Evaluating the metabolic effects of neoadjuvant treatment in clear cell renal cell carcinoma using hyperpolarised pyruvate MRI
Horvat-Menih, I.; McLean, M. A.; Birchall, J.; Zamora Morales, M. J.; Wylot, M.; Ursprung, S.; Woitek, R.; Serrao, E.; Grimmer, A.; Latimer, E.; Khan, A. S.; Priest, A. N.; Gill, A. B.; Kaggie, J.; Graves, M. J.; Barrett, T.; Wason, J. M. S.; Mossop, H.; Thomas, M.; Said, S.; Warren, A. Y.; Fife, K.; Eisen, T.; Matakidou, A.; Ince, W.; O'Carrigan, B.; Jones, J.; Welsh, S. J.; Mitchell, T. J.; Armitage, J. N.; Riddick, A. C. P.; Stewart, G. D.; Gallagher, F. A.
Show abstract
Despite recent advances, [~]50% of people developing renal cell carcinoma (RCC) will die of the disease. The development of new neoadjuvant therapeutic strategies requires reliable companion biomarkers to measure early and successful response to treatment. Tumour size changes are often late markers of response, but novel imaging-based biomarkers may be more accurate for treatment response prediction. Here we evaluated the potential of hyperpolarised carbon-13 MRI (HP 13C-MRI) as an emerging clinical imaging technique for assessing response to neoadjuvant treatment in RCC, as part of the WIndow of opportunity in REnal cancer (WIRE) trial. The change in LAC/PYR ratio following treatment was variable across the four patients (mean{+/-}S.D. %change = +6{+/-}27%). LAC/PYR decreased in the patient treated with cediranib monotherapy (-21%), and in one of the patients receiving combination treatment (-14%). A higher LAC/PYR ratio post-treatment was observed in the second patient receiving combination treatment (+21%) and in the patient receiving olaparib monotherapy (+35%). This is the first study to evaluate the potential of clinical HP 13C-MRI in assessing early treatment response in renal cancer, which detected metabolic changes following treatment in the absence of significant changes in tumour size. Future studies should assess this finding in larger patient cohorts. Patient summaryIn this study we used an emerging clinical imaging technique, called hyperpolarised carbon-13 MRI, to visualise how kidney cancer changes with drug treatment before surgery. The method visualised rapid changes in cancer metabolism before substantial changes were seen in tumour size, the latter being the conventional method for detecting response to treatment. Hyperpolarised carbon-13 MRI holds promise in informing clinicians which cancers have successfully responded, and which may benefit from a change in treatment.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Imaging the Transmembrane and Transendothelial Sodium Gradients in Gliomas 91%
- Two years later – changes in abdominal organs: First observations from the UK Biobank longitudinal imaging study 91%
- Towards integration of 64Cu-DOTA-Trasztusumab PET-CT and MRI with mathematical modeling to predict response to neoadjuvant therapy in HER2+ breast cancer 91%
Similar papers in this journal
- Multimetric MRI Captures Early Response and Acquired Resistance of Pancreatic Cancer to KRAS Inhibitor Therapy 91%
- PARP1/2 imaging with 18F-PARPi in patients with head and neck cancer 91%
- Diffusion Histology Imaging Combining Diffusion Basis Spectrum Imaging (DBSI) and Machine Learning Improves Detection and Classification of Glioblastoma Pathology 88%
Similar papers in this journal
- Co-clinical FDG-PET Radiomic Signature in Predicting Response to Neoadjuvant Chemotherapy in Triple Negative Breast Cancer 93%
- A simple strategy to reduce the salivary gland and kidney uptake of PSMA targeting small molecule radiopharmaceuticals 91%
- Automated Long Axial Field of View PET Image Processing and Kinetic Modelling with the TurBO Toolbox 90%
Similar papers in this journal
- SPECT/CT imaging, biodistribution and radiation dosimetry of a 177Lu-DOTA-integrin αvβ6 cystine knot peptide in a pancreatic cancer xenograft model 91%
- Circulating tumor fraction analyses with ultra-low pass whole genome sequencing predict response to chemoradiation and recurrence in stage IV small cell carcinoma of the cervix: a longitudinal case study 89%
- Deep-Learning-Based Generation of Synthetic High-Resolution MRI from Low-Resolution MRI for Use in Head and Neck Cancer Adaptive Radiotherapy 88%
Similar papers in this journal
- Combining imaging- and gene-based hypoxia biomarkers in cervical cancer improves prediction of chemoradiotherapy failure independent of intratumor heterogeneity 90%
- Fusing Data from CT Deep Learning, CT Radiomics and Peripheral Blood Immune profiles to Diagnose Lung Cancer in Symptomatic Patients 87%
- Metabolomic profiling of pancreatic adenocarcinoma reveals fundamental clinical features 87%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.