Universität zu Köln

Mueller, Lukas, Kloeckner, Roman, Maehringer-Kunz, Aline, Stoehr, Fabian, Dueber, Christoph, Arnhold, Gordon, Gairing, Simon Johannes, Foerster, Friedrich, Weinmann, Arndt, Galle, Peter Robert, Mittler, Jens, dos Santos, Daniel Pinto and Hahn, Felix (2022). Fully automated AI-based splenic segmentation for predicting survival and estimating the risk of hepatic decompensation in TACE patients with HCC. Eur. Radiol., 32 (9). S. 6302 - 6314. NEW YORK: SPRINGER. ISSN 1432-1084

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Abstract

Objectives Splenic volume (SV) was proposed as a relevant prognostic factor for patients with hepatocellular carcinoma (HCC). We trained a deep-learning algorithm to fully automatically assess SV based on computed tomography (CT) scans. Then, we investigated SV as a prognostic factor for patients with HCC undergoing transarterial chemoembolization (TACE). Methods This retrospective study included 327 treatment-naive patients with HCC undergoing initial TACE at our tertiary care center between 2010 and 2020. A convolutional neural network was trained and validated on the first 100 consecutive cases for spleen segmentation. Then, we used the algorithm to evaluate SV in all 327 patients. Subsequently, we evaluated correlations between SV and survival as well as the risk of hepatic decompensation during TACE. Results The algorithm showed Sorensen Dice Scores of 0.96 during both training and validation. In the remaining 227 patients assessed with the algorithm, spleen segmentation was visually approved in 223 patients (98.2%) and failed in four patients (1.8%), which required manual re-assessments. Mean SV was 551 ml. Survival was significantly lower in patients with high SV (10.9 months), compared to low SV (22.0 months, p = 0.001). In contrast, overall survival was not significantly predicted by axial and craniocaudal spleen diameter. Furthermore, patients with a hepatic decompensation after TACE had significantly higher SV (p < 0.001). Conclusion Automated SV assessments showed superior survival predictions in patients with HCC undergoing TACE compared to two-dimensional spleen size estimates and identified patients at risk of hepatic decompensation. Thus, SV could serve as an automatically available, currently underappreciated imaging biomarker.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Mueller, Lukas UNSPECIFIED UNSPECIFIED UNSPECIFIED Kloeckner, Roman UNSPECIFIED UNSPECIFIED UNSPECIFIED Maehringer-Kunz, Aline UNSPECIFIED UNSPECIFIED UNSPECIFIED Stoehr, Fabian UNSPECIFIED UNSPECIFIED UNSPECIFIED Dueber, Christoph UNSPECIFIED UNSPECIFIED UNSPECIFIED Arnhold, Gordon UNSPECIFIED UNSPECIFIED UNSPECIFIED Gairing, Simon Johannes UNSPECIFIED UNSPECIFIED UNSPECIFIED Foerster, Friedrich UNSPECIFIED UNSPECIFIED UNSPECIFIED Weinmann, Arndt UNSPECIFIED UNSPECIFIED UNSPECIFIED Galle, Peter Robert UNSPECIFIED UNSPECIFIED UNSPECIFIED Mittler, Jens UNSPECIFIED UNSPECIFIED UNSPECIFIED dos Santos, Daniel Pinto UNSPECIFIED UNSPECIFIED UNSPECIFIED Hahn, Felix UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-671882
DOI:	10.1007/s00330-022-08737-z
Journal or Publication Title:	Eur. Radiol.
Volume:	32
Number:	9
Page Range:	S. 6302 - 6314
Date:	2022
Publisher:	SPRINGER
Place of Publication:	NEW YORK
ISSN:	1432-1084
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language BEAD TRANSARTERIAL CHEMOEMBOLIZATION; HEPATOCELLULAR-CARCINOMA PATIENTS; VOLUME Multiple languages Radiology, Nuclear Medicine & Medical Imaging Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/67188