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Contains fulltext : 238654.pdf (Publisher’s version ) (Open Access), Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. KEY POINTS: * Data-driven processes like radiomics risk false discoveries due to high-dimensionality of the da

Existing quantitative imaging biomarkers (QIBs) are associated with known biological tissue characteristics and follow a well-understood path of technical, biological and clinical validation before incorporation into clinical trials. In radiomics, novel data-driven processes extract numerous visually imperceptible statistical features from the imaging data with no a priori assumptions on their correlation with biological processes. The selection of relevant features (radiomic signature) and incorporation into clinical trials therefore requires additional considerations to ensure meaningful imaging endpoints. Also, the number of radiomic features tested means that power calculations would result in sample sizes impossible to achieve within clinical trials. This article examines how the process of standardising and validating data-driven imaging biomarkers differs from those based on biological associations. Radiomic signatures are best developed initially on datasets that represent diversity of acquisition protocols as well as diversity of disease and of normal findings, rather than within clinical trials with standardised and optimised protocols as this would risk the selection of radiomic features being linked to the imaging process rather than the pathology. Normalisation through discretisation and feature harmonisation are essential pre-processing steps. Biological correlation may be performed after the technical and clinical validity of a radiomic signature is established, but is not mandatory. Feature selection may be part of discovery within a radiomics-specific trial or represent exploratory endpoints within an established trial; a previously validated radiomic signature may even be used as a primary/secondary endpoint, particularly if associations are demonstrated with specific biological processes and pathways being targeted within clinical trials. Key Points: • Data-driven processes like radiomics risk false discoveries due to high-dimensionality

Oligometastatic disease has been proposed as an intermediate state between localised and systemically metastasised disease. In the absence of randomised phase 3 trials, early clinical studies show improved survival when radical local therapy is added to standard systemic therapy for oligometastatic disease. However, since no biomarker for the identification of patients with true oligometastatic disease is clinically available, the diagnosis of oligometastatic disease is based solely on imaging findings. A small number of metastases on imaging could represent different clinical scenarios, which are associated with different prognoses and might require different treatment strategies. 20 international experts including 19 members of the European Society for Radiotherapy and Oncology and European Organisation for Research and Treatment of Cancer OligoCare project developed a comprehensive system for characterisation and classification of oligometastatic disease. We first did a systematic review of the literature to identify inclusion and exclusion criteria of prospective interventional oligometastatic disease clinical trials. Next, we used a Delphi consensus process to select a total of 17 oligometastatic disease characterisation factors that should be assessed in all patients treated with radical local therapy for oligometastatic disease, both within and outside of clinical trials. Using a second round of the Delphi method, we established a decision tree for oligometastatic disease classification together with a nomenclature. We agreed oligometastatic disease as the overall umbrella term. A history of polymetastatic disease before diagnosis of oligometastatic disease was used as the criterion to differentiate between induced oligometastatic disease (previous history of polymetastatic disease) and genuine oligometastatic disease (no history of polymetastatic disease). We further subclassified genuine oligometastatic disease into repeat oligometastatic disease (previous

Contains fulltext : 205490.pdf (publisher's version ) (Closed access), CONTEXT: In patients treated for prostate cancer, a rising serum prostate-specific antigen (PSA) level is a first sign of relapse, but imaging is needed to determine the localization of the recurrence, which may be local, in lymph nodes, and/or metastatic. With the increasing success rate of earlier salvage therapy, the diagnosis has become pertinent when the recurrent PSA level is still very low. OBJECTIVE: To systematically review the literature on the role of the existing imaging techniques in patients with early recurrent prostate cancer. EVIDENCE ACQUISITION: A systematic literature search across the MEDLINE and EMBASE databases was conducted in February 2018, searching for original studies reporting on imaging in a (sub)group of patients with recurrent PSA levels not higher than 5ng/ml. This systematic review was performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The methodological quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) tool. EVIDENCE SYNTHESIS: A total of 98 studies were included in this systematic review, reporting on the role of transrectal ultrasonography (TRUS), computed tomography (CT), bone scintigraphy (BS), single-photon emission CT, multiparametric magnetic resonance imaging (mpMRI), whole-body MRI (wbMRI), and positron emission tomography (PET)-CT/MRI using 18F fluoro-deoxy-glucose, 11C choline, 18F (fluoro)(methyl)choline, 11C acetate, 18F FACBC (fluciclovine) and prostate-specific membrane antigen (PSMA)-based tracers. CT and BS were not sufficiently sensitive in the early recurrence setting. For the detection of local recurrence, TRUS or mpMRI can be used; however, at the lowest PSA levels, few data were available, only after radical prostatectomy, showing a wide range of positivity. TRUS or mpMRI need to be combined with (PET)-CT to assess distant disease, but new techniques such as wbMRI, PET-MRI, or PET-CT allow

The exponential growth of novel therapies for the treatment of metastatic castration-resistant prostate cancer (mCRPC) over the last decade has created an acute need for education and guidance of clinicians regarding optimal strategies for patient management. A multidisciplinary panel of 21 European experts in mCRPC assembled for comprehensive discussion and consensus development, seeking to move the field forward and provide guidance and perspectives on optimal selection and sequencing of therapeutic agents and monitoring of response to treatment and disease progression. A total of 110 clinically-relevant questions were addressed and a modified Delphi method was utilised to obtain a consensus. The panel reached a consensus on several important issues, providing recommendations on appropriate phase III clinical trial end-points and optimal strategies for imaging and monitoring of bone metastases. Guidance regarding selection and sequencing of therapy in patients with newly diagnosed or progressive mCRPC is emphasised, including the use of novel bone-targeted agents, chemotherapy, androgen receptor pathway-targeted agents and immunotherapy. The impact of drug resistance and prostate-specific antigen flare on treatment decisions was also addressed. Ultimately, individualised therapy for patients with mCRPC is dependent on continued refinement of clinical decision-making based on patient and disease characteristics. This consensus statement offers clinicians expert guidance on the implementation of recent advances to improve patient outcome, focusing on the future of prostate cancer care.