CT Imaging Features Associated with Recurrence in Non-small Cell Lung Cancer Patients After Stereotactic Body Radiotherapy

Overview

Journal Radiat Oncol

Publisher Biomed Central

Specialties Oncology
Radiology

Date 2017 Sep 27

PMID 28946909

Citations 38

Authors

Qian Li

Jongphil Kim

Yoganand Balagurunathan

Jin Qi

Ying Liu

Kujtim Latifi

Eduardo G Moros

Matthew B Schabath

Zhaoxiang Ye

Robert J Gillies

Thomas J Dilling

Affiliations

Soon will be listed here.

Abstract

Background: Predicting recurrence after stereotactic body radiotherapy (SBRT) in non-small cell lung cancer (NSCLC) patients is problematic, but critical for the decision of following treatment. This study aims to investigate the association of imaging features derived from the first follow-up computed tomography (CT) on lung cancer patient outcomes following SBRT, and identify patients at high risk of recurrence.

Methods: Fifty nine biopsy-proven non-small cell lung cancer patients were qualified for this study. The first follow-up CTs were performed about 3 months after SBRT (median time: 91 days). Imaging features included 34 manually scored radiological features (semantics) describing the lesion, lung and thorax and 219 quantitative imaging features (radiomics) extracted automatically after delineation of the lesion. Cox proportional hazard models and Harrel's C-index were used to explore predictors of overall survival (OS), recurrence-free survival (RFS), and loco-regional recurrence-free survival (LR-RFS). Five-fold cross validation was performed on the final prognostic model.

Results: The median follow-up time was 42 months. The model for OS contained Eastern Cooperative Oncology Group (ECOG) performance status (HR = 3.13, 95% CI: 1.17-8.41), vascular involvement (HR = 3.21, 95% CI: 1.29-8.03), lymphadenopathy (HR = 3.59, 95% CI: 1.58-8.16) and the 1st principle component of radiomic features (HR = 1.24, 95% CI: 1.02-1.51). The model for RFS contained vascular involvement (HR = 3.06, 95% CI: 1.40-6.70), vessel attachment (HR = 3.46, 95% CI: 1.65-7.25), pleural retraction (HR = 3.24, 95% CI: 1.41-7.42), lymphadenopathy (HR = 6.41, 95% CI: 2.58-15.90) and relative enhancement (HR = 1.40, 95% CI: 1.00-1.96). The model for LR-RFS contained vascular involvement (HR = 4.96, 95% CI: 2.23-11.03), lymphadenopathy (HR = 2.64, 95% CI: 1.19-5.82), circularity (F13, HR = 1.60, 95% CI: 1.10-2.32) and 3D Laws feature (F92, HR = 1.96, 95% CI: 1.35-2.83). Five-fold cross-validated the areas under the receiver operating characteristic curves (AUC) of these three models were all above 0.8.

Conclusions: Our analysis reveals disease progression could be prognosticated as early as 3 months after SBRT using CT imaging features, and these features would be helpful in clinical decision-making.

Citing Articles

Harnessing Baseline Radiomic Features in Early-Stage NSCLC: What Role in Clinical Outcome Modeling for SBRT Candidates?.

Volpe S, Vincini M, Zaffaroni M, Gaeta A, Raimondi S, Piperno G Cancers (Basel). 2025; 17(5).

PMID: 40075755 PMC: 11899142. DOI: 10.3390/cancers17050908.

Predefined and data-driven CT radiomics predict recurrence-free and overall survival in patients with pulmonary metastases treated with stereotactic body radiotherapy.

Salazar P, Cheung P, Ganeshan B, Oikonomou A PLoS One. 2024; 19(12):e0311910.

PMID: 39739866 PMC: 11687728. DOI: 10.1371/journal.pone.0311910.

Artificial intelligence for chimeric antigen receptor-based therapies: a comprehensive review of current applications and future perspectives.

Shahzadi M, Rafique H, Waheed A, Naz H, Waheed A, Zokirova F Ther Adv Vaccines Immunother. 2024; 12:25151355241305856.

PMID: 39691280 PMC: 11650588. DOI: 10.1177/25151355241305856.

Delta radiomics to track radiation response in lung tumors receiving stereotactic magnetic resonance-guided radiotherapy.

Zha Y, Ye Z, Zapaishchykova A, He J, Hsu S, Leeman J Phys Imaging Radiat Oncol. 2024; 31:100626.

PMID: 39253728 PMC: 11381448. DOI: 10.1016/j.phro.2024.100626.

Prospective external validation of radiomics-based predictive model of distant metastasis after dynamic tumor tracking stereotactic body radiation therapy in patients with non-small-cell lung cancer: A multi-institutional analysis.

Adachi T, Nakamura M, Matsuo Y, Karasawa K, Kokubo M, Sakamoto T J Appl Clin Med Phys. 2024; 25(10):e14475.

PMID: 39178139 PMC: 11466494. DOI: 10.1002/acm2.14475.

References

Vu C, Matthews R, Kim B, Franceschi D, Bilfinger T, Moore W . Prognostic value of metabolic tumor volume and total lesion glycolysis from ¹⁸F-FDG PET/CT in patients undergoing stereotactic body radiation therapy for stage I non-small-cell lung cancer. Nucl Med Commun. 2013; 34(10):959-63. DOI: 10.1097/MNM.0b013e32836491a9. View

Shultz D, Trakul N, Abelson J, Murphy J, Maxim P, Le Q . Imaging features associated with disease progression after stereotactic ablative radiotherapy for stage I non-small-cell lung cancer. Clin Lung Cancer. 2014; 15(4):294-301.e3. DOI: 10.1016/j.cllc.2013.12.011. View

Na F, Wang J, Li C, Deng L, Xue J, Lu Y . Primary tumor standardized uptake value measured on F18-Fluorodeoxyglucose positron emission tomography is of prediction value for survival and local control in non-small-cell lung cancer receiving radiotherapy: meta-analysis. J Thorac Oncol. 2014; 9(6):834-42. PMC: 4219540. DOI: 10.1097/JTO.0000000000000185. View

Baatz M, Zimmermann J, Blackmore C . Automated analysis and detailed quantification of biomedical images using Definiens Cognition Network Technology. Comb Chem High Throughput Screen. 2009; 12(9):908-16. DOI: 10.2174/138620709789383196. View

Gillies R, Kinahan P, Hricak H . Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2015; 278(2):563-77. PMC: 4734157. DOI: 10.1148/radiol.2015151169. View

Dahele M, Palma D, Lagerwaard F, Slotman B, Senan S . Radiological changes after stereotactic radiotherapy for stage I lung cancer. J Thorac Oncol. 2011; 6(7):1221-8. DOI: 10.1097/JTO.0b013e318219aac5. View

Harrell Jr F, Lee K, Mark D . Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996; 15(4):361-87. DOI: 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4. View

Balagurunathan Y, Gu Y, Wang H, Kumar V, Grove O, Hawkins S . Reproducibility and Prognosis of Quantitative Features Extracted from CT Images. Transl Oncol. 2014; 7(1):72-87. PMC: 3998690. DOI: 10.1593/tlo.13844. View

Kessler R, Gasser B, Massard G, Roeslin N, Meyer P, Wihlm J . Blood vessel invasion is a major prognostic factor in resected non-small cell lung cancer. Ann Thorac Surg. 1996; 62(5):1489-93. DOI: 10.1016/0003-4975(96)00540-1. View

10.

Viera A, Garrett J . Understanding interobserver agreement: the kappa statistic. Fam Med. 2005; 37(5):360-3. View

11.

Clarke K, Taremi M, Dahele M, Freeman M, Fung S, Franks K . Stereotactic body radiotherapy (SBRT) for non-small cell lung cancer (NSCLC): is FDG-PET a predictor of outcome?. Radiother Oncol. 2012; 104(1):62-6. DOI: 10.1016/j.radonc.2012.04.019. View

12.

Halpenny D, Ridge C, Hayes S, Zheng J, Moskowitz C, Rimner A . Computed tomographic features predictive of local recurrence in patients with early stage lung cancer treated with stereotactic body radiation therapy. Clin Imaging. 2015; 39(2):254-8. PMC: 4547627. DOI: 10.1016/j.clinimag.2014.12.005. View

13.

Bollineni V, Widder J, Pruim J, Langendijk J, Wiegman E . Residual ¹⁸F-FDG-PET uptake 12 weeks after stereotactic ablative radiotherapy for stage I non-small-cell lung cancer predicts local control. Int J Radiat Oncol Biol Phys. 2012; 83(4):e551-5. DOI: 10.1016/j.ijrobp.2012.01.012. View

14.

Takeda A, Kunieda E, Fujii H, Yokosuka N, Aoki Y, Oooka Y . Evaluation for local failure by 18F-FDG PET/CT in comparison with CT findings after stereotactic body radiotherapy (SBRT) for localized non-small-cell lung cancer. Lung Cancer. 2012; 79(3):248-53. DOI: 10.1016/j.lungcan.2012.11.008. View

15.

Mattonen S, Palma D, Haasbeek C, Senan S, Ward A . Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer. Med Phys. 2014; 41(3):033502. DOI: 10.1118/1.4866219. View

16.

Burdick M, Stephans K, Reddy C, Djemil T, Srinivas S, Videtic G . Maximum standardized uptake value from staging FDG-PET/CT does not predict treatment outcome for early-stage non-small-cell lung cancer treated with stereotactic body radiotherapy. Int J Radiat Oncol Biol Phys. 2010; 78(4):1033-9. DOI: 10.1016/j.ijrobp.2009.09.081. View

17.

Tsuchiya T, Akamine S, Muraoka M, Kamohara R, Tsuji K, Urabe S . Stage IA non-small cell lung cancer: vessel invasion is a poor prognostic factor and a new target of adjuvant chemotherapy. Lung Cancer. 2007; 56(3):341-8. DOI: 10.1016/j.lungcan.2007.01.019. View

18.

Wang H, Schabath M, Liu Y, Berglund A, Bloom G, Kim J . Semiquantitative Computed Tomography Characteristics for Lung Adenocarcinoma and Their Association With Lung Cancer Survival. Clin Lung Cancer. 2015; 16(6):e141-63. PMC: 4609593. DOI: 10.1016/j.cllc.2015.05.007. View

19.

Chang Y, Lin M, Shih J, Wu C, Lee Y . The significance of visceral pleural surface invasion in 321 cases of non-small cell lung cancers with pleural retraction. Ann Surg Oncol. 2012; 19(9):3057-64. DOI: 10.1245/s10434-012-2354-y. View

20.

Huang K, Dahele M, Senan S, Guckenberger M, Rodrigues G, Ward A . Radiographic changes after lung stereotactic ablative radiotherapy (SABR)--can we distinguish recurrence from fibrosis? A systematic review of the literature. Radiother Oncol. 2012; 102(3):335-42. DOI: 10.1016/j.radonc.2011.12.018. View