A Radiomic Model for Risk of Local Recurrence and DFS for T3 and T4 Non-small Cell Lung Cancer
Development of a Tumor and Peritumor Radiomics-based Model to Predict the High-risk Surgical Margin and Prognosis of T3 and T4 Non-Small Cell Lung Cancer
Study Overview
Status
Status
Conditions
Conditions
Intervention / Treatment
Intervention / Treatment
Study Type
Study Type
Enrollment (Actual)
Enrollment
Contacts and Locations
Study Locations
-
-
Jiangsu
-
Nanjing, Jiangsu, China
- Jinling Hospital
-
-
Participation Criteria
Eligibility Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Sampling Method
Study Population
Description
Inclusion Criteria:
- patients with T3 and T4 stage NSCLC;
- available preoperative chest CTE within two weeks of surgery
Exclusion Criteria:
- inadequate imaging quality resulted from breathing artifact;
- without regularly follow-up information on recurrence location and time
Study Plan
How is the study designed?
Design Details
Number of groups / cohorts
Cohorts and Interventions
Group / CohortGroup / Cohort |
Intervention / TreatmentIntervention / Treatment |
|---|---|
|
high-risk surgical margin
High-risk margins were defined as R1 or R2 surgical margins or local recurrence during follow-up.
|
extracted the tumor and peritumor radiomic feature from the preoperative enhanced chest CT
|
|
Low-risk surgical margin
Low-risk margins were defined as R0 surgical margin meanwhile arising distant metastasis during follow-up.
|
extracted the tumor and peritumor radiomic feature from the preoperative enhanced chest CT
|
What is the study measuring?
Primary Outcome Measures
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
disease free time and recurrence location
Time Frame: until the December 2023
|
the time from the surgery time to the recurrence time
|
until the December 2023
|
Collaborators and Investigators
Sponsor
Sponsor
Investigators
Investigators
- Study Director: Guangming Lu, Department of Radiology, Jinling Hospital
Publications and helpful links
General Publications
- 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.
- 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.
- 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.
- Wang EH, Corso CD, Rutter CE, Park HS, Chen AB, Kim AW, Wilson LD, Decker RH, Yu JB. Postoperative Radiation Therapy Is Associated With Improved Overall Survival in Incompletely Resected Stage II and III Non-Small-Cell Lung Cancer. J Clin Oncol. 2015 Sep 1;33(25):2727-34. doi: 10.1200/JCO.2015.61.1517. Epub 2015 Jun 22.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Study record dates
Study Major Dates
Study Start (Actual)
Study Start
Primary Completion (Actual)
Primary Completion
Study Completion (Actual)
Study Completion
Study Registration Dates
First Submitted
First Submitted
First Submitted That Met QC Criteria
First Submitted That Met QC Criteria
First Posted (Actual)
First Posted
Study Record Updates
Last Update Posted (Actual)
Last Update Posted
Last Update Submitted That Met QC Criteria
Last Update Submitted That Met QC Criteria
Last Verified
Last Verified
More Information
Terms related to this study
Additional Relevant MeSH Terms
Other Study ID Numbers
Other Study ID Numbers
- JinlingHospital_lungcancer
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.