The use of hyperpolarised 13 C-MRI in clinical body imaging to probe cancer metabolism

Abstract: Metabolic reprogramming is one of the hallmarks of cancer and includes the Warburg effect, which is exhibited by many tumours. This can be exploited by positron emission tomography (PET) as part of routine clinical cancer imaging. However, an emerging and alternative method to detect altered metabolism is carbon-13 magnetic resonance imaging (MRI) following injection of hyperpolarised [1-13C]pyruvate. The technique increases the signal-to-noise ratio for the detection of hyperpolarised 13C-labelled metabolites by several orders of magnitude and facilitates the dynamic, noninvasive imaging of the exchange of 13C-pyruvate to 13C-lactate over time. The method has produced promising preclinical results in the area of oncology and is currently being explored in human imaging studies. The first translational studies have demonstrated the safety and feasibility of the technique in patients with prostate, renal, breast and pancreatic cancer, as well as revealing a successful response to treatment in breast and prostate cancer patients at an earlier stage than multiparametric MRI. This review will focus on the strengths of the technique and its applications in the area of oncological body MRI including noninvasive characterisation of disease aggressiveness, mapping of tumour heterogeneity, and early response assessment. A comparison of hyperpolarised 13C-MRI with state-of-the-art multiparametric MRI is likely to reveal the unique additional information and applications offered by the technique

A method for mapping and quantifying whole organ diffusion-weighted image distortion in MR imaging of the prostate.

A computational algorithm was designed to produce a measure of DW image distortion across the prostate. This algorithm was tested and validated on virtual phantoms incorporating known degrees and distributions of distortion. A study was then carried out on DW image volumes from three sets of 10 patients who had been imaged previously. These volumes had been radiologically assessed to have, respectively, 'no distortion' or 'significant distortion' or the potential for 'significant distortion' due to susceptibility effects from hip prostheses. Prostate outlines were drawn on a T2-weighted (T2W) image 'gold-standard' volume and on an ADC image volume derived from DW images acquired over the same region. The algorithm was then applied to these outlines to quantify and map image distortion. The proposed method correctly reproduced known distortion values and distributions in virtual phantoms. It also successfully distinguished between the three groups of patients: mean distortion in 'non-distorted' image volumes, 1.942 ± 0.582 mm; 'distorted', 4.402 ± 1.098 mm; and 'hip patients' 8.083 ± 4.653 mm; P < 0.001. This work has demonstrated and validated a means of quantifying and mapping image distortion in clinical prostate MRI cases

In Vivo Cell Tracking Using PET: Opportunities and Challenges for Clinical Translation in Oncology.

Cell therapy is a rapidly evolving field involving a wide spectrum of therapeutic cells for personalised medicine in cancer. In vivo imaging and tracking of cells can provide useful information for improving the accuracy, efficacy, and safety of cell therapies. This review focuses on radiopharmaceuticals for the non-invasive detection and tracking of therapeutic cells using positron emission tomography (PET). A range of approaches for imaging therapeutic cells is discussed: Direct ex vivo labelling of cells, in vivo indirect labelling of cells by utilising gene reporters, and detection of specific antigens expressed on the target cells using antibody-based radiopharmaceuticals (immuno-PET). This review examines the evaluation of PET imaging methods for therapeutic cell tracking in preclinical cancer models, their role in the translation into patients, first-in-human studies, as well as the translational challenges involved and how they can be overcome

Effects of Multi-Shell Free Water Correction on Glioma Characterization.

Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity

Effects of Multi-Shell Free Water Correction on Glioma Characterization.

Diffusion MRI is a useful tool to investigate the microstructure of brain tumors. However, the presence of fast diffusing isotropic signals originating from non-restricted edematous fluids, within and surrounding tumors, may obscure estimation of the underlying tissue characteristics, complicating the radiological interpretation and quantitative evaluation of diffusion MRI. A multi-shell regularized free water (FW) elimination model was therefore applied to separate free water from tissue-related diffusion components from the diffusion MRI of 26 treatment-naïve glioma patients. We then investigated the diagnostic value of the derived measures of FW maps as well as FW-corrected tensor-derived maps of fractional anisotropy (FA). Presumed necrotic tumor regions display greater mean and variance of FW content than other parts of the tumor. On average, the area under the receiver operating characteristic (ROC) for the classification of necrotic and enhancing tumor volumes increased by 5% in corrected data compared to non-corrected data. FW elimination shifts the FA distribution in non-enhancing tumor parts toward higher values and significantly increases its entropy (p ≤ 0.003), whereas skewness is decreased (p ≤ 0.004). Kurtosis is significantly decreased (p < 0.001) in high-grade tumors. In conclusion, eliminating FW contributions improved quantitative estimations of FA, which helps to disentangle the cancer heterogeneity

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

Hyperpolarised 13C-MRI metabolic and functional imaging: an emerging renal MR diagnostic modality.

Magnetic resonance imaging (MRI) is a well-established modality for assessing renal morphology and function, as well as changes that occur during disease. However, the significant metabolic changes associated with renal disease are more challenging to assess with MRI. Hyperpolarized carbon-13 MRI is an emerging technique which provides an opportunity to probe metabolic alterations at high sensitivity by providing an increase in the signal-to-noise ratio of 20,000-fold or more. This review will highlight the current status of hyperpolarised 13C-MRI and its translation into the clinic and how it compares to metabolic measurements provided by competing technologies such as positron emission tomography (PET).This study was funded by Aarhus University Research Foundation and Karen Elise Jensen Foundation

Quantification and reduction of cross-vendor variation in multicenter DWI MR imaging: results of the Cancer Core Europe imaging task force

Magnetic resonance imaging; Radiomics; Measurement VariabilityImatges per ressonància magnètica; Radiòmica; Variabilitat de mesuraImágenes por resonancia magnética; Radiómica; Variabilidad de medidaObjectives In the Cancer Core Europe Consortium (CCE), standardized biomarkers are required for therapy monitoring oncologic multicenter clinical trials. Multiparametric functional MRI and particularly diffusion-weighted MRI offer evident advantages for noninvasive characterization of tumor viability compared to CT and RECIST. A quantification of the inter- and intraindividual variation occurring in this setting using different hardware is missing. In this study, the MRI protocol including DWI was standardized and the residual variability of measurement parameters quantified. Methods Phantom and volunteer measurements (single-shot T2w and DW-EPI) were performed at the seven CCE sites using the MR hardware produced by three different vendors. Repeated measurements were performed at the sites and across the sites including a traveling volunteer, comparing qualitative and quantitative ROI-based results including an explorative radiomics analysis. Results For DWI/ADC phantom measurements using a central post-processing algorithm, the maximum deviation could be decreased to 2%. However, there is no significant difference compared to a decentralized ADC value calculation at the respective MRI devices. In volunteers, the measurement variation in 2 repeated scans did not exceed 11% for ADC and is below 20% for single-shot T2w in systematic liver ROIs. The measurement variation between sites amounted to 20% for ADC and < 25% for single-shot T2w. Explorative radiomics classification experiments yield better results for ADC than for single-shot T2w. Conclusion Harmonization of MR acquisition and post-processing parameters results in acceptable standard deviations for MR/DW imaging. MRI could be the tool in oncologic multicenter trials to overcome the limitations of RECIST-based response evaluation.Open Access funding enabled and organized by Projekt DEAL. This study has received funding by Cancer Core Europe for the travel expenses of M. Bach traveling with the MR – Phantom between centers

Enhancing the spatial resolution of hyperpolarized carbon‐13 MRI of human brain metabolism using structure guidance

Funder: Mark Foundation Institute for Cancer ResearchFunder: Cambridge Experimental Cancer Medicine CentreFunder: Alan Turing Institute; Id: http://dx.doi.org/10.13039/100012338Funder: Cantab Capital Institute for the Mathematics of InformationPurpose: Dynamic nuclear polarization is an emerging imaging method that allows noninvasive investigation of tissue metabolism. However, the relatively low metabolic spatial resolution that can be achieved limits some applications, and improving this resolution could have important implications for the technique. Methods: We propose to enhance the 3D resolution of carbon‐13 magnetic resonance imaging (13C‐MRI) using the structural information provided by hydrogen‐1 MRI (1H‐MRI). The proposed approach relies on variational regularization in 3D with a directional total variation regularizer, resulting in a convex optimization problem which is robust with respect to the parameters and can efficiently be solved by many standard optimization algorithms. Validation was carried out using an in silico phantom, an in vitro phantom and in vivo data from four human volunteers. Results: The clinical data used in this study were upsampled by a factor of 4 in‐plane and by a factor of 15 out‐of‐plane, thereby revealing occult information. A key finding is that 3D super‐resolution shows superior performance compared to several 2D super‐resolution approaches: for example, for the in silico data, the mean‐squared‐error was reduced by around 40% and for all data produced increased anatomical definition of the metabolic imaging. Conclusion: The proposed approach generates images with enhanced anatomical resolution while largely preserving the quantitative measurements of metabolism. Although the work requires clinical validation against tissue measures of metabolism, it offers great potential in the field of 13C‐MRI and could significantly improve image quality in the future

Comparison of initial and tertiary centre second opinion reads of multiparametric magnetic resonance imaging of the prostate prior to repeat biopsy.

OBJECTIVES: To investigate the value of second-opinion evaluation of multiparametric prostate magnetic resonance imaging (MRI) by subspecialised uroradiologists at a tertiary centre for the detection of significant cancer in transperineal fusion prostate biopsy. METHODS: Evaluation of prospectively acquired initial and second-opinion radiology reports of 158 patients who underwent MRI at regional hospitals prior to transperineal MR/untrasound fusion biopsy at a tertiary referral centre over a 3-year period. Gleason score (GS) 7-10 cancer, positive predictive value (PPV) and negative (NPV) predictive value (±95 % confidence intervals) were calculated and compared by Fisher's exact test. RESULTS: Disagreement between initial and tertiary centre second-opinion reports was observed in 54 % of cases (86/158). MRIs had a higher NPV for GS 7-10 in tertiary centre reads compared to initial reports (0.89 ± 0.08 vs 0.72 ± 0.16; p = 0.04), and a higher PPV in the target area for all cancer (0.61 ± 0.12 vs 0.28 ± 0.10; p = 0.01) and GS 7-10 cancer (0.43 ± 0.12 vs 0.2 3 ± 0.09; p = 0.02). For equivocal suspicion, the PPV for GS 7-10 was 0.12 ± 0.11 for tertiary centre and 0.11 ± 0.09 for initial reads; p = 1.00. CONCLUSIONS: Second readings of prostate MRI by subspecialised uroradiologists at a tertiary centre significantly improved both NPV and PPV. Reporter experience may help to reduce overcalling and avoid overtargeting of lesions. KEY POINTS: • Multiparametric MRIs were more often called negative in subspecialist reads (41 % vs 20 %). • Second readings of prostate mpMRIs by subspecialist uroradiologists significantly improved NPV and PPV. • Reporter experience may reduce overcalling and avoid overtargeting of lesions. • Greater education and training of radiologists in prostate MRI interpretation is advised.RWTH Aachen University Hospital (Aachen, Germany), National Institute for Health Research Cambridge Biomedical Research Centre, Cancer Research UK, Engineering and Physical Sciences Research Council Imaging Centre in Cambridge and Manchester, Cambridge Experimental Cancer Medicine Centr