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Abstract Background Lesion/tissue segmentation on digital medical images enables biomarker extraction, image-guided therapy delivery, treatment response measurement, and training/validation for developing artificial intelligence algorithms and workflows. To ensure data reproducibility, criteria for standardised segmentation are critical but currently unavailable. Methods A modified Delphi process initiated by the European Imaging Biomarker Alliance (EIBALL) of the European Society of Radiology (ESR) and the European Organisation for Research and Treatment of Cancer (EORTC) Imaging Group was undertaken. Three multidisciplinary task forces addressed modality and image acquisition, segmentation methodology itself, and standards and logistics. Devised survey questions were fed via a facilitator to expert participants. The 58 respondents to Round 1 were invited to participate in Rounds 2–4. Subsequent rounds were informed by responses of previous rounds. Results/conclusions Items with ≥ 75% consensus are considered a recommendation. These include system performance certification, thresholds for image signal-to-noise, contrast-to-noise and tumour-to-background ratios, spatial resolution, and artefact levels. Direct, iterative, and machine or deep learning reconstruction methods, use of a mixture of CE marked and verified research tools were agreed and use of specified reference standards and validation processes considered essential. Operator training and refreshment were considered mandatory for clinical trials and clinical research. Items with a 60–74% agreement require reporting (site-specific accreditation for clinical research, minimal pixel number within lesion segmented, use of post-reconstruction algorithms, operator training refreshment for clinical practice). Items with ≤ 60% agreement are outside current recommendations for segmentation (frequency of system performance tests, use of only CE-marked tools, board certification of operators, frequency of operator refresher training). Recommendations by anatomical area are also specified.

BackgroundSize-based assessments are inaccurate indicators of tumor response in soft-tissue sarcoma (STS), motivating the requirement for new response imaging biomarkers for this rare and heterogeneous disease. In this study, we assess the test–retest repeatability of radiomic features from MR diffusion-weighted imaging (DWI) and derived maps of apparent diffusion coefficient (ADC) in retroperitoneal STS and compare baseline repeatability with changes in radiomic features following radiotherapy (RT).Materials and MethodsThirty patients with retroperitoneal STS received an MR examination prior to treatment, of whom 23/30 were investigated in our repeatability analysis having received repeat baseline examinations and 14/30 patients were investigated in our post-treatment analysis having received an MR examination after completing pre-operative RT. One hundred and seven radiomic features were extracted from the full manually delineated tumor region using PyRadiomics. Test–retest repeatability was assessed using an intraclass correlation coefficient (baseline ICC), and post-radiotherapy variance analysis (post-RT-IMS) was used to compare the change in radiomic feature value to baseline repeatability.ResultsFor the ADC maps and DWI images, 101 and 102 features demonstrated good baseline repeatability (baseline ICC > 0.85), respectively. Forty-three and 2 features demonstrated both good baseline repeatability and a high post-RT-IMS (>0.85), respectively. Pearson correlation between the baseline ICC and post-RT-IMS was weak (0.432 and 0.133, respectively).ConclusionsThe ADC-based radiomic analysis shows better test–retest repeatability compared with features derived from DWI images in STS, and some of these features are sensitive to post-treatment change. However, good repeatability at baseline does not imply sensitivity to post-treatment change.

Abstract Background Patients with metastatic colorectal cancer are treated with cytotoxic chemotherapy supplemented by molecularly targeted therapies. There is a critical need to define biomarkers that can optimise the use of these therapies to maximise efficacy and avoid unnecessary toxicity. However, it is important to first define the changes in potential biomarkers following cytotoxic chemotherapy alone. This study reports the impact of standard cytotoxic chemotherapy across a range of circulating and imaging biomarkers. Methods A single-centre, prospective, biomarker-driven study. Eligible patients included those diagnosed with colorectal cancer with liver metastases that were planned to receive first line oxaliplatin plus 5-fluorouracil or capecitabine. Patients underwent paired blood sampling and magnetic resonance imaging (MRI), and biomarkers were associated with progression-free survival (PFS) and overall survival (OS). Results Twenty patients were recruited to the study. Data showed that chemotherapy significantly reduced the number of circulating tumour cells as well as the circulating concentrations of Ang1, Ang2, VEGF-A, VEGF-C and VEGF-D from pre-treatment to cycle 2 day 2. The changes in circulating concentrations were not associated with PFS or OS. On average, the MRI perfusion/permeability parameter, K trans, increased in response to cytotoxic chemotherapy from pre-treatment to cycle 2 day 2 and this increase was associated with worse OS (HR 1.099, 95%CI 1.01–1.20, p = 0.025). Conclusions In patients diagnosed with colorectal cancer with liver metastases, treatment with standard chemotherapy changes cell- and protein-based biomarkers, although these changes are not associated with survival outcomes. In contrast, the imaging biomarker, K trans, offers promise to direct molecularly targeted therapies such as anti-angiogenic agents.

Identification of response biomarkers is a key step towards the development of personalised care. Here, Jayson et al. identify plasma Tie2 as a biomarker for the response of the tumor vasculature to anti-angiogenics in patients with metastatic colorectal cancer, suggesting that monitoring Tie2 levels may help guide therapy in the clinics.

Perianal Crohn’s Disease (pCD) is a common manifestation of Crohn’s Disease. Absence of reliable disease measures makes disease monitoring unreliable. Qualitative MRI has been increasingly used for diagnosing and monitoring pCD and has shown potential for assessing response to treatment. Quantitative MRI sequences, such as diffusion-weighted imaging (DWI), dynamic contrast enhancement (DCE) and magnetisation transfer (MT), along with T2 relaxometry, offer opportunities to improve diagnostic capability. Quantitative MRI sequences (DWI, DCE, MT and T2) were used in a cohort of 25 pCD patients before and 12 weeks after biological therapy at two different field strengths (1.5 and 3 T). Disease activity was measured with the Perianal Crohn’s Disease Activity index (PDAI) and serum C-reactive protein (CRP). Diseased tissue areas on MRI were defined by a radiologist. A baseline model to predict outcome at 12 weeks was developed. No differences were seen in the quantitative MR measured in the diseased tissue regions from baseline to 12 weeks; however, PDAI and CRP decreased. Baseline PDAI, CRP, T2 relaxometry and surgical history were found to have a moderate ability to predict response after 12 weeks of biological treatment. Validation in larger cohorts with MRI and clinical measures are needed in order to further develop the model.