From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors
By R. Wahl, H. Jacene, Y. Kasamon, M. Lodge. Journal of Nuclear Medicine, 2009
3,646 citations recorded by the source corpus.
The purpose of this article is to review the status and limitations of anatomic tumor response metrics including the World Health Organization (WHO) criteria, the Response Evaluation Criteria in Solid Tumors (RECIST), and RECIST 1.1. This article also reviews qualitative and quantitative approaches to metabolic tumor response assessment with 18F-FDG PET and proposes a draft framework for PET Response Criteria in Solid Tumors (PERCIST), version 1.0. Methods: PubMed searches, including searches for the terms RECIST, positron, WHO, FDG, cancer (including specific types), treatment response, region of interest, and derivative references, were performed. Abstracts and articles judged most relevant to the goals of this report were reviewed with emphasis on limitations and strengths of the anatomic and PET approaches to treatment response assessment. On the basis of these data and the authors' experience, draft criteria were formulated for PET tumor response to treatment. Results: Approximately 3,000 potentially relevant references were screened. Anatomic imaging alone using standard WHO, RECIST, and RECIST 1.1 criteria is widely applied but still has limitations in response assessments. For example, despite effective treatment, changes in tumor size can be minimal in tumors such as lymphomas, sarcoma, hepatomas, mesothelioma, and gastrointestinal stromal tumor. CT tumor density, contrast enhancement, or MRI characteristics appear more informative than size but are not yet routinely applied. RECIST criteria may show progression of tumor more slowly than WHO criteria. RECIST 1.1 criteria (assessing a maximum of 5 tumor foci, vs. 10 in RECIST) result in a higher complete response rate than the original RECIST criteria, at least in lymph nodes. Variability appears greater in assessing progression than in assessing response. Qualitative and quantitative approaches to 18F-FDG PET response assessment have been applied and require a consistent PET methodology to allow quantitative assessments. Statistically significant changes in tumor standardized uptake value (SUV) occur in careful test–retest studies of high-SUV tumors, with a change of 20% in SUV of a region 1 cm or larger in diameter; however, medically relevant beneficial changes are often associated with a 30% or greater decline. The more extensive the therapy, the greater the decline in SUV with most effective treatments. Important components of the proposed PERCIST criteria include assessing normal reference tissue values in a 3-cm-diameter region of interest in the liver, using a consistent PET protocol, using a fixed small region of interest about 1 cm3 in volume (1.2-cm diameter) in the most active region of metabolically active tumors to minimize statistical variability, assessing tumor size, treating SUV lean measurements in the 1 (up to 5 optional) most metabolically active tumor focus as a continuous variable, requiring a 30% decline in SUV for “response,” and deferring to RECIST 1.1 in cases that do not have 18F-FDG avidity or are technically unsuitable. Criteria to define progression of tumor-absent new lesions are uncertain but are proposed. Conclusion: Anatomic imaging alone using standard WHO, RECIST, and RECIST 1.1 criteria have limitations, particularly in assessing the activity of newer cancer therapies that stabilize disease, whereas 18F-FDG PET appears particularly valuable in such cases. The proposed PERCIST 1.0 criteria should serve as a starting point for use in clinical trials and in structured quantitative clinical reporting. Undoubtedly, subsequent revisions and enhancements will be required as validation studies are undertaken in varying diseases and treatments.
Subfields: Genetics, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/1526a310d898c01f4aca47942d1cf92850ca71c6
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Genetics
In Radiology, Nuclear Medicine and Imaging
- Hugo J. W. L. Aerts
- I. E. El Naqa
- Philippe Lambin
- Ronald Boellaard
- Fabian Isensee
- Klaus Hermann Maier-Hein
- Milan Sonka
- Christos Davatzikos
Citations in the corpus
- 3D Slicer as an Image Computing Platform for the Quantitative Imaging Network (2012, methodology): “Response assessment to cancer therapy based on molecular imaging with PET/CT lacks an accepted robust and accurate quantitative metric [62–64].”
- FDG PET/CT: EANM procedure guidelines for tumour imaging: version 2.0 (2014, neutral): “2-cm diameter (or 1-mL volume) spherical VOI [61] positioned such that the average value across all positions within the lesion is maximized.”
- FDG PET and PET/CT: EANM procedure guidelines for tumour PET imaging: version 1.0 (2009, background): “2 cm diameter fixed size circular ROI (defined in axial plane), centreed on the tumour area with highest uptake, as recently suggested in [12].”
- Role of imaging in the staging and response assessment of lymphoma: consensus of the International Conference on Malignant Lymphomas Imaging Working Group. (2014, methodology): “Work is ongoing to assess optimal tumor and liver metrics.(102) The liver is also affected by”
- A Review on Segmentation of Positron Emission Tomography Images (2014, methodology): “A quantitative assessment of changes in FDG uptake in PET images is required for accurate diagnosis and assessment of treatment response, whereas a qualitative assessment of PET images is usually sufficient for the detection of lesions [16].”
- The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping. (2016, background): “ourhood draws upon all voxels regardless of being in a ROI. 4.2.1 Local intensity peak The local intensity peak was originally devised for reducing variance in determining standardised uptake values (Wahl et al., 2009). It is defined as the mean grey level in a 1 cm3 spherical volume, centered on the”