Predicting pathologic response to neoadjuvant chemoradiation in resectable stage III non-small cell lung cancer patients using computed tomography radiomic features
Introduction
The treatment of stage III NSCLC involves a multi-disciplinary approach and careful patient selection to determine which resectable patients might benefit from a trimodality treatment [1,2]. Neoadjuvant chemotherapy administered prior to surgery can reduce tumor extent and metastases, thereby improving resectability. The role of surgery in stage IIIA patients still remains controversial. Survival benefit of surgery in this setting has long been debated and has proven difficult to demonstrate in multi-institute trials compared to definitive chemoradiation [1,3]. Yet, ad hoc subgroup analyses have provided data to suggest that resection (lobectomy) confers a clear survival benefit in this setting [1]. In current clinical practice the selection of patients for trimodality therapy is largely based on relatively limited lymph node burden, single lobe involvement, and patient fitness for this aggressive approach with little attention paid to specific markers of response.
Several studies have shown that pathologic response to chemoradiation is highly predictive of disease free survival and overall survival [[4], [5], [6]]. The degree of down staging seems to correlate with survival with the greatest benefit associated with ≤10% residual tumor noted on resected specimens (defined as major pathologic response (MPR)) [5]. Unfortunately, there are no extant clinically validated and approved biomarkers to predict MPR to chemoradiation.
Use of radiomics, or computerized feature analysis of radiographic scans, to capture quantitative phenotypic attributes of the tumor has emerged as an important prospect for survival prediction [[7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19]]. These approaches have been used to capture and associate quantitative measurements of intratumoral heterogeneity and tumor shape from CT scans to predict response to first line chemotherapy and neoadjuvant chemoradiation in patients with NSCLC [7,20,21]. However, apart from radiomic assessment of intratumoral heterogeneity patterns, there is increasing evidence that heterogeneity patterns associated with the peritumoral region—the area immediately surrounding the tumor mass—might harbor valuable disease specific prognostic cues. For instance, signatures of immune response such as presence of peritumoral lymphocytes have been shown to be associated with disease specific survival [22]. Also, vascular invasion and neovascularization within the peritumoral region have been shown to be associated with an increased likelihood of tumor recurrence as well as reduced overall survival [23].
In this work we sought to explore whether textural patterns of the peritumoral space coupled with measurements of lesion shape and intratumoral texture patterns might identify which stage IIIA NSCLC patients are likely to have MPR after chemoradiation. The association of these radiomic features with overall survival and disease free survival was also evaluated. The intra- and peritumoral texture features were extracted from baseline CT images and only a limited number of features that found to be strongly associated with response were validated in the testing set. Additionally, the prognostic ability of the radiomic features against tumor shape and clinicopathologic variables was also evaluated.
Section snippets
Study population
In this single-institution study we retrospectively evaluated the pretreatment CT scans of patients with locally advanced stage IIIA NSCLC who were treated with neoadjuvant chemoradiation followed by surgical resection. The treatment regimen included Carboplatin + Paclitaxel, Carboplatin + Docetaxel, Cisplatin + Etoposide and Carboplatin + Pemetrexed. This study was approved by the institutional review board at the Cleveland Clinic. One hundred twenty-three patients with stage III NSCLC treated
Statistical analysis
Ninety patients with NSCLC were included for analysis with a median age of 64 years (range 38 − 88 years), and majority of men (54.4%). Tumor histology was predominantly adenocarcinoma (71.1%) vs. 22.2% squamous cell carcinoma while the histology for 6.7% was unknown, stage IIIA (94.4%), with positive N2 nodes (91.1%). The median follow-up and survival time was 34.57 months (range: 0.13–114 months). The median time to recurrence or distant metastasis (DM) was 17.95 months (range: 0.2–70
Discussion
Tumoral heterogeneity is associated with a more aggressive tumor phenotype and poor clinical outcome [33,34]. Stage IIIA NSCLC is a highly heterogeneous disease, the role of trimodality approach is somewhat controversial and outcome of neoadjuvant chemoradiotherapy (NAC) followed by surgery is variable. Patients who do not respond to neoadjuvant chemoradiation often do not benefit from such aggressive surgical approach due to early recurrence of disease. Thus, using a biomarker directed
Conclusion
In conclusion, our study revealed that texture and shape features extracted from intratumoral and peritumoral region of lung tumors on CT images can identify patients with pathological response to chemoradiation. Our results point towards a promising role of radiomics in complementing existing clinical and radiological information in better patient selection, hopefully resulting in meaningful clinical benefit from trimodality approach in locally advanced NSCLC.
Funding
Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under award numbers 1U24CA199374-01, R01CA202752-01A1, R01CA208236-01A1, R01CA216579-01A1and R01 CA220581-01A1. National Center for Research Resources under award number 1 C06 RR12463-01. VA Merit Review Award IBX004121A from the United States Department of Veterans Affairs Biomedical Laboratory Research and Development Service, the DOD Prostate Cancer Idea Development Award
Acknowledgements and author contributions
Guarantor of integrity of entire study, A.M.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, M.K., P.J.; manuscript final version approval, all authors; literature research, M.K., A.M.; clinical studies, V.V., P.J.; statistical analysis, M.K., P.F; and manuscript editing, all authors. M.K., P.J. contributed equally to this manuscript.
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Introduction to radiomics for a clinical audience
2023, Clinical RadiologyRadiomics for Predicting Lung Cancer Outcomes Following Radiotherapy: A Systematic Review
2022, Clinical OncologyCitation Excerpt :The lack of standardisation on key clinical variables for comparison of radiomics performance also restricts the interpretation of the literature, and tumour-specific international consensus statements to this effect would be constructive. Commonly tested clinicopathological factors in the studies identified include patient fitness [42,46,48] and tumour histology [42,46,81,86], volume [48,81,86] and stage [42,46,48]. As one of the first grading systems designed for the field [114], the RQS has been readily implemented in the assessment of the quality of radiomics studies [115–117].
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Joint first authors.