A multi-centric evaluation of self-learning GAN based pseudo-CT generation software for low field pelvic magnetic resonance imaging

Purpose/objectivesAn artificial intelligence-based pseudo-CT from low-field MR images is proposed and clinically evaluated to unlock the full potential of MRI-guided adaptive radiotherapy for pelvic cancer care.Materials and methodIn collaboration with TheraPanacea (TheraPanacea, Paris, France) a pseudo-CT AI-model was generated using end-to-end ensembled self-supervised GANs endowed with cycle consistency using data from 350 pairs of weakly aligned data of pelvis planning CTs and TrueFisp-(0.35T)MRIs. The image accuracy of the generated pCT were evaluated using a retrospective cohort involving 20 test cases coming from eight different institutions (US: 2, EU: 5, AS: 1) and different CT vendors. Reconstruction performance was assessed using the organs at risk used for treatment. Concerning the dosimetric evaluation, twenty-nine prostate cancer patients treated on the low field MR-Linac (ViewRay) at Montpellier Cancer Institute were selected. Planning CTs were non-rigidly registered to the MRIs for each patient. Treatment plans were optimized on the planning CT with a clinical TPS fulfilling all clinical criteria and recalculated on the warped CT (wCT) and the pCT. Three different algorithms were used: AAA, AcurosXB and MonteCarlo. Dose distributions were compared using the global gamma passing rates and dose metrics.ResultsThe observed average scaled (between maximum and minimum HU values of the CT) difference between the pCT and the planning CT was 33.20 with significant discrepancies across organs. Femoral heads were the most reliably reconstructed (4.51 and 4.77) while anal canal and rectum were the less precise ones (63.08 and 53.13). Mean gamma passing rates for 1%1mm, 2%/2mm, and 3%/3mm tolerance criteria and 10% threshold were greater than 96%, 99% and 99%, respectively, regardless the algorithm used. Dose metrics analysis showed a good agreement between the pCT and the wCT. The mean relative difference were within 1% for the target volumes (CTV and PTV) and 2% for the OARs.ConclusionThis study demonstrated the feasibility of generating clinically acceptable an artificial intelligence-based pseudo CT for low field MR in pelvis with consistent image accuracy and dosimetric results

Pan-cancer deconvolution of tumour composition using DNA methylation

The nature and extent of immune cell infiltration into solid tumours are key determinants of therapeutic response. Here, using a DNA methylation-based approach to tumour cell fraction deconvolution, we report the integrated analysis of tumour composition and genomics across a wide spectrum of solid cancers. Initially studying head and neck squamous cell carcinoma, we identify two distinct tumour subgroups: ‘immune hot’ and ‘immune cold’, which display differing prognosis, mutation burden, cytokine signalling, cytolytic activity and oncogenic driver events. We demonstrate the existence of such tumour subgroups pan-cancer, link clonal-neoantigen burden to cytotoxic T-lymphocyte infiltration, and show that transcriptional signatures of hot tumours are selectively engaged in immunotherapy responders. We also find that treatment-naive hot tumours are markedly enriched for known immune-resistance genomic alterations, potentially explaining the heterogeneity of immunotherapy response and prognosis seen within this group. Finally, we define a catalogue of mediators of active antitumour immunity, deriving candidate biomarkers and potential targets for precision immunotherapy

Erratum: Tumour-infiltrating lymphocytes predict response to definitive chemoradiotherapy in head and neck cancer

Correction to: British Journal of Cancer (2014) 110, 501–509. 10.1038/bjc.2013.64

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Background:We aimed to investigate the prognostic value of tumour-infiltrating lymphocytes' (TILs) expression in pretreatment specimens from patients with head and neck squamous cell carcinoma (HNSCC) treated with definitive chemoradiotherapy (CRT).Methods:The prevalence of CD3+, CD8+, CD4+ and FOXP3+ TILs was assessed using immunohistochemistry in tumour tissue obtained from 101 patients before CRT and was correlated with clinicopathological characteristics as well as local failure-free-(LFFS), distant metastases free-(DMFS), progression-free (PFS) and overall survival (OS). Survival curves were measured using the Kaplan-Meier method, and differences in survival between the groups were estimated using the log-rank test. Prognostic effects of TIL subset density were determined using the Cox regression analysis.Results:With a mean follow-up of 25 months (range, 2.3-63 months), OS at 2 years was 57.4% for the entire cohort. Patients with high immunohistochemical CD3 and CD8 expression had significantly increased OS (P=0.024 and P=0.028), PFS (P=0.044 and P=0.047) and DMFS (P=0.021 and P=0.026) but not LFFS (P=0.90 and P=0.104) in multivariate analysis that included predictive clinicopathologic factors, such as age, sex, T-stage, N-stage, tumour grading and localisation. Neither CD4 nor FOXP3 expression showed significance for the clinical outcome. The lower N-stage was associated with improved OS in the multivariate analysis (P=0.049).Conclusion:The positive correlation between a high number of infiltrating CD3+ and CD8+ cells and clinical outcome indicates that TILs may have a beneficial role in HNSCC patients and may serve as a biomarker to identify patients likely to benefit from definitive CRT. © 2014 Cancer Research UK