- ICH GCP
- US Clinical Trials Registry
- Klinisk forsøg NCT03198975
Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma
22. juni 2017 opdateret af: Ming Kuang
Development of a Machine Learning-based Model for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma
Microvascular invasion (MVI) has been well demonstrated as an unfavorable prognostic factor for hepatocellular carcinoma (HCC), and patients with MVI have a high risk of tumor recurrence after curative hepatectomy.
Currently, the diagnosis of MVI is determined on the postoperative histologic examination, which greatly limits its influence on preoperative decision making.
Therefore, we constructed this prospective study to develop a machine learning-based model for preoperative prediction of MVI by extracting high-dimensional magnetic resonance (MR) image features.
Studieoversigt
Status
Ukendt
Betingelser
Intervention / Behandling
Detaljeret beskrivelse
Histologically-diagnosed primary HCC after curative hepatectomy.
The magnetic resonance image will be imported into the imaging management software (GE healthcare Analysis-Kit software),and the tumor lesions will manually delineated by two independent radiologists and then reconstruct into three-dimensional images for feature extraction.
The radiomic textural features including grayscale histogram, transform matrix, wavelet transform and filter transformation are automatically extracted by the Analysis-Kit software.The high-throughput extracted features will be then selected by the univariate analysis, and a prediction model will be developed based on machine learning algorithm in a training set in which patients were collected from a retrospective study.
And in the present study, an independent validation set will be collected and used to validate the prediction accuracy of the model.
Undersøgelsestype
Observationel
Tilmelding (Forventet)
40
Kontakter og lokationer
Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.
Studiesteder
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Guangdong
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Guangzhou, Guangdong, Kina, 510080
- Rekruttering
- The First Affiliated Hospital of Sun Yat-sen University
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Kontakt:
- Chen Zebin
- Telefonnummer: +8615017581009
- E-mail: chenzebin_2008@126.com
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Deltagelseskriterier
Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.
Berettigelseskriterier
Aldre berettiget til at studere
18 år til 80 år (Voksen, Ældre voksen)
Tager imod sunde frivillige
Ingen
Køn, der er berettiget til at studere
Alle
Prøveudtagningsmetode
Sandsynlighedsprøve
Studiebefolkning
Between June 2017 and July 2017,all patients who will undergo curative resection (R0 resection) at the First Affiliated Hospital of Sun YatSen University in Guangzhou, China, for HCC based on the modified WHO classification of tumors of the digestive system, are considered for inclusion.
By the eligibility criteria stated below, MVI presentative rate is 30-42% in chinese HCC population as reported, we retrospectively collected about 80 patients for training and an estimated 40 patients will be needed for validation set of this study.
Beskrivelse
Inclusion Criteria:
- Asian patients aged 18~80 years old;
- HCC without macroscopic vascular invasion according to imaging findings;
- Child Pugh A-B stage;
- Receipt of preoperative Gd-EOB-DTPA enhanced MR imaging of the abdomen within one month before surgery;
- Histologically-diagnosed primary HCC after curative hepatectomy;
Exclusion Criteria:
- Combined hepatocellular-cholangiocarcinoma;
- With extra-hepatic metastasis or macrovascular invasion;
- With incomplete clinical and imaging data;
- Non-radical resection;
Studieplan
Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.
Hvordan er undersøgelsen tilrettelagt?
Design detaljer
Kohorter og interventioner
Gruppe / kohorte |
Intervention / Behandling |
---|---|
Preoperative imaging features
In this project, there is only one study group which comprises of patients with Hepatocellular Carcinoma (HCC) who will undergo preoperative Gd-EOB-DTPA enhanced magnetic resonance image.
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Histologically-diagnosed primary HCC after curative hepatectomy.
The magnetic resonance image will be imported into the software ,and the radiomic textural features will be automatically extracted by the Analysis-Kit software.The high-throughput extracted features will be then selected and a prediction model will be developed in the training set in which patients were collected from a retrospective study.
In this project, an independent validation set will be collected and used to validate the prediction accuracy of the model.
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Hvad måler undersøgelsen?
Primære resultatmål
Resultatmål |
Foranstaltningsbeskrivelse |
Tidsramme |
---|---|---|
Presence of microvascular invasion
Tidsramme: Through patient enrollment completion ,an average of 2 years
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Postoperative histologically confirmed microvascular invasion
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Through patient enrollment completion ,an average of 2 years
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Samarbejdspartnere og efterforskere
Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.
Sponsor
Efterforskere
- Studieleder: Ming Kuang, PhD, Department of Liver Surgery, The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
Publikationer og nyttige links
Den person, der er ansvarlig for at indtaste oplysninger om undersøgelsen, leverer frivilligt disse publikationer. Disse kan handle om alt relateret til undersøgelsen.
Generelle publikationer
- 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].
- 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 YQ, Liang CH, He L, Tian J, Liang CS, Chen X, Ma ZL, Liu ZY. Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer. J Clin Oncol. 2016 Jun 20;34(18):2157-64. doi: 10.1200/JCO.2015.65.9128. Epub 2016 May 2. Erratum In: J Clin Oncol. 2016 Jul 10;34(20):2436.
- Zhang YD, Wang Q, Wu CJ, Wang XN, Zhang J, Liu H, Liu XS, Shi HB. The histogram analysis of diffusion-weighted intravoxel incoherent motion (IVIM) imaging for differentiating the gleason grade of prostate cancer. Eur Radiol. 2015 Apr;25(4):994-1004. doi: 10.1007/s00330-014-3511-4. Epub 2014 Nov 28.
- Woo S, Lee JM, Yoon JH, Joo I, Han JK, Choi BI. Intravoxel incoherent motion diffusion-weighted MR imaging of hepatocellular carcinoma: correlation with enhancement degree and histologic grade. Radiology. 2014 Mar;270(3):758-67. doi: 10.1148/radiol.13130444. Epub 2013 Oct 30.
Datoer for undersøgelser
Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.
Studer store datoer
Studiestart (Faktiske)
23. juni 2017
Primær færdiggørelse (Forventet)
31. juli 2017
Studieafslutning (Forventet)
31. juli 2017
Datoer for studieregistrering
Først indsendt
22. juni 2017
Først indsendt, der opfyldte QC-kriterier
22. juni 2017
Først opslået (Faktiske)
26. juni 2017
Opdateringer af undersøgelsesjournaler
Sidste opdatering sendt (Faktiske)
26. juni 2017
Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier
22. juni 2017
Sidst verificeret
1. juni 2017
Mere information
Begreber relateret til denne undersøgelse
Yderligere relevante MeSH-vilkår
Andre undersøgelses-id-numre
- HCC10
Plan for individuelle deltagerdata (IPD)
Planlægger du at dele individuelle deltagerdata (IPD)?
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Disse oplysninger blev hentet direkte fra webstedet clinicaltrials.gov uden ændringer. Hvis du har nogen anmodninger om at ændre, fjerne eller opdatere dine undersøgelsesoplysninger, bedes du kontakte register@clinicaltrials.gov. Så snart en ændring er implementeret på clinicaltrials.gov, vil denne også blive opdateret automatisk på vores hjemmeside .
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