Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics.
Purpose: To test radiomics for prognostication of intrahepatic mass-forming cholangiocarcinoma (IMCC) and to develop a comprehensive risk model. Methods: Histologically proven IMCC (representing the full range of stages) were retrospectively analyzed by volume segmentation on baseline hepatic venous...
| Publicado en: | Abdominal Radiology Vol. 46; no. 10; pp. 4689 - 4701 |
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| Autores principales: | , , , , , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Oct2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=152397981&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 152397981 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 2366004X JT14 jtl: Abdominal Radiology issn: 2366004X maglogo: N pubinfo: dt: Oct2021 vid: 46 iid: 10 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 152397981 151075475 10.1007/s00261-021-03183-9 152397981 ppf: 4689 ppct: 12 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Integrated prognostication of intrahepatic cholangiocarcinoma by contrast-enhanced computed tomography: the adjunct yield of radiomics. aug: au: Silva, Mario Maddalo, Michele Leoni, Eleonora Giuliotti, Sara Milanese, Gianluca Ghetti, Caterina Biasini, Elisabetta De Filippo, Massimo Missale, Gabriele Sverzellati, Nicola affil: Department of Medicine and Surgery (DiMeC), University of Parma, Via Gramsci 14, Parma, Italy sug: ab: Purpose: To test radiomics for prognostication of intrahepatic mass-forming cholangiocarcinoma (IMCC) and to develop a comprehensive risk model. Methods: Histologically proven IMCC (representing the full range of stages) were retrospectively analyzed by volume segmentation on baseline hepatic venous phase computed tomography (CT), by two readers with different experience (R1 and R2). Morphological CT features included: tumor size, hepatic satellite lesions, lymph node and distant metastases. Radiomic features (RF) were compared across CT protocols and readers. Univariate analysis against overall survival (OS) warranted ranking and selection of RF into radiomic signature (RSign), which was dichotomized into high and low-risk strata (RSign*). Models without and with RSign* (Model 1 and 2, respectively) were compared. Results: Among 78 patients (median follow-up 262 days, IQR 73–957), 62/78 (79%) died during the study period, 46/78 (59%) died within 1 year. Up to 10% RF showed variability across CT protocols; 37/108 (34%) RF showed variability due to manual segmentation. RSign stratified OS (univariate: HR 1.37 for R1, HR 1.28 for R2), RSign* was different between readers (R1 0.39; R2 0.57). Model 1 showed AUC 0.71, which increased in Model 2: AUC 0.81 (p < 0.001) and AIC 89 for R1, AUC 0.81 (p = 0.001) and AIC 90.2 for R2. Conclusion: The use of RF into a unified RSign score stratified OS in patients with IMCC. Dichotomized RSign* classified survival strata, its inclusion in risk models showed adjunct yield. The cut-off value of RSign* was different between readers, suggesting that the use of reference values is hampered by interobserver variability. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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