Deep Learning Radiogenomics For Individualized Therapy in Unresectable Gallbladder Cancer
NCT ID: NCT05718115
Last Updated: 2023-02-08
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
75 participants
OBSERVATIONAL
2023-02-15
2023-12-31
Brief Summary
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(i) whether a deep learning radiomics (DLR) model can be used for identification of HER2status and prediction of response to anti-HER2 directed therapy in unresectable GBC.
(ii) validation of the deep learning radiomics (DLR) model for identification of HER2 status and prediction of response to anti-HER2 directed therapy in unresectable GBC.
Participants will be asked to
1. Undergo biopsy of the gallbladder mass after a baseline CT scan
2. Based on the results of the biopsy, patients will be given chemotherapy either targeted (if Her2 positive) or non-targeted
3. Response to treatment will be assessed with a CT scan at 12 weeks of chemotherapy
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Detailed Description
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Conditions
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Study Design
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CASE_ONLY
PROSPECTIVE
Interventions
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CT scan
Biphasic CT scan including arterial phase and portal venous phase after intravenous injection of 80-100 mL of non-ionic iodinated contrast at rate of 4ml/s using pressure injector.
Eligibility Criteria
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Inclusion Criteria
2. Patients willing to give informed consent
Exclusion Criteria
2. Patients with deranged RFTs
3. Patients with contrast allergy
18 Years
70 Years
ALL
No
Sponsors
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Radiological Society of North America
OTHER
Post Graduate Institute of Medical Education and Research, Chandigarh
OTHER
Responsible Party
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Pankaj Gupta
Associate Professor
Principal Investigators
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Pankaj Gupta
Role: PRINCIPAL_INVESTIGATOR
PGIMER, CHANDIGARH
Locations
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Post Graduate Institute of Medical Education and Research
Chandigarh, Punjab, India
Countries
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Central Contacts
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Facility Contacts
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Pankaj Gupta
Role: primary
References
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Boddapati SB, Lal A, Gupta P, Kalra N, Yadav TD, Gupta V, Dass A, Srinivasan R, Singhal M. Contrast enhanced ultrasound versus multiphasic contrast enhanced computed tomography in evaluation of gallbladder lesions. Abdom Radiol (NY). 2022 Feb;47(2):566-575. doi: 10.1007/s00261-021-03364-6. Epub 2021 Dec 7.
Gupta P, Dutta U, Rana P, Singhal M, Gulati A, Kalra N, Soundararajan R, Kalage D, Chhabra M, Sharma V, Gupta V, Yadav TD, Kaman L, Irrinki S, Singh H, Sakaray Y, Das CK, Saikia U, Nada R, Srinivasan R, Sandhu MS, Sharma R, Shetty N, Eapen A, Kaur H, Kambadakone A, de Haas R, Kapoor VK, Barreto SG, Sharma AK, Patel A, Garg P, Pal SK, Goel M, Patkar S, Behari A, Agarwal AK, Sirohi B, Javle M, Garcea G, Nervi F, Adsay V, Roa JC, Han HS. Gallbladder reporting and data system (GB-RADS) for risk stratification of gallbladder wall thickening on ultrasonography: an international expert consensus. Abdom Radiol (NY). 2022 Feb;47(2):554-565. doi: 10.1007/s00261-021-03360-w. Epub 2021 Dec 1.
Rana P, Gupta P, Kalage D, Soundararajan R, Kumar-M P, Dutta U. Grayscale ultrasonography findings for characterization of gallbladder wall thickening in non-acute setting: a systematic review and meta-analysis. Expert Rev Gastroenterol Hepatol. 2022 Jan;16(1):59-71. doi: 10.1080/17474124.2021.2011210. Epub 2022 Jan 17.
Gupta P, Rana P, Ganeshan B, Kalage D, Irrinki S, Gupta V, Yadav TD, Kumar R, Das CK, Gupta P, Endozo R, Nada R, Srinivasan R, Kalra N, Dutta U, Sandhu M. Computed tomography texture-based radiomics analysis in gallbladder cancer: initial experience. Clin Exp Hepatol. 2021 Dec;7(4):406-414. doi: 10.5114/ceh.2021.111173. Epub 2021 Dec 2.
Gupta P, Marodia Y, Bansal A, Kalra N, Kumar-M P, Sharma V, Dutta U, Sandhu MS. Imaging-based algorithmic approach to gallbladder wall thickening. World J Gastroenterol. 2020 Oct 28;26(40):6163-6181. doi: 10.3748/wjg.v26.i40.6163.
Gupta P, Kumar M, Sharma V, Dutta U, Sandhu MS. Evaluation of gallbladder wall thickening: a multimodality imaging approach. Expert Rev Gastroenterol Hepatol. 2020 Jun;14(6):463-473. doi: 10.1080/17474124.2020.1760840. Epub 2020 Apr 30.
Gupta P, Meghashyam K, Marodia Y, Gupta V, Basher R, Das CK, Yadav TD, Irrinki S, Nada R, Dutta U. Locally advanced gallbladder cancer: a review of the criteria and role of imaging. Abdom Radiol (NY). 2021 Mar;46(3):998-1007. doi: 10.1007/s00261-020-02756-4. Epub 2020 Sep 18.
Kalra N, Gupta P, Singhal M, Gupta R, Gupta V, Srinivasan R, Mittal BR, Dhiman RK, Khandelwal N. Cross-sectional Imaging of Gallbladder Carcinoma: An Update. J Clin Exp Hepatol. 2019 May-Jun;9(3):334-344. doi: 10.1016/j.jceh.2018.04.005. Epub 2018 Apr 30.
Javle M, Borad MJ, Azad NS, Kurzrock R, Abou-Alfa GK, George B, Hainsworth J, Meric-Bernstam F, Swanton C, Sweeney CJ, Friedman CF, Bose R, Spigel DR, Wang Y, Levy J, Schulze K, Cuchelkar V, Patel A, Burris H. Pertuzumab and trastuzumab for HER2-positive, metastatic biliary tract cancer (MyPathway): a multicentre, open-label, phase 2a, multiple basket study. Lancet Oncol. 2021 Sep;22(9):1290-1300. doi: 10.1016/S1470-2045(21)00336-3. Epub 2021 Jul 30.
Javle M, Churi C, Kang HC, Shroff R, Janku F, Surapaneni R, Zuo M, Barrera C, Alshamsi H, Krishnan S, Mishra L, Wolff RA, Kaseb AO, Thomas MB, Siegel AB. HER2/neu-directed therapy for biliary tract cancer. J Hematol Oncol. 2015 May 29;8:58. doi: 10.1186/s13045-015-0155-z.
Albrecht T, Rausch M, Roessler S, Geissler V, Albrecht M, Halske C, Seifert C, Renner M, Singer S, Mehrabi A, Vogel MN, Pathil-Warth A, Busch E, Kohler B, Rupp C, Weiss KH, Springfeld C, Rocken C, Schirmacher P, Goeppert B. HER2 gene (ERBB2) amplification is a low-frequency driver with potential predictive value in gallbladder carcinoma. Virchows Arch. 2020 Jun;476(6):871-880. doi: 10.1007/s00428-019-02706-6. Epub 2019 Dec 14.
May M, Raufi AG, Sadeghi S, Chen K, Iuga A, Sun Y, Ahmed F, Bates S, Manji GA. Prolonged Response to HER2-Directed Therapy in Three Patients with HER2-Amplified Metastatic Carcinoma of the Biliary System: Case Study and Review of the Literature. Oncologist. 2021 Aug;26(8):640-646. doi: 10.1002/onco.13800. Epub 2021 May 11.
Other Identifiers
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31875
Identifier Type: -
Identifier Source: org_study_id
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