Tumor Size Is Not Everything: Advancing Radiomics as a Precision Medicine Biomarker in Oncology Drug Development and Clinical Care. A Report of a Multidisciplinary Workshop Coordinated by the RECIST Working Group.

Radiomics, the science of extracting quantifiable data from routine medical images, is a powerful tool that has many potential applications in oncology. The Response Evaluation Criteria in Solid Tumors Working Group (RWG) held a workshop in May 2022, which brought together various stakeholders to discuss the potential role of radiomics in oncology drug development and clinical trials, particularly with respect to response assessment. This article summarizes the results of that workshop, reviewing radiomics for the practicing oncologist and highlighting the work that needs to be done to move forward the incorporation of radiomics into clinical trials.

Application of the Lugano Classification for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The PRoLoG Consensus Initiative (Part 1-Clinical).

Our objective was to provide consensus recommendations from a consortium of academic and industry experts in the field of lymphoma and imaging for consistent application of the Lugano classification. Methods: Consensus was obtained through a series of meetings from July 2019 until September 2021 sponsored by the Pharma Imaging Network for Therapeutics and Diagnostics (PINTaD) as part of the PINTaD Response Criteria in Lymphoma Working Group (PRoLoG) consensus initiative. Results: Consensus recommendations clarified technical considerations for PET/CT and diagnostic CT from the Lugano classification, including updating the FDG avidity of different lymphoma entities, clarifying the response nomenclature, and refining lesion classification and scoring, especially with regard to scores 4 and 5 and the X category of the 5-point scale. Combination of metabolic and anatomic responses is clarified, as well as response assessment in cases of discordant or missing evaluations. Use of clinical data in the classification, especially the requirement for bone marrow assessment, is further updated on the basis of lymphoma entities. Clarification is provided with regard to spleen and liver measurements and evaluation, as well as nodal response. Conclusion: Consensus recommendations are made to comprehensively address areas of inconsistency and ambiguity in the classification encountered during response evaluation by end users, and such guidance should be used as a companion to the 2014 Lugano classification.

Application of the Lugano Classification for Initial Evaluation, Staging, and Response Assessment of Hodgkin and Non-Hodgkin Lymphoma: The PRoLoG Consensus Initiative (Part 2-Technical).

The aim of this initiative was to provide consensus recommendations from a consortium of academic and industry experts in the field of lymphoma and imaging for the consistent application of imaging assessment with the Lugano classification. Methods: Consensus was obtained through a series of meetings from July 2019 to October 2021 sponsored by the PINTaD (Pharma Imaging Network for Therapeutics and Diagnostics) as part of the ProLoG (PINTaD RespOnse criteria in Lymphoma wOrking Group) consensus initiative. Results: Consensus recommendations encompass all technical imaging aspects of the Lugano classification. Some technical considerations for PET/CT and diagnostic CT are clarified with regards to required imaging series and scan visits, as well as acquisition and reconstruction of PET images and influence of lesion size and background activity. Recommendations are given on the role of imaging and clinical reviewers as well as on training and monitoring. Finally, an example template of an imaging case report form is provided to support efficient collection of data with Lugano Classification. Conclusion: Consensus recommendations are made to comprehensively address technical and imaging areas of inconsistency and ambiguity in the classification encountered by end users. Such guidance should be used to support standardized acquisition and evaluation with the Lugano 2014.

CT cerebral blood flow maps optimally correlate with admission diffusion-weighted imaging in acute stroke but thresholds vary by postprocessing platform.

BACKGROUND AND PURPOSE: Admission infarct core lesion size is an important determinant of management and outcome in acute (<9 hours) stroke. Our purposes were to: (1) determine the optimal CT perfusion parameter to define infarct core using various postprocessing platforms; and (2) establish the degree of variability in threshold values between these different platforms. METHODS: We evaluated 48 consecutive cases with vessel occlusion and admission CT perfusion and diffusion-weighted imaging within 3 hours of each other. CT perfusion was acquired with a "second-generation" 66-second biphasic cine protocol and postprocessed using "standard" (from 2 vendors, "A-std" and "B-std") and "delay-corrected" (from 1 vendor, "A-dc") commercial software. Receiver operating characteristic curve analysis was performed comparing each CT perfusion parameter-both absolute and normalized to the contralateral uninvolved hemisphere-between infarcted and noninfarcted regions as defined by coregistered diffusion-weighted imaging. RESULTS: Cerebral blood flow had the highest accuracy (receiver operating characteristic area under the curve) for all 3 platforms (P<0.01). The maximal areas under the curve for each parameter were: absolute cerebral blood flow 0.88, cerebral blood volume 0.81, and mean transit time 0.82 and relative Cerebral blood flow 0.88, cerebral blood volume 0.83, and mean transit time 0.82. Optimal receiver operating characteristic operating point thresholds varied significantly between different platforms (Friedman test, P<0.01). CONCLUSIONS: Admission absolute and normalized "second-generation" cine acquired CT cerebral blood flow lesion volumes correlate more closely with diffusion-weighted imaging-defined infarct core than do those of CT cerebral blood volume or mean transit time. Although limited availability of diffusion-weighted imaging for some patients creates impetus to develop alternative methods of estimating core, the marked variability in quantification among different postprocessing software limits generalizability of parameter map thresholds between platforms.