Imaging Response Assessment in Immuno‑Oncology: Navigating an Evolving Landscape

Immuno-oncology (IO) has transformed cancer therapy, introducing durable responses across a range of tumor types. However, it has also made imaging response assessment in immuno-oncology more complex. Traditional radiologic frameworks remain foundational, but immune-mediated effects, such as pseudoprogression, delayed responses, and tumor flare, require adapted criteria and careful longitudinal evaluation to ensure accurate interpretation.

Why Immuno-Oncology Imaging is Different

Unlike cytotoxic therapies, immunotherapies can produce atypical response patterns on imaging. Lesions may initially increase in size due to immune cell infiltration, new lesions may transiently appear, and findings may fluctuate before a response becomes clear.

To address this, immune-adapted response criteria have been developed. These frameworks preserve the rigor of conventional oncologic imaging assessment while allowing for confirmation of progression and better characterization of immune-related effects¹.

Response Assessment in Solid Tumors

Read criteria evaluation in solid tumors is based on RECIST 1.1, which standardizes tumor measurement and classification². Building on this foundation, several immune-adapted criteria have been introduced, including:

• Immune-related Response Criteria (irRC)
• Immune-related RECIST (irRECIST)
• Immune-modified RECIST (imRECIST)
• Immune RECIST (iRECIST)

Among these, iRECIST is widely adopted in immuno-oncology clinical trials. It introduces the concept of:

• Unconfirmed progressive disease (iUPD)
• Confirmed progressive disease (iCPD)

Progression identified on imaging must be confirmed on a subsequent scan (typically 4–8 weeks later) to account for pseudoprogression. This confirmatory framework helps prevent premature discontinuation of effective therapies and improves the reliability of imaging-based endpoints.

Response Assessment in Neuro-Oncology

Neuro-oncology imaging is especially challenging because treatment effects, steroid use, edema, and immune activity can all affect MRI appearance.

The Response Assessment in Neuro-Oncology (RANO) criteria form the foundation for evaluating gliomas³. Extensions of this framework include:

• iRANO (adapted for immunotherapy trials)
• mRANO (modified criteria addressing imaging-related treatment effects)
• RANO 2.0, which standardizes response assessment across high- and low-grade gliomas⁴

These frameworks explicitly address:

• Pseudoprogression (PsP): treatment-related increases in enhancement
• Pseudoresponse (PsR): apparent imaging improvement not reflective of true tumor response

When pseudoprogression or pseudoresponse is suspected, continued therapy with follow-up imaging is recommended to confirm true disease status.

Response Assessment in Lymphoma and Leukemia

In hematologic malignancies, imaging response assessment is based on the Lugano classification, which incorporates PET-CT and CT imaging for staging and response evaluation⁵.

For immunotherapy studies, the LYRIC (Lymphoma Response to Immunomodulatory Therapy Criteria) framework extends Lugano by introducing Indeterminate response (IR) to account for pseudoprogression or tumor flare and requires follow-up imaging before confirming progression⁶. PET-CT is strongly recommended for staging FDG-avid nodal lymphomas, while contrast-enhanced CT may be needed in specific settings for more accurate measurement or anatomical clarification. Consistency in modality and timing across assessments is essential for reliable longitudinal evaluation.

Hybrid Read Criteria for Primary Central Nervous System Lymphoma

Primary CNS lymphoma requires a hybrid imaging approach that integrates both lymphoma and neuro-oncology response criteria⁷.

Response evaluation incorporates:

• International Primary CNS Lymphoma Collaborative Group (IPCG) criteria
• RANO-based imaging frameworks

Given the complexity of CNS imaging, confirmation of complete response and progressive disease with repeat imaging is recommended to ensure accurate classification and avoid misinterpretation of transient findings.

The Role of Imaging Partners in IO Trials

In immuno-oncology trials, imaging partners ensure that complex response criteria such as iRECIST, RANO, and LYRIC are applied consistently across timepoints. Beyond image interpretation, they support adherence to protocol-defined imaging schedules and confirmation requirements, which is essential for evaluating pseudoprogression and delayed response. Reliable longitudinal assessment underpins accurate and reproducible endpoint determination⁸.

Sponsors should also expect standardized workflows, regulatory-compliant systems, and efficient data handling across multicenter studies. Imaging platforms that enable segmentation, tracking, and response assessment, combined with oncology expertise, help reduce variability and preserve data quality. At Voiant, this approach is supported by purpose-built technology and scientific expertise designed to bring consistency and clarity to complex imaging endpoints⁹. Together, these capabilities support confident decision-making and the advancement of clinical development programs.

Conclusion

Immuno-oncology has reshaped response assessment, requiring more nuanced and disciplined imaging approaches. Across solid tumors, neuro-oncology, and hematologic malignancies, frameworks such as iRECIST, RANO, and LYRIC provide the structure needed to interpret complex response patterns, including pseudoprogression and delayed effects. Consistent application of these criteria is essential for reliable trial endpoints.

As trials grow more complex, imaging plays an increasingly important role in supporting clinical decision-making. With experienced partners, standardized workflows, and robust technology, sponsors can better manage variability, maintain data integrity, and generate reliable evidence that advances immuno-oncology development.

References

1. Seymour L, Bogaerts J, Perrone A, et al. iRECIST: guidelines for response criteria for use in trials testing immunotherapeutics. Lancet Oncol. 2017;18(3):e143–e152. https://doi.org/10.1016/S1470-2045(17)30074-8 ↩︎
2. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer. 2009;45(2):228–247. https://doi.org/10.1016/j.ejca.2008.10.026 ↩︎
3. Wen PY, Macdonald DR, Reardon DA, et al. Updated response assessment criteria for high-grade gliomas: RANO. J Clin Oncol. 2010;28(11):1963–1972. https://doi.org/10.1200/JCO.2009.26.3541 ↩︎
4. Wen PY, van den Bent M, Vogelbaum MA, Chang SM. RANO 2.0: The revised Response Assessment in Neuro-Oncology (RANO) criteria for high- and low-grade glial tumors in adults designed for the future. Neuro Oncol. 2024;26(1):2-4. https://doi.org/10.1093/neuonc/noad189 ↩︎
5. Cheson BD, Fisher RI, Barrington SF, et al. Recommendations for initial evaluation, staging, and response assessment of lymphoma: Lugano classification. J Clin Oncol. 2014;32(27):3059–3068. https://doi.org/10.1200/JCO.2013.54.8800 ↩︎
6. Cheson BD, Ansell S, Schwartz L, et al. Refinement of lymphoma response criteria in the era of immunomodulatory therapy (LYRIC). Blood. 2016;128(21):2489–2496. https://doi.org/10.1182/blood-2016-05-718528 ↩︎
7. Abrey LE, Batchelor TT, Ferreri AJM, et al. Report of an International Workshop to Standardize Baseline Evaluation and Response Criteria for Primary CNS Lymphoma. J Clin Oncol. 2005;23(22):5034–5043. https://doi.org/10.1200/JCO.2005.13.524 ↩︎
8. Voiant Clinical. Oncology Imaging Solutions for Clinical Trials. https://www.voiantclinical.com/therapeutic-areas/oncology/ ↩︎
9. Voiant Clinical. AI-Enabled Clinical Trial Imaging Technology Platform. https://www.voiantclinical.com/technology/ ↩︎