A Radiomic Model for Risk of Local Recurrence and DFS for T3 and T4 Non-small Cell Lung Cancer

NCT06405815 | Completed

• 1 other identifier: JinlingHospital_lungcancer
• Study Type: observational
• Target: 200
• Locations: 1 country
• Sites: 1

Brief Summary

The investigators retrospectively collected the participants with T3 and T4, N0-2, M0 NSCLC patients resected between January 2013 to December 2021 for training and internal validation. The Clinical data, preoperative laboratory results and images were collected. High-risk margins were defined as R1 or R2 surgical margins or local recurrence during follow-up, and the investigators also collected the disease-free survival time. On the Deepwise multi-modal research platform, the images were semi-automatically segmented and expanded outward by 3mm to obtain the peritumor tissue. PyRadiomics was used to extract the radiomic features. LASSO was used to select the features and tumor radiomics model, peritumor model and combined model were built using 5-fold cross-validation. And it was further tested on the independent cohort. Discrimination was assessed by using the C-index and area under the receiver operating characteristic curve (AUC), sensibility, specificity.

Conditions

Lung Cancer, Nonsmall Cell

Keywords

non-small cell lung cancer; surgical margin; DFS; radiomics

Outcome Measures

Primary Outcomes (1)

• disease free time and recurrence location

  the time from the surgery time to the recurrence time

  until the December 2023

Study Arms (2)

high-risk surgical margin

High-risk margins were defined as R1 or R2 surgical margins or local recurrence during follow-up.

Other: tumor and peritumor radiomic feature

Low-risk surgical margin

Low-risk margins were defined as R0 surgical margin meanwhile arising distant metastasis during follow-up.

Other: tumor and peritumor radiomic feature

Interventions

tumor and peritumor radiomic feature OTHER

extracted the tumor and peritumor radiomic feature from the preoperative enhanced chest CT

Low-risk surgical margin; high-risk surgical margin

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

All T3 and T4 non-small cell lung cancers with surgery, and we retrospectively collected the preoperative enhanced chest CT and the recurrence location and time.

You may qualify if:

• patients with T3 and T4 stage NSCLC；
• available preoperative chest CTE within two weeks of surgery

You may not qualify if:

• inadequate imaging quality resulted from breathing artifact;
• without regularly follow-up information on recurrence location and time

Sponsors & Collaborators

• Jinling Hospital, China: lead

Study Sites (1)

Jinling Hospital

Nanjing, Jiangsu, China

Location

Related Publications (13)

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  PMID: 26101240 BACKGROUND

• Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2016 Feb;278(2):563-77. doi: 10.1148/radiol.2015151169. Epub 2015 Nov 18.

  PMID: 26579733 BACKGROUND

• Huang Y, Liu Z, He L, Chen X, Pan D, Ma Z, Liang C, Tian J, Liang C. Radiomics Signature: A Potential Biomarker for the Prediction of Disease-Free Survival in Early-Stage (I or II) Non-Small Cell Lung Cancer. Radiology. 2016 Dec;281(3):947-957. doi: 10.1148/radiol.2016152234. Epub 2016 Jun 27.

  PMID: 27347764 BACKGROUND

• Yang H, Wang L, Shao G, Dong B, Wang F, Wei Y, Li P, Chen H, Chen W, Zheng Y, He Y, Zhao Y, Du X, Sun X, Wang Z, Wang Y, Zhou X, Lai X, Feng W, Shen L, Qiu G, Ji Y, Chen J, Jiang Y, Liu J, Zeng J, Wang C, Zhao Q, Yang X, Hu X, Ma H, Chen Q, Chen M, Jiang H, Xu Y. A combined predictive model based on radiomics features and clinical factors for disease progression in early-stage non-small cell lung cancer treated with stereotactic ablative radiotherapy. Front Oncol. 2022 Aug 2;12:967360. doi: 10.3389/fonc.2022.967360. eCollection 2022.

  PMID: 35982975 BACKGROUND

• She Y, He B, Wang F, Zhong Y, Wang T, Liu Z, Yang M, Yu B, Deng J, Sun X, Wu C, Hou L, Zhu Y, Yang Y, Hu H, Dong D, Chen C, Tian J. Deep learning for predicting major pathological response to neoadjuvant chemoimmunotherapy in non-small cell lung cancer: A multicentre study. EBioMedicine. 2022 Dec;86:104364. doi: 10.1016/j.ebiom.2022.104364. Epub 2022 Nov 14.

  PMID: 36395737 BACKGROUND

• Sawabata N, Matsumura A, Ohota M, Maeda H, Hirano H, Nakagawa K, Matsuda H; Thoracic Surgery Study Group of Osaka University. Cytologically malignant margins of wedge resected stage I non-small cell lung cancer. Ann Thorac Surg. 2002 Dec;74(6):1953-7. doi: 10.1016/s0003-4975(02)03993-0.

  PMID: 12643379 BACKGROUND

• Akinci D'Antonoli T, Farchione A, Lenkowicz J, Chiappetta M, Cicchetti G, Martino A, Ottavianelli A, Manfredi R, Margaritora S, Bonomo L, Valentini V, Larici AR. CT Radiomics Signature of Tumor and Peritumoral Lung Parenchyma to Predict Nonsmall Cell Lung Cancer Postsurgical Recurrence Risk. Acad Radiol. 2020 Apr;27(4):497-507. doi: 10.1016/j.acra.2019.05.019. Epub 2019 Jul 6.

  PMID: 31285150 BACKGROUND

• Ohguri T, Yahara K, Moon SD, Yamaguchi S, Imada H, Hanagiri T, Tanaka F, Terashima H, Korogi Y. Postoperative radiotherapy for incompletely resected non-small cell lung cancer: clinical outcomes and prognostic value of the histological subtype. J Radiat Res. 2012;53(2):319-25. doi: 10.1269/jrr.11082. Epub 2012 Feb 13.

  PMID: 22327172 RESULT

• Hancock JG, Rosen JE, Antonicelli A, Moreno A, Kim AW, Detterbeck FC, Boffa DJ. Impact of adjuvant treatment for microscopic residual disease after non-small cell lung cancer surgery. Ann Thorac Surg. 2015 Feb;99(2):406-13. doi: 10.1016/j.athoracsur.2014.09.033. Epub 2014 Dec 17.

  PMID: 25528723 RESULT

• Sawabata N, Maeda H, Matsumura A, Ohta M, Okumura M; Thoracic Surgery Study Group of Osaka University. Clinical implications of the margin cytology findings and margin/tumor size ratio in patients who underwent pulmonary excision for peripheral non-small cell lung cancer. Surg Today. 2012 Feb;42(3):238-44. doi: 10.1007/s00595-011-0031-6. Epub 2011 Nov 10.

  PMID: 22072149 RESULT

• Qi LL, Wang JW, Yang L, Huang Y, Zhao SJ, Tang W, Jin YJ, Zhang ZW, Zhou Z, Yu YZ, Wang YZ, Wu N. Natural history of pathologically confirmed pulmonary subsolid nodules with deep learning-assisted nodule segmentation. Eur Radiol. 2021 Jun;31(6):3884-3897. doi: 10.1007/s00330-020-07450-z. Epub 2020 Nov 21.

  PMID: 33219848 RESULT

• Kelsey CR, Marks LB, Hollis D, Hubbs JL, Ready NE, D'Amico TA, Boyd JA. Local recurrence after surgery for early stage lung cancer: an 11-year experience with 975 patients. Cancer. 2009 Nov 15;115(22):5218-27. doi: 10.1002/cncr.24625.

  PMID: 19672942 RESULT

• Zwanenburg A, Vallieres M, Abdalah MA, Aerts HJWL, Andrearczyk V, Apte A, Ashrafinia S, Bakas S, Beukinga RJ, Boellaard R, Bogowicz M, Boldrini L, Buvat I, Cook GJR, Davatzikos C, Depeursinge A, Desseroit MC, Dinapoli N, Dinh CV, Echegaray S, El Naqa I, Fedorov AY, Gatta R, Gillies RJ, Goh V, Gotz M, Guckenberger M, Ha SM, Hatt M, Isensee F, Lambin P, Leger S, Leijenaar RTH, Lenkowicz J, Lippert F, Losnegard A, Maier-Hein KH, Morin O, Muller H, Napel S, Nioche C, Orlhac F, Pati S, Pfaehler EAG, Rahmim A, Rao AUK, Scherer J, Siddique MM, Sijtsema NM, Socarras Fernandez J, Spezi E, Steenbakkers RJHM, Tanadini-Lang S, Thorwarth D, Troost EGC, Upadhaya T, Valentini V, van Dijk LV, van Griethuysen J, van Velden FHP, Whybra P, Richter C, Lock S. The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping. Radiology. 2020 May;295(2):328-338. doi: 10.1148/radiol.2020191145. Epub 2020 Mar 10.

  PMID: 32154773 RESULT

MeSH Terms

Conditions

Carcinoma, Non-Small-Cell Lung; Margins of Excision

Interventions

Tumor Burden

Condition Hierarchy (Ancestors)

Carcinoma, Bronchogenic; Bronchial Neoplasms; Lung Neoplasms; Respiratory Tract Neoplasms; Thoracic Neoplasms; Neoplasms by Site; Neoplasms; Lung Diseases; Respiratory Tract Diseases; Morphological and Microscopic Findings; Pathological Conditions, Signs and Symptoms

Intervention Hierarchy (Ancestors)

Body Weights and Measures; Anthropometry; Investigative Techniques

Study Officials

• Guangming Lu

  Department of Radiology, Jinling Hospital

  STUDY DIRECTOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Director of the Medical Imaging Center of the Jinling Hospital

Study Record Dates

• First Submitted: May 4, 2024
• First Posted: May 8, 2024
• Study Start: January 1, 2021
• Primary Completion: December 31, 2022
• Study Completion: December 31, 2023
• Last Updated: May 9, 2024

Record last verified: 2024-05

Locations

CN (1)