in cervical cancer and correlation with hematological toxicity.

PURPOSE: To investigate bone marrow changes after chemoradiation (CRT) using intravoxel incoherent motion magnetic resonance imaging (IVIM-MRI) and correlate imaging changes with hematological toxicity (HT) in patients with locally advanced cervical cancer. MATERIALS AND METHODS: Thirty-nine patients with newly diagnosed cervical cancer were prospectively recruited for two sequential 3.0T IVIM-MRI studies: before treatment (MRI-1) and 3-4 weeks after standardized CRT (MRI-2). The irradiated pelvic bone marrow was outlined as the regions of interest to derive the true diffusion coefficient (D) and perfusion fraction (f) based on a biexponential model. The apparent coefficient diffusion (ADC) was derived using the monoexponential model. Changes in these parameters between MRI-1 and MRI-2 were calculated as ΔD, Δf, and ΔADC. HT was defined accordingly to NCI-CTCAE (v. 4.03) of grade 3 and above. Statistical analysis was performed using Mann-Whitney U-test. RESULTS: The median age of patients was 54 years old (range 27-83 years old); 14 patients suffered from HT. Early bone marrow changes (3-4 weeks) of ΔD showed a significant difference between HT and non-HT groups (6.4 ± 19.7% vs. -6.4 ± 19.4%, respectively, P = 0.041). However, no significant changes were noted in Δf (3.7 ± 13.3% vs. 1.5 ± 12.5% respectively, P = 0. 592) and ΔADC (5.5 ± 26.3% vs. -3.3 ± 27.0% respectively, P = 0.303) between the HT and non-HT groups. Δf increased insignificantly for both groups. CONCLUSION: ΔD was the only significant parameter to differentiate early cellular environment changes in bone marrow after CRT, suggestive that ΔD was more sensitive than Δf and ΔADC to reflect the underlying microenvironment injury. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1491-1498.