Automated Textural Classification of Osteoarthritis Magnetic Resonance Images

Osteoarthritis (OA) is the most common cause of disability in the United Kingdom and United States. Identifying the rate of OA progression remains an important clinical and research challenge for early disease monitoring. Texture analysis of tibial subchondral bone using magnetic resonance imaging (MRI) has demonstrated the ability to discriminate between different stages of OA. This work combines texture analysis with machine learning methods (Lasso, Decision Tree, and Neural Network) to predict radiographic disease progression over 3 years, trained using data from the Osteoarthritis Initiative. We achieved high sensitivity (86%), specificity (64%) and accuracy (74%) for predictions of OA progression.The authors acknowledge research support from the National Institute of Health Research Cambridge Biomedical Research Centre. RT acknowledges the support of the UK Engineering and Physical Sciences Research Council (EPSRC) grant EP/L016516/1 for the University of Cambridge Centre for Doctoral Training, the Cambridge Centre for Analysis. JK and JM acknowledge support by GlaxoSmithKline. AM acknowledges research support from Arthritis Research UK; Tissue Engineering Centre award. FG acknowledges research support from Cancer Research UK

Do gadolinium-based contrast agents alter 23Na T1 relaxivity in glioma?

Incomplete fluid suppression on fluid-attenuated inversion-recovery 23Na-MRI (IR-23Na-MRI) was observed in three patients undergoing IR-23Na-MRI after gadolinium contrast injection, as part of a brain tumour imaging study. To evaluate this, 23Na-MRI T1 maps were acquired before and after injection of a gadolinium-based contrast agent on a grade IV glioma (GBM) patient, which showed a statistically significant change of 23Na-MRI T1 within the peritumoral oedema (p=0.0095). Gadolinium contrast-enhanced 23Na-MRI could potentially add further applications for sodium imaging and probe tumour tissue structure in new ways to investigate proliferation and treatment response

Dynamic contrast-enhanced MRI of synovitis in knee osteoarthritis: repeatability, discrimination and sensitivity to change in a prospective experimental study

OBJECTIVES: Evaluate test-retest repeatability, ability to discriminate between osteoarthritic and healthy participants, and sensitivity to change over 6 months, of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) biomarkers in knee OA. METHODS: Fourteen individuals aged 40-60 with mild-moderate knee OA and 6 age-matched healthy volunteers (HV) underwent DCE-MRI at 3 T at baseline, 1 month and 6 months. Voxelwise pharmacokinetic modelling of dynamic data was used to calculate DCE-MRI biomarkers including Ktrans and IAUC60. Median DCE-MRI biomarker values were extracted for each participant at each study visit. Synovial segmentation was performed using both manual and semiautomatic methods with calculation of an additional biomarker, the volume of enhancing pannus (VEP). Test-retest repeatability was assessed using intraclass correlation coefficients (ICC). Smallest detectable differences (SDDs) were calculated from test-retest data. Discrimination between OA and HV was assessed via calculation of between-group standardised mean differences (SMD). Responsiveness was assessed via the number of OA participants with changes greater than the SDD at 6 months. RESULTS: Ktrans demonstrated the best test-retest repeatability (Ktrans/IAUC60/VEP ICCs 0.90/0.84/0.40, SDDs as % of OA mean 33/71/76%), discrimination between OA and HV (SMDs 0.94/0.54/0.50) and responsiveness (5/1/1 out of 12 OA participants with 6-month change > SDD) when compared to IAUC60 and VEP. Biomarkers derived from semiautomatic segmentation outperformed those derived from manual segmentation across all domains. CONCLUSIONS: Ktrans demonstrated the best repeatability, discrimination and sensitivity to change suggesting that it is the optimal DCE-MRI biomarker for use in experimental medicine studies. KEY POINTS: • Dynamic contrast-enhanced MRI (DCE-MRI) provides quantitative measures of synovitis in knee osteoarthritis which may permit early assessment of efficacy in experimental medicine studies. • This prospective observational study compared DCE-MRI biomarkers across domains relevant to experimental medicine: test-retest repeatability, discriminative validity and sensitivity to change. • The DCE-MRI biomarker Ktrans demonstrated the best performance across all three domains, suggesting that it is the optimal biomarker for use in future interventional studies

Multiparametric MRI of early tumor response to immune checkpoint blockade in metastatic melanoma

Data availability statement: Data are available on reasonable request. Data may be obtained from a third party and are not publicly available. All data relevant to the study are included in the article or uploaded as supplementary information. Please contact the corresponding author Doreen Lau ([email protected]).Background: Immune checkpoint inhibitors are now standard of care treatment for many cancers. Treatment failure in metastatic melanoma is often due to tumor heterogeneity, which is not easily captured by conventional CT or tumor biopsy. The aim of this prospective study was to investigate early microstructural and functional changes within melanoma metastases following immune checkpoint blockade using multiparametric MRI. Methods: Fifteen treatment-naïve metastatic melanoma patients (total 27 measurable target lesions) were imaged at baseline and following 3 and 12 weeks of treatment on immune checkpoint inhibitors using: T2-weighted imaging, diffusion kurtosis imaging, and dynamic contrast-enhanced MRI. Treatment timepoint changes in tumor cellularity, vascularity, and heterogeneity within individual metastases were evaluated and correlated to the clinical outcome in each patient based on Response Evaluation Criteria in Solid Tumors V.1.1 at 1 year. Results: Differential tumor growth kinetics in response to immune checkpoint blockade were measured in individual metastases within the same patient, demonstrating significant intertumoral heterogeneity in some patients. Early detection of tumor cell death or cell loss measured by a significant increase in the apparent diffusivity (Dapp) (p<0.05) was observed in both responding and pseudoprogressive lesions after 3 weeks of treatment. Tumor heterogeneity, as measured by apparent diffusional kurtosis (Kapp), was consistently higher in the pseudoprogressive and true progressive lesions, compared with the responding lesions throughout the first 12 weeks of treatment. These preceded tumor regression and significant tumor vascularity changes (Ktrans, ve, and vp) detected after 12 weeks of immunotherapy (p<0.05). Conclusions: Multiparametric MRI demonstrated potential for early detection of successful response to immune checkpoint inhibitors in metastatic melanoma.This project was supported by Cancer Research UK (CRUK; C19212/A16628, C19212/A911376), the CRUK Cambridge Centre (C9685/A25177), a Cambridge Commonwealth, European and International Trust PhD Scholarship, a European Institute of Innovation and Technology (EIT) health grant for Innovation for Personalized Cancer Medicine, the CRUK & Engineering and Physical Sciences Research Council (EPSRC) Cancer Imaging Centre in Cambridge and Manchester (C197/A16465), Cancer Core Europe, and Addenbrooke’s Charitable Trust. This research was also supported by the National Institute for Health Research Cambridge Biomedical Research Centre (RG85317)

Creating a clinical platform for carbon‐13 studies using the sodium‐23 and proton resonances

Purpose Calibration of hyperpolarized 13C‐MRI is limited by the low signal from endogenous carbon‐containing molecules and consequently requires 13C‐enriched external phantoms. This study investigated the feasibility of using either 23Na‐MRI or 1H‐MRI to calibrate the 13C excitation. Methods Commercial 13C‐coils were used to estimate the transmit gain and center frequency for 13C and 23Na resonances. Simulations of the transmit B1 profile of a Helmholtz loop were performed. Noise correlation was measured for both nuclei. A retrospective analysis of human data assessing the use of the 1H resonance to predict [1‐13C]pyruvate center frequency was also performed. In vivo experiments were undertaken in the lower limbs of 6 pigs following injection of hyperpolarized 13C‐pyruvate. Results The difference in center frequencies and transmit gain between tissue 23Na and [1‐13C]pyruvate was reproducible, with a mean scale factor of 1.05179 ± 0.00001 and 10.4 ± 0.2 dB, respectively. Utilizing the 1H water peak, it was possible to retrospectively predict the 13C‐pyruvate center frequency with a standard deviation of only 11 Hz sufficient for spectral–spatial excitation‐based studies. Conclusion We demonstrate the feasibility of using the 23Na and 1H resonances to calibrate the 13C transmit B1 using commercially available 13C‐coils. The method provides a simple approach for in vivo calibration and could improve clinical workflow.</p

Three-Dimensional Surface-Based Analysis of Cartilage MRI Data in Knee Osteoarthritis: Validation and Initial Clinical Application

Background: Traditional quantitative analysis of cartilage with MRI averages measurements (eg, thickness) across regions-of-interest (ROIs) which may reduce responsiveness. Purpose: To validate and describe clinical application of a semiautomated surface-based method for analyzing cartilage relaxation times (“composition”) and morphology on MRI, 3D cartilage surface mapping (3D-CaSM). Study Type: Validation study in cadaveric knees and prospective observational (cohort) study in human participants. Population: Four cadaveric knees and 14 participants aged 40–60 with mild–moderate knee osteoarthritis (OA) and 6 age-matched healthy volunteers, imaged at baseline, 1, and 6 months. Field Strength/Sequence: 3D spoiled gradient echo, T1rho/T2 magnetization-prepared 3D fast spin echo for mapping of T1rho/T2 relaxation times and delayed gadolinium enhanced MRI of cartilage (dGEMRIC) using variable flip angle T1 relaxation time mapping at 3T. Assessment: 3D-CaSM was validated against high-resolution peripheral quantitative computed tomography (HRpQCT) in cadaveric knees, with comparison to expert manual segmentation. The clinical study assessed test–retest repeatability and sensitivity to change over 6 months for cartilage thickness and relaxation times. Statistical Tests: Bland–Altman analysis was performed for the validation study and evaluation of test–retest repeatability. Six-month changes were assessed via calculation of the percentage of each cartilage surface affected by areas of significant change (%SC), defined using thresholds based on area and smallest detectable difference (SDD). Results: Bias and precision (0.06 ± 0.25 mm) of 3D-CaSM against reference HRpQCT data were comparable to expert manual segmentation (−0.13 ± 0.26 mm). 3D-CaSM demonstrated significant (>SDD) 6-month changes in cartilage thickness and relaxation times in both OA participants and healthy controls. The parameter demonstrating the greatest 6-month change was T2 relaxation time (OA median %SC [IQR] = 8.8% [5.5 to 12.6]). Data Conclusion: This study demonstrates the construct validity and potential clinical utility of 3D-CaSM, which may offer advantages to conventional ROI-based methods. Level of Evidence: 2. Technical Efficacy Stage: 2. J. Magn. Reson. Imaging 2020;52:1139–1151

Hyperpolarised 13C-MRI identifies the emergence of a glycolytic cell population within intermediate-risk human prostate cancer

Hyperpolarised magnetic resonance imaging (HP 13C-MRI) is an emerging clinical technique to detect [1-13C]lactate production in prostate cancer (PCa) following intravenous injection of hyperpolarised [1-13C]pyruvate. Here we differentiate clinically significant PCa from indolent disease in a low/intermediate-risk population by correlating [1-13C]lactate labelling on MRI with the percentage of Gleason pattern 4 (%GP4) disease. Using immunohistochemistry and spatial transcriptomics, we show that HP 13C-MRI predominantly measures metabolism in the epithelial compartment of the tumour, rather than the stroma. MRI-derived tumour [1-13C]lactate labelling correlated with epithelial mRNA expression of the enzyme lactate dehydrogenase (LDHA and LDHB combined), and the ratio of lactate transporter expression between the epithelial and stromal compartments (epithelium-to-stroma MCT4). We observe similar changes in MCT4, LDHA, and LDHB between tumours with primary Gleason patterns 3 and 4 in an independent TCGA cohort. Therefore, HP 13C-MRI can metabolically phenotype clinically significant disease based on underlying metabolic differences in the epithelial and stromal tumour compartments