Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications

Bera, Kaustav; Velcheti, Vamsidhar; Madabhushi, Anant

doi:10.1200/edbk_199747

Cited by 56 publications

(49 citation statements)

References 135 publications

(130 reference statements)

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“…In our retrospective multi-institutional analysis, we have restricted the testing of texture parameters to NSCLC patients undergone to salvage treatment with Nivolumab. We have described morphological, histogram and GLCM matrix features defining parameters which have been subsequently correlated in lung cancer imaging, and in recent years with immunotherapy in NSCLC (26,36,(45)(46)(47)(48)(49). Interestingly, within our sample of NSCLC patients, subjected to Nivolumab treatment, we defined morphological features able to identify a cohort of patients with a very poor prognosis.…”

Section: Discussionmentioning

confidence: 99%

Radiomics predicts survival of patients with advanced non‑small cell lung cancer undergoing PD‑1 blockade using Nivolumab

Nardone¹,

Tini

Pastina

et al. 2019

Oncol Lett

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Section: Discussionmentioning

confidence: 99%

Radiomics predicts survival of patients with advanced non‑small cell lung cancer undergoing PD‑1 blockade using Nivolumab

Nardone¹,

Tini

Pastina

et al. 2019

Oncol Lett

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“…As we look to the future, automated sTIL assessment holds the promise of adding complementarity to the current pathological evaluation of breast cancers. A heterogeneous pattern of lymphocyte infiltration may be better addressed with computational pathology methods 40,41 . Further, there is some evidence that the spatial distribution of TILs may provide additional prognostic information 42 .…”

Section: Frequency Seen Recommendationmentioning

confidence: 99%

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Kos¹,

et al. 2020

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Stromal tumor-infiltrating lymphocytes (sTILs) are important prognostic and predictive biomarkers in triple-negative (TNBC) and HER2-positive breast cancer. Incorporating sTILs into clinical practice necessitates reproducible assessment. Previously developed standardized scoring guidelines have been widely embraced by the clinical and research communities. We evaluated sources of variability in sTIL assessment by pathologists in three previous sTIL ring studies. We identify common challenges and evaluate impact of discrepancies on outcome estimates in early TNBC using a newly-developed prognostic tool. Discordant sTIL assessment is driven by heterogeneity in lymphocyte distribution. Additional factors include: technical slide-related issues; scoring outside the tumor boundary; tumors with minimal assessable stroma; including lymphocytes associated with other structures; and including other inflammatory cells. Small variations in sTIL assessment modestly alter risk estimation in early TNBC but have the potential to affect treatment selection if cutpoints are employed. Scoring and averaging multiple areas, as well as use of reference images, improve consistency of sTIL evaluation. Moreover, to assist in avoiding the pitfalls identified in this analysis, we developed an educational resource available at www.tilsinbreastcancer.org/pitfalls.

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“…However, no clear and validated textural model distinguishing high and low PD-L1 expression is described, and more studies have yet to be done. Finally, delta-radiomics (∆-radiomics), studying changes in radiomic features (e.g., texture within the nodule) on serial images could be useful to assess the effectiveness of therapy as well as predict early treatment response, but this domain as yet to be explored [50].…”

Section: Radiomics and Complex Quantitative Parametersmentioning

confidence: 99%

Immunotherapy by Immune Checkpoint Inhibitors and Nuclear Medicine Imaging: Current and Future Applications

Decazes

Bohn

2020

Cancers

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Immunotherapy by using immune checkpoint inhibitors is a revolutionary development in oncology. Medical imaging is also impacted by this new therapy, particularly nuclear medicine imaging (also called radionuclide imaging), which uses radioactive tracers to visualize metabolic functions. Our aim was to review the current applications of nuclear medicine imaging in immunotherapy, along with their limitations, and the perspectives offered by this imaging modality. Method: Articles describing the use of radionuclide imaging in immunotherapy were researched using PubMed by April 2019 and analyzed. Results: More than 5000 articles were analyzed, and nearly 100 of them were retained. Radionuclide imaging, notably 18F-FDG PET/CT, already has a major role in many cancers for pre-therapeutic and therapeutic evaluation, diagnoses of adverse effects, called immune-related adverse events (IrAE), and end-of-treatment evaluations. However, these current applications can be hindered by immunotherapy, notably due to atypical response patterns such as pseudoprogression, which is defined as an increase in the size of lesions, or the visualization of new lesions, followed by a response, and hyperprogression, which is an accelerated tumor growth rate after starting treatment. To overcome these difficulties, new opportunities are offered, particularly therapeutic evaluation criteria adapted to immunotherapy and immuno-PET allowing us to predict responses to immunotherapy. Moreover, some new technological solutions are also promising, such as radiomic analyses and body composition on associated anatomical images. However, more research has to be done, notably for the diagnosis of hyperprogression and pseudoprogression. Conclusion: Immunotherapy, by its major impact on cancer and by the new patterns generated on images, is revolutionary in the field of medical images. Nuclear medicine imaging is already established and will be able to help meet new challenges through its plasticity.

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Novel Quantitative Imaging for Predicting Response to Therapy: Techniques and Clinical Applications

Cited by 56 publications

References 135 publications

Radiomics predicts survival of patients with advanced non‑small cell lung cancer undergoing PD‑1 blockade using Nivolumab

Radiomics predicts survival of patients with advanced non‑small cell lung cancer undergoing PD‑1 blockade using Nivolumab

Pitfalls in assessing stromal tumor infiltrating lymphocytes (sTILs) in breast cancer

Immunotherapy by Immune Checkpoint Inhibitors and Nuclear Medicine Imaging: Current and Future Applications

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