The Image Biomarker Standardization Initiative validated consensus-based reference values for 169 radiomics features, thus enabling calibration and verification of radiomics software. Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpos...

Imaging biomarkers (IBs) are used extensively in drug development and cancer research, but important differences exist between IBs and biospecimen-derived biomarkers. A tailored 'roadmap' is required for the development of new IBs to be used either in clinical research or for decision-making in healthcare. In this Consensus statement, a group of experts assembled by CRUK and the EORTC present 14 key recommendations for accelerating the clinical translation of IBs. Imaging biomarkers (IBs) are integral to the routine management of patients with cancer. IBs used daily in oncology include clinical TNM stage, objective response and left ventricular ejection fraction. Other CT, MRI, PET and ultrasonography biomarkers are used extensively in cancer research and drug development. New IBs need to be established either as useful tools for testing research hypotheses in clinical trials and research studies, or as clinical decision-making tools for use in healthcare, by crossing 'translational gaps' through validation and qualification. Important differences exist between IBs and biospecimen-derived biomarkers and, therefore, the development of IBs requires a tailored 'roadmap'. Recognizing this need, Cancer Research UK (CRUK) and the European Organisation for Research and Treatment of Cancer (EORTC) assembled experts to review, debate and summarize the challenges of IB validation and qualification. This consensus group has produced 14 key recommendations for accelerating the clinical translation of IBs, which highlight the role of parallel (rather than sequential) tracks of technical (assay) validation, biological/clinical validation and assessment of cost-effectiveness; the need for IB standardization and accreditation systems; the need to continually revisit IB precision; an alternative framework for biological/clinical validation of IBs; and the essential requirements for multicentre studies to qualify IBs for clinical use.

Tumor spatial heterogeneity is an important prognostic factor, which may be reflected in medical images Image texture analysis is an approach of quantifying heterogeneity that may not be appreciated by the naked eye. Different methods can be applied including statistical-, model-, and transform-based methods. Early evidence suggests that texture analysis has the potential to augment diagnosis and characterization as well as improve tumor staging and therapy response assessment in oncological practice. This review provides an overview of the application of texture analysis with different imaging modalities, CT, MRI, and PET, to date and describes the technical challenges that have limited its widespread clinical implementation so far. With further efforts to refine its application, image texture analysis has the potential to develop into a valuable clinical tool for oncologic imaging. • Tumor spatial heterogeneity is an important prognostic factor. • Image texture analysis is an approach of quantifying heterogeneity. • Different methods can be applied, including statistical-, model-, and transform-based methods. • Texture analysis could improve the diagnosis, tumor staging, and therapy response assessment.

PURPOSE: 99mTechnetium methylene diphosphonate (99mTc MDP) bone scintigraphy is currently the method of choice for the detection of bone metastases, but 18F-fluoro-deoxy-D-glucose positron emission tomography (18FDG PET) offers superior spatial resolution and improved sensitivity. We have compared 18FDG PET with 99mTc MDP bone scintigraphy in patients with skeletal metastases from breast cancer and have analyzed the data in subgroups based on radiographic characteristics of lesions. PATIENTS AND METHODS: Twenty-three women with breast cancer and confirmed bone metastases were studied with both 99mTC MDP bone scintigraphy and 18FDG PET, and the number of lesions detected and the quantitation of uptake (standardized uptake values [SUVs]) of 18FDG in osteolytic and osteoblastic metastases were compared. Survival was compared for both lytic and blastic bone metastases and for patients with high and low accumulation of 18FDG. RESULTS: 18FDG PET detected more lesions than 99mTc MDP scintigraphy (mean, 14.1 and 7.8 lesions, respectively; P < .01). However, 18FDG detected fewer bone metastases compared with 99mTc MDP scintigraphy in a subgroup of patients with osteoblastic disease (P < .05). Higher SUVs were observed for osteolytic than osteoblastic disease (mean, 6.77 and 0.95, respectively; P < .01). Survival was lower in patients with osteolytic disease compared with the remainder (P=.01). A difference in survival was not found for those patients with high SUVs (> 3.6; P=.4). CONCLUSION: 18FDG PET is superior to bone scintigraphy in the detection of osteolytic breast cancer metastases, which led to a poorer prognosis. In contrast, osteoblastic metastases show lower metabolic activity and are frequently undetectable by PET. The biologic explanation for this observation remains to be elucidated.

There is evidence in some solid tumors that textural features of tumoral uptake in ¹⁸F-FDG PET images are associated with response to chemoradiotherapy and survival. We have investigated whether a similar relationship exists in non–small cell lung cancer (NSCLC). Methods: Fifty-three patients (mean age, 65.8 y; 31 men, 22 women) with NSCLC treated with chemoradiotherapy underwent pretreatment ¹⁸F-FDG PET/CT scans. Response was assessed by CT Response Evaluation Criteria in Solid Tumors (RECIST) at 12 wk. Overall survival (OS), progression-free survival (PFS), and local PFS (LPFS) were recorded. Primary tumor texture was measured by the parameters coarseness, contrast, busyness, and complexity. The following parameters were also derived from the PET data: primary tumor standardized uptake values (SUVs) (mean SUV, maximum SUV, and peak SUV), metabolic tumor volume, and total lesion glycolysis. Results: Compared with nonresponders, RECIST responders showed lower coarseness (mean, 0.012 vs. 0.027; P = 0.004) and higher contrast (mean, 0.11 vs. 0.044; P = 0.002) and busyness (mean, 0.76 vs. 0.37; P = 0.027). Neither complexity nor any of the SUV parameters predicted RECIST response. By Kaplan–Meier analysis, OS, PFS, and LPFS were lower in patients with high primary tumor coarseness (median, 21.1 mo vs. not reached, P = 0.003; 12.6 vs. 25.8 mo, P = 0.002; and 12.9 vs. 20.5 mo, P = 0.016, respectively). Tumor coarseness was an independent predictor of OS on multivariable analysis. Contrast and busyness did not show significant associations with OS (P = 0.075 and 0.059, respectively), but PFS and LPFS were longer in patients with high levels of each (for contrast: median of 20.5 vs. 12.6 mo, P = 0.015, and median not reached vs. 24 mo, P = 0.02; and for busyness: median of 20.5 vs. 12.6 mo, P = 0.01, and median not reached vs. 24 mo, P = 0.006). Neither complexity nor any of the SUV parameters showed significant associations with the survival parameters. Conclusion: In NSCLC, baseline ¹⁸F-FDG PET scan uptake showing abnormal texture as measured by coarseness, contrast, and busyness is associated with nonresponse to chemoradiotherapy by RECIST and with poorer prognosis. Measurement of tumor metabolic heterogeneity with these parameters may provide indices that can be used to stratify patients in clinical trials for lung cancer chemoradiotherapy.