Clinical Trials Logo

Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT03648151
Other study ID # 20170501
Secondary ID
Status Completed
Phase
First received
Last updated
Start date January 1, 2010
Est. completion date December 31, 2019

Study information

Verified date July 2020
Source The First Affiliated Hospital of Shanxi Medical University
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

Radiomics is an attractive field in objectively quantifying image features, and may overcome the subjectivity of visually interpreting computed tomography (CT), or positron emission tomography (PET). It is reported that the features related to treatment response, outcomes, tumor staging, tissue identification, and cancer genetics. Therefore, the investigators try to explore the key features for the outcome of lung cancer patients.


Description:

Radiomic Features:

PET/CT images, including other kinds of CT serials, were transported into a personal computer. Using the open source software of 3D-Slicer, volumes of interest (VOIs) for primary tumor, or even lymph nodes, was semi-automatically or manually segmented. And then, radiomic features were extracted.

PET Parameters:

Using combined CT VOIs, corresponding PET standard uptake value (SUV, no unit) were measured. For a foci (either tumor, or lymph node), mean, sum and maximum SUV were documented, and were used for training and validating models alongside radiomic features.

Feature Selection:

Data were analyzed by deep learning or random forests method, and top 20 variables were scored by their contribution to the regression (variable importance, VIMP). The generalized features were identified as the same ones between two kinds of image serials (for example, ordinary and thin-section CT, or PET and CT). Additionally, when three or more features met the criterion, a lower value of Akaike information criterion (AIC) which measures the relative quality of statistical models was used to find appropriate features with lower overfitting possibility.

Model Validation:

The developed model was validated internally and externally. The internal indices for independent continuous variable were accuracy (bias and absolute bias) and precision (correlation coefficient and R square), and that for independent classified or survival variable was c-index. The patients enrolled from another medical center were used for external validation.


Recruitment information / eligibility

Status Completed
Enrollment 1000
Est. completion date December 31, 2019
Est. primary completion date December 31, 2019
Accepts healthy volunteers No
Gender All
Age group N/A and older
Eligibility Inclusion Criteria:

1. Pathologically diagnosed as lung caner.

2. Accepted PET/CT scans at the hospitals either affiliated to Shanxi Medical University or Anhui Medical University

3. Both PET and CT serials can be obtained

4. Can be followed for treatment modalities (including chemotherapy regimens, radiotherapy dose, and et al), survival time and status, and other related information.

Exclusion Criteria:

1. Simultaneously suffering from the cancers from other tissues and organs

2. Have a history of diabetes, chronic heart diseases, or chronic renal failure

Study Design


Related Conditions & MeSH terms


Locations

Country Name City State
China First Affiliated Hospital of Anhui Medical University Hefei Anhui
China First Affiliated Hospital of Shanxi Medical University Taiyuan Shanxi

Sponsors (2)

Lead Sponsor Collaborator
The First Affiliated Hospital of Shanxi Medical University The First Affiliated Hospital of Anhui Medical University

Country where clinical trial is conducted

China, 

References & Publications (6)

Aerts HJ, Velazquez ER, Leijenaar RT, Parmar C, Grossmann P, Carvalho S, Bussink J, Monshouwer R, Haibe-Kains B, Rietveld D, Hoebers F, Rietbergen MM, Leemans CR, Dekker A, Quackenbush J, Gillies RJ, Lambin P. Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach. Nat Commun. 2014 Jun 3;5:4006. doi: 10.1038/ncomms5006. Erratum in: Nat Commun. 2014;5:4644. Cavalho, Sara [corrected to Carvalho, Sara]. — View Citation

Ganeshan B, Skogen K, Pressney I, Coutroubis D, Miles K. Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: preliminary evidence of an association with tumour metabolism, stage, and survival. Clin Radiol. 2012 Feb;67(2):157-64. doi: 10.1016/j.crad.2011.08.012. Epub 2011 Sep 23. — View Citation

Giesel FL, Schneider F, Kratochwil C, Rath D, Moltz J, Holland-Letz T, Kauczor HU, Schwartz LH, Haberkorn U, Flechsig P. Correlation Between SUVmax and CT Radiomic Analysis Using Lymph Node Density in PET/CT-Based Lymph Node Staging. J Nucl Med. 2017 Feb;58(2):282-287. doi: 10.2967/jnumed.116.179648. Epub 2016 Sep 22. — View Citation

Sollini M, Cozzi L, Antunovic L, Chiti A, Kirienko M. PET Radiomics in NSCLC: state of the art and a proposal for harmonization of methodology. Sci Rep. 2017 Mar 23;7(1):358. doi: 10.1038/s41598-017-00426-y. Review. — View Citation

Yip SS, Aerts HJ. Applications and limitations of radiomics. Phys Med Biol. 2016 Jul 7;61(13):R150-66. doi: 10.1088/0031-9155/61/13/R150. Epub 2016 Jun 8. Review. — View Citation

Yip SS, Kim J, Coroller TP, Parmar C, Velazquez ER, Huynh E, Mak RH, Aerts HJ. Associations Between Somatic Mutations and Metabolic Imaging Phenotypes in Non-Small Cell Lung Cancer. J Nucl Med. 2017 Apr;58(4):569-576. doi: 10.2967/jnumed.116.181826. Epub 2016 Sep 29. — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary Overall survival (OS) of lung cancer patients The time from the scan date to death for any reason The patients were followed to December 31, 2019
See also
  Status Clinical Trial Phase
Completed NCT03918538 - A Series of Study in Testing Efficacy of Pulmonary Rehabilitation Interventions in Lung Cancer Survivors N/A
Recruiting NCT05078918 - Comprehensive Care Program for Their Return to Normal Life Among Lung Cancer Survivors N/A
Active, not recruiting NCT04548830 - Safety of Lung Cryobiopsy in People With Cancer Phase 2
Completed NCT04633850 - Implementation of Adjuvants in Intercostal Nerve Blockades for Thoracoscopic Surgery in Pulmonary Cancer Patients
Recruiting NCT06037954 - A Study of Mental Health Care in People With Cancer N/A
Recruiting NCT06006390 - CEA Targeting Chimeric Antigen Receptor T Lymphocytes (CAR-T) in the Treatment of CEA Positive Advanced Solid Tumors Phase 1/Phase 2
Recruiting NCT05583916 - Same Day Discharge for Video-Assisted Thoracoscopic Surgery (VATS) Lung Surgery N/A
Completed NCT00341939 - Retrospective Analysis of a Drug-Metabolizing Genotype in Cancer Patients and Correlation With Pharmacokinetic and Pharmacodynamics Data
Not yet recruiting NCT06376253 - A Phase I Study of [177Lu]Lu-EVS459 in Patients With Ovarian and Lung Cancers Phase 1
Recruiting NCT05898594 - Lung Cancer Screening in High-risk Black Women N/A
Active, not recruiting NCT05060432 - Study of EOS-448 With Standard of Care and/or Investigational Therapies in Participants With Advanced Solid Tumors Phase 1/Phase 2
Active, not recruiting NCT03667716 - COM701 (an Inhibitor of PVRIG) in Subjects With Advanced Solid Tumors. Phase 1
Active, not recruiting NCT03575793 - A Phase I/II Study of Nivolumab, Ipilimumab and Plinabulin in Patients With Recurrent Small Cell Lung Cancer Phase 1/Phase 2
Terminated NCT01624090 - Mithramycin for Lung, Esophagus, and Other Chest Cancers Phase 2
Terminated NCT03275688 - NanoSpectrometer Biomarker Discovery and Confirmation Study
Not yet recruiting NCT04931420 - Study Comparing Standard of Care Chemotherapy With/ Without Sequential Cytoreductive Surgery for Patients With Metastatic Foregut Cancer and Undetectable Circulating Tumor-Deoxyribose Nucleic Acid Levels Phase 2
Recruiting NCT06052449 - Assessing Social Determinants of Health to Increase Cancer Screening N/A
Recruiting NCT06010862 - Clinical Study of CEA-targeted CAR-T Therapy for CEA-positive Advanced/Metastatic Malignant Solid Tumors Phase 1
Not yet recruiting NCT06017271 - Predictive Value of Epicardial Adipose Tissue for Pulmonary Embolism and Death in Patients With Lung Cancer
Recruiting NCT05787522 - Efficacy and Safety of AI-assisted Radiotherapy Contouring Software for Thoracic Organs at Risk