Universität zu Köln

Fervers, Philipp, Fervers, Florian, Kottlors, Jonathan, Lohneis, Philipp, Pollman-Schweckhorst, Philip, Zaytoun, Hasan, Rinneburger, Miriam, Maintz, David and Grosse Hokamp, Nils . Feasibility of artificial intelligence-supported assessment of bone marrow infiltration using dual-energy computed tomography in patients with evidence of monoclonal protein - a retrospective observational study. Eur. Radiol.. NEW YORK: SPRINGER. ISSN 1432-1084

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Abstract

Objectives To demonstrate the feasibility of an automated, non-invasive approach to estimate bone marrow (BM) infiltration of multiple myeloma (MM) by dual-energy computed tomography (DECT) after virtual non-calcium (VNCa) post-processing. Methods Individuals with MM and monoclonal gammopathy of unknown significance (MGUS) with concurrent DECT and BM biopsy between May 2018 and July 2020 were included in this retrospective observational study. Two pathologists and three radiologists reported BM infiltration and presence of osteolytic bone lesions, respectively. Bone mineral density (BMD) was quantified CT-based by a CE-certified software. Automated spine segmentation was implemented by a pre-trained convolutional neural network. The non-fatty portion of BM was defined as voxels > 0 HU in VNCa. For statistical assessment, multivariate regression and receiver operating characteristic (ROC) were conducted. Results Thirty-five patients (mean age 65 +/- 12 years; 18 female) were evaluated. The non-fatty portion of BM significantly predicted BM infiltration after adjusting for the covariable BMD (p = 0.007, r = 0.46). A non-fatty portion of BM > 0.93% could anticipate osteolytic lesions and the clinical diagnosis of MM with an area under the ROC curve of 0.70 [0.49-0.90] and 0.71 [0.54-0.89], respectively. Our approach identified MM-patients without osteolytic lesions on conventional CT with a sensitivity and specificity of 0.63 and 0.71, respectively. Conclusions Automated, AI-supported attenuation assessment of the spine in DECT VNCa is feasible to predict BM infiltration in MM. Further, the proposed method might allow for pre-selecting patients with higher pre-test probability of osteolytic bone lesions and support the clinical diagnosis of MM without pathognomonic lesions on conventional CT.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Fervers, Philipp UNSPECIFIED UNSPECIFIED UNSPECIFIED Fervers, Florian UNSPECIFIED UNSPECIFIED UNSPECIFIED Kottlors, Jonathan UNSPECIFIED UNSPECIFIED UNSPECIFIED Lohneis, Philipp UNSPECIFIED UNSPECIFIED UNSPECIFIED Pollman-Schweckhorst, Philip UNSPECIFIED UNSPECIFIED UNSPECIFIED Zaytoun, Hasan UNSPECIFIED UNSPECIFIED UNSPECIFIED Rinneburger, Miriam UNSPECIFIED UNSPECIFIED UNSPECIFIED Maintz, David UNSPECIFIED UNSPECIFIED UNSPECIFIED Grosse Hokamp, Nils UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-577368
DOI:	10.1007/s00330-021-08419-2
Journal or Publication Title:	Eur. Radiol.
Publisher:	SPRINGER
Place of Publication:	NEW YORK
ISSN:	1432-1084
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language VIRTUAL NONCALCIUM TECHNIQUE; MINERAL DENSITY; DIAGNOSTIC-ACCURACY; MULTIPLE-MYELOMA; RADIOMICS; FRACTURES; STRATEGIES; SYSTEM; SPINE Multiple languages Radiology, Nuclear Medicine & Medical Imaging Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/57736