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From RECIST to PERCIST: Evolving Considerations for PET Response Criteria in Solid Tumors
Open accessAbstract
UNLABELLED: 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 (18)F-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 (18)F-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 cm(3) 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 (18)F-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 (18)F-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.
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“SUVmax of normal background tissues, including the liver and mediastinal blood pool are commonly used as references to define the disease and assess tumor response to therapy.[7]”
From Intrapatient variability of 18F-FDG uptake in normal tissues (2022) · cites this paper as [7]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“However, it has been demonstrated that inter-rater agreement in response assessment with [18F]FDG-PET in non-small cell lung cancer or metastatic breast cancer can be considerably improved through the use of the target lesion SULpeak (PERCIST 1.0 criteria) in comparison with a subjective assessment [194,214,215].”
From Influences on PET Quantification and Interpretation (2022) · cites this paper as [194]
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“SUVmax and the standardized uptake value normalized by lean body mass are becoming popular indices for quantitative assessment of the therapeutic response in cancer patients.(13) However, SUVmax is a semi-quantitative parameter that does not reflect the volume or intensity of the FDG uptake and can be affected by the…”
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“The mean and maximum standard uptake values (SUVmean and SUVmax) corrected for body weight in a 2D region of interest (ROI) in the most metabolic part of as many tumors as possible are used in EORTC [2], while SUVs corrected for lean body mass (=SUL) in a stringent volume of interest (VOI) of 1 cm3 centered on the mos…”
BackgroundMethodSystemic therapy response evaluation in prostate carcinoma with [68Ga]Ga-PSMA-11 PET/CT
Kucuker, K. A., Yapar, Z., Guney, I. B., & Paydaş, S. (2022) · The Egyptian Journal of Radiology and Nuclear Medicine · doi:10.1186/s43055-022-00857-2 · Cited by 1
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“Das häufigste Ereignis im kombiniertenArmwar eineProgressionwährend der Strahlentherapie nach RECIST-Kriterien [12], obwohl der Wert der RECISTKriterien für die Beurteilung des Ansprechens von Weichgewebssarkomen nach Radio- oder Chemotherapie umstritten ist [13, 14].”
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“It is noteworthy that despite the stability of tumor 18F-FDG uptake, the target lesion also displayed a significant increase in tumor metabolic, active tumor volume (MATV) and should therefore had been classified as progressive disease if PERCIST criteria [22] had been applied.”
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Topkan, E., Somay, E., Başçıl, S., Ozturk, D., & Selek, U. (2026) · Diseases · doi:10.3390/diseases14090306
“Treatment response was evaluated according to the PET Response Criteria for Solid Tumors (PERCIST) [25].”
Deleu, A.-L., Bondue, B., Öztürk, A. A., Artigas, C., Lacroix, S., Vercauteren, S., Marin, C., Vanderlinden, B., Taraji, L., Lavis, P., et al. (2026) · Annals of Nuclear Medicine · doi:10.1007/s12149-026-02271-4
Dual‐view scout scans with deep learning for ultra‐low dose attenuation correction in PET
Muller, F. M., Daube-Witherspoon, M., Parma, M. J., Perkins, A., Noël, P., Vanhove, C., Vandenberghe, S., & Karp, J. (2026) · Medical Physics (Lancaster) · doi:10.1002/mp.70647
“58 Our findings suggest that the reported biases for (NAC + Scout)-to-(Tr) network are unlikely to substantially affect clinical response assessment, while potentially supporting improved precision in tracking smaller longitudinal changes.”
Hartrampf, P., Kosmala, A., Alwers, S., Lutz, F., Serfling, S., Hasenauer, N., Däubler, C., Meining, A., Buck, A. K., Werner, R. A., et al. (2026) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-026-08130-8
Cozzi, S., Brenna, D., Vial, N., Roukoz, C., Oprea-Lager, D., & Zilli, T. (2026) · International Journal of Radiation Oncology, Biology, Physics · doi:10.1016/j.ijrobp.2026.02.225
Esophageal and Gastric Cancers.
Babu, A., Umar, M., Alavi, A., & Kumar, R. (2026) · PET Clinics · doi:10.1016/j.cpet.2026.06.011
Mourath, D., Romdhani, N. S., Bergman, V., Siikanen, J., Tran, T., Alhuseinalkhudhur, A., Kistner, A., & Altena, R. (2026) · Cancers · doi:10.3390/cancers18152514
“SUVmax was chosen as the quantitative measure in the majority of the included trials and is a simple and clinically useful metric, but it may, as it is based on a single voxel, be particularly susceptible to image noise and statistical fluctuations [33].”
Shiva, C., Vengadesan, K., Alavi, A., & Kumar, R. (2026) · PET Clinics · doi:10.1016/j.cpet.2026.06.012
Fluorodeoxyglucose PET/Computed Tomography in Multimodality and Theranostic Workflows
Khandelwal, Y., Bishnoi, K., Jain, B., & Kumar, R. (2026) · PET Clinics · doi:10.1016/j.cpet.2026.06.015
Akgun, E., Tepedelenli̇oğlu, H. E., Aydin, S., Yurdakul, T., Gültekin, S. S., & Çevi̇k, H. (2026) · Journal of Clinical Medicine · doi:10.3390/jcm15166436
“…the broader literature, in which baseline SUVmax has been associated with prognosis and treatment response across multiple oncologic settings [23–26], and supports integrating metabolic data into surgical planning rather than restricting their use to diagnostic or follow-up purposes [21,24,26–28].”
Cardona, J. J., Lam, F., Gharyani, M. F. A., Hori, Y. S., Abu-Reesh, D., Ustrzynski, L., Emrich, S., Tayag, A., Gu, X.-J., Pollom, E., et al. (2026) · Neurosurgical review · doi:10.1007/s10143-026-04415-6
Zhai, W.-H., Wang, R.-Y., Ye, M.-M., Li, X.-L., Wang, Y., Zhou, T.-H., Zhou, X.-X., Jin, Q.-X., Zhang, Z.-W., & Fan, L. (2026) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-026-08098-5
“The result - ing liver-normalized standardized uptake ratio (SUR) metrics were reported as SUR (Mean) and SUR (SD) for each tissue compartment [ 17 , 18 ].”
Takagawa, Y., Takai, Y., Ono, T., Seto, I., Takayama, K., Komori, S., Kato, R., Takeuchi, A., Yamazaki, Y., Motoyanagi, T., et al. (2026) · Journal of Radiation Research · doi:10.1093/jrr/rrag053
Wang, H.-Y., Wu, Y.-P., Duan, Y.-H., Li, L., Sun, L.-B., Tao, X.-T., Zhang, N., Zhao, X.-W., Liu, J.-J., Guan, Z.-L., et al. (2026) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-026-08086-9
“SUL was recommended by both the Society for Nuclear Medicine and Molecular Imaging (SNMMI) and the European Association for Nuclear Medicine (EANM) in their FDG PET/CT imaging operation guidelines, especially in multicenter and quantitative studies [29, 30].”
Nakamoto, R., Fujimoto, K., Sakamoto, R., Yakami, M., Nobashi, T. W., Isoda, H., 片岡正子, & Nakamoto, Y. (2026) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-026-02131-7
Zhang, Z., Zhao, Y., & Li, Z. (2026) · Medicine · doi:10.1097/md.0000000000049724
“The initial PET-CT findings met PERCIST criteria for malignancy, [5] with hypermetabolic lesions (SUVmax 8.7 in the bladder, 7.8 in retroperitoneal nodes) and an anatomical distribution suggestive of urothelial carcinoma with metastatic spread.”
InfluentialOlivas, K., Byrd, D. W., Felice, N., Segars, W. P., Kinahan, P., Abadi, E., & Samei, E. (2026) · Physica medica (Testo stampato) · doi:10.1016/j.ejmp.2026.105885
Tamimi, A. S. A. A., Albusaidi, H., Mamari, M. A. A., Salmi, S. Z. A., Al-Bulushi, H. A., Balushi, M. A. A., Abri, S. A. A., Abri, S. S. A., & Omairi, Q. H. A. (2026) · World Journal of Nuclear Medicine · doi:10.1055/s-0046-1825754
“82 Finally, accessibility and cost considerations remain barriers to the widespread adoption of advanced PET tracers and multiparametric imaging, particularly in resource-limited settings, limiting their integration into routine clinical work-fl ows.”
Stenvall, A., Minarik, D., Trägårdh, E., & Kvernby, S. (2026) · EJNMMI Physics · doi:10.1186/s40658-026-00919-8
“The optimal parameters for the evaluated BGO PET/CT system, balancing SNR and lesion detectability within a clinical reasonable acquisition time, were 60–90 s with β-values of 500–300, in combination with the Medium DLb-TOF model, when 3.5 MBq/ kg [ 18 F]FDG was administered.”
InfluentialGLOW-FDG: Generalized cancer LesiOn Whole-body segmentation model for 18F-FDG-PET/CT
Fritsak, M., Rokuss, M. R., Gabryś, H., Kirchhoff, Y., Hamm, B., Christ, S., Martz, N., Opitz, I., Stahel, R., Hüllner, M., et al. (2026) · arXiv.org · doi:10.48550/arxiv.2607.03931
“Whole-body 18 F-fluorodeoxyglucose positron emission tomography combined with computed tomography (FDG-PET/CT) is widely adopted in oncologic staging [1, 2], response assessment [1, 3], and prognostication [1, 4] due to its visualization of tumor metabolism against anatomic context.”
Fan, M., Yao, Z.-H., Guo, X., Hu, M., Zhang, F., Liu, G.-F., Zhang, C.-Y., Zhao, J., & Chen, Y. (2026) · Clinical Nuclear Medicine · doi:10.1097/rlu.0000000000006588
Frega, J., Somme, L., Martin, T., Petit, T., Salvadori, J., Bund, C., & Somme, F. (2026) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-026-08029-4
“Target lesions were defined in accordance with PERCIST 1.0 criteria [13] as having a SULpeak greater than 1.5 × mean hepatic SUL + 2 SD, with a longest diameter > 1.5 cm (or > 1.0 cm for lymph nodes).”
InfluentialJiao, T., Zhang, C., Hu, Y., Cao, Y.-B., Tang, H.-W., Ma, G.-Y., & Lu, S.-Y. (2026) · European Journal of Radiology · doi:10.1016/j.ejrad.2026.113055
Atieh, M., Pushparajah, K., Ghidaglia, J., Castilla-Lièvre, M., Deliu, D., Massaria, V., Harnais, K., Buffon, A., Beau, M., Jentreau, Y., et al. (2026) · EANM Innovation · doi:10.1016/j.eanmi.2026.100280
Xu, T.-T., Yu, X., Chen, F., Wang, W., Cheng, K., Liu, Y., Wang, Y.-W., Peng, D.-S., Huang, Z.-W., Zhang, C.-Y., et al. (2026) · Radiology · doi:10.1148/radiol.260907
Andersson, V., Johnson, K., & Skarping, I. (2026) · European Journal of Radiology · doi:10.1016/j.ejrad.2026.113083
Beyond pain response: rethinking endpoints in radiotherapy trials for bone metastases.
Lee, S.-F., Wong, H. C. Y., Oldenburger, E., Raman, S., Marta, G., Chan, A. W., Rades, D., van der Linden, Y. M., der Velden, J. M. V., Nguyen, Q.-N., et al. (2026) · European Journal of Cancer · doi:10.1016/j.ejca.2026.116946
50 Years with FDG PET: The Warm-Up
Høilund-Carlsen, P. (2026) · The EANM Journal · doi:10.1016/j.eanmj.2026.100238
FDG PET/CT in Immuno-Oncology.
Sanjith, L. S., Khangembam, B., & Kumar, R. (2026) · PET Clinics · doi:10.1016/j.cpet.2026.06.014
Applications of [18F]fluorodeoxyglucose PET Imaging in Colorectal Cancer.
Chandekar, K., Karna, R., & Damle, N. (2026) · PET Clinics · doi:10.1016/j.cpet.2026.06.008
[18F]FDG-PET in Lung Cancer: From Staging to Therapy Response
Singh, H., Aggarwal, P., Kumar, R., & Singh, N. (2026) · PET Clinics · doi:10.1016/j.cpet.2026.06.005
Sagar, S., Khan, D., Kundu, N., & Kumar, R. (2026) · PET Clinics · doi:10.1016/j.cpet.2026.06.017
Withey, S., Caglič, I., Dafydd, D. A., Wicki, A., Kelly-Morland, C., Sohaib, A., Sit, C., Remer, E. M., & Kekelidze, M. (2026) · Abdominal Radiology · doi:10.1007/s00261-026-05604-z
Kashyap, R. K., Buteau, J. P., Papa, N. P., Ayati, N., Eifer, M., Betech-Antar, V., Akhurst, T. J., Alipour, R., Kong, G., Saghebi, J., et al. (2026) · Journal of Nuclear Medicine · doi:10.2967/jnumed.126.272531
Open-Geometry PET: quantifying the trade-off between time-of-flight resolution and angular coverage
Razdevšek, G., Dolenec, R., Orehar, M., Fakhri, G. E., Majewski, S., & Pestotnik, R. (2026) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ae8217
“While no universal clinical threshold exists, contrast differences of this magnitude are often considered small in PET image quality assessment and may be below the level of visual detectability for many imaging tasks, depending on noise level and lesion size (Wahl et al 2009).”
Voxel-wise Repeatability of [18F]FDG PET/MRI Quantitative Metrics in Cervical Cancer
Fraum, T. J., Nagarajan, P., & Wahl, R. L. (2026) · Nuclear Medicine and Molecular Imaging · doi:10.1007/s13139-026-01038-z
Self-citationThunold, S., Hernes, E., Mikalsen, L. T. G., Farooqi, S., Öjlert, Å., Francis, R. J., Nowak, A. K., Szejniuk, W., Nielsen, S. S., Cedres, S., et al. (2026) · EJNMMI Research · doi:10.1186/s13550-026-01469-x
“…of 2 cm was positioned over the region demonstrating the highest uptake intensity to derive peak standardised uptake value (SUVpeak), in line with the PET Response Criteria in Solid Tumours (PER-CIST) recommendation to use SUVpeak as a quantitative metric [27], and was recorded as SUV 60min .”
di Micco, R., Saraçoğlu, S., Pfob, A., Canevari, C., Gallivanone, F., Antunovic, L., Gelardi, F., Scifo, P., Neri, I., Losio, C., et al. (2026) · Frontiers in Oncology · doi:10.3389/fonc.2026.1845216
“According to RECIST and PERCIST criteria, the breast cCR was determined by the disappearance of breast lesions on US and MRI and the complete resolution of FDG uptake to background levels on PET imaging (29, 30).”
Xin, T., Lee, C., Perlman, S. B., Gowdy, C., Shin, M., Renfro, L., Kelly, K. M., McCarten, K., Alazraki, A. L., Voss, S. D., et al. (2026) · Journal of Nuclear Medicine · doi:10.2967/jnumed.125.270791
“All annotators adhered to a standardized labeling guide, provided in the supplemental materials, available at http://jnm.snmjournals.org ( 13 – 16 ).”
Li, L., Feng, L., Zhou, Y., Chen, H., Li, Q., & Liu, S.-M. (2026) · Cancer Biotherapy and Radiopharmaceuticals · doi:10.1177/10849785261450841
Petter, E., LoPiccolo, J., Groha, S., Border, R., Pasaniuc, B., Kehl, K., Zaitlen, N., & Gusev, A. (2026) · Genome Medicine · doi:10.1186/s13073-026-01695-x
“However, clinicians focus on more granular and longitudinal measurements that can capture additional components of the tumor trajectory [17] not visible with a single end-point or time-to-first-event analyses.”
Zhu, K., Li, Z.-Y., Liao, J., Wang, C., Guo, R., Tang, Y., Zhou, S.-Q., Ding, Y., Chen, D.-D., Wang, J.-K., et al. (2026) · Oncology Letters · doi:10.3892/ol.2026.15693
“This finding is consistent with those of a previous study (36) and further supports the importance of tumor size in predicting NAT efficacy and informing surgical planning (37).”
Işık, Z., Volkan-Salancı, B., Yalçın, Ş., Güner, G., & Uğur, Ö. (2026) · Clinical and translational imaging · doi:10.1007/s40336-026-00779-3
“Anatomical response was graded by RECIST 1.1 and meta - bolic response by PERCIST [16 , 17 ].”
Influential
Metadata
- Authors
- Wahl, R. L., Jacene, H., Kasamon, Y., & Lodge, M. A.
- Affiliations
- Johns Hopkins University (US)
- Corresponding author
- Wahl, Richard L.
- Venue
- Journal of Nuclear Medicine
- Publisher
- Society of Nuclear Medicine
- Published
- 2009-04-29
- Volume
- 50
- Issue
- Suppl 1
- Pages
- 122S-150S
- ISSN
- 0161-5505 (ISSN-L)
- 2159-662X
- PMC
- PMC2755245
- OpenAlex
- W2155263737
- Cited by
- 3,777
- References
- 157
- Citations by year
- 2026: 180 · 2025: 200 · 2024: 197 · 2023: 230 · 2022: 248 · 2021: 309 · 2020: 271 · 2019: 259 · 2018: 225 · 2017: 274 · 2016: 246 · 2015: 245 · 2014: 221 · 2013: 230 · 2012: 192
- FWCI
- 21.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Nuclear Medicine (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (CA006973, P30CA006973)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Medical Imaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Radiomics and Machine Learning in Medical Imaging
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Diagnosis and Treatment
- Keywords
- RECIST, PERCIST, 18F-FDG PET, tumor response assessment, standardized uptake value, WHO criteria, RECIST 1.1, region of interest, treatment response assessment, solid tumors, lymphoma, sarcoma, hepatocellular carcinoma, mesothelioma, gastrointestinal stromal tumor, test-retest variability
- MeSH terms
- Forecasting, Humans, Neoplasms, Prognosis, World Health Organization, Treatment Outcome, Outcome Assessment, Health Care, Practice Guidelines as Topic, Radiopharmaceuticals, Fluorodeoxyglucose F18, Internationality, Positron-Emission Tomography
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