000302832 001__ 302832
000302832 005__ 20251006141214.0
000302832 0247_ $$2doi$$a10.1016/j.acra.2025.06.034
000302832 0247_ $$2pmid$$apmid:40640054
000302832 0247_ $$2ISSN$$a1076-6332
000302832 0247_ $$2ISSN$$a1878-4046
000302832 037__ $$aDKFZ-2025-01372
000302832 041__ $$aEnglish
000302832 082__ $$a610
000302832 1001_ $$0P:(DE-He78)e7c860fe438c12cbe5f071b3f86d5738$$aWennmann, Markus$$b0$$eFirst author$$udkfz
000302832 245__ $$aAutomated Detection of Focal Bone Marrow Lesions From MRI: A Multi-center Feasibility Study in Patients with Monoclonal Plasma Cell Disorders.
000302832 260__ $$aPhiladelphia, PA [u.a.]$$bElsevier$$c2025
000302832 3367_ $$2DRIVER$$aarticle
000302832 3367_ $$2DataCite$$aOutput Types/Journal article
000302832 3367_ $$0PUB:(DE-HGF)16$$2PUB:(DE-HGF)$$aJournal Article$$bjournal$$mjournal$$s1759752690_8194
000302832 3367_ $$2BibTeX$$aARTICLE
000302832 3367_ $$2ORCID$$aJOURNAL_ARTICLE
000302832 3367_ $$00$$2EndNote$$aJournal Article
000302832 500__ $$a#EA:E010#LA:E010#LA:E230# / 2025 Oct;32(10):6012-6026
000302832 520__ $$aTo train and test an AI-based algorithm for automated detection of focal bone marrow lesions (FL) from MRI.This retrospective feasibility study included 444 patients with monoclonal plasma cell disorders. For this feasibility study, only FLs in the left pelvis were included. Using the nnDetection framework, the algorithm was trained based on 334 patients with 494 FLs from center 1, and was tested on an internal test set (36 patients, 89 FLs, center 1) and a multicentric external test set (74 patients, 262 FLs, centers 2-11). Mean average precision (mAP), F1-score, sensitivity, positive predictive value (PPV), and Spearman correlation coefficient between automatically determined and actual number of FLs were calculated.On the internal/external test set, the algorithm achieved a mAP of 0.44/0.34, F1-Score of 0.54/0.44, sensitivity of 0.49/0.34, and a PPV of 0.61/0.61, respectively. In two subsets of the external multicentric test set with high imaging quality, the performance nearly matched that of the internal test set, with mAP of 0.45/0.41, F1-Score of 0.50/0.53, sensitivity of 0.44/0.43, and a PPV of 0.60/0.71, respectively. There was a significant correlation between the automatically determined and actual number of FLs on both the internal (r=0.51, p=0.001) and external multicentric test set (r=0.59, p<0.001).This study demonstrates that the automated detection of FLs from MRI, and thereby the automated assessment of the number of FLs, is feasible.
000302832 536__ $$0G:(DE-HGF)POF4-315$$a315 - Bildgebung und Radioonkologie (POF4-315)$$cPOF4-315$$fPOF IV$$x0
000302832 588__ $$aDataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
000302832 650_7 $$2Other$$aAI
000302832 650_7 $$2Other$$aDetection
000302832 650_7 $$2Other$$aFocal lesions
000302832 650_7 $$2Other$$aMonoclonal plasma cell disorders
000302832 650_7 $$2Other$$aMulticenter
000302832 7001_ $$0P:(DE-He78)05779b8fc2a612fdf8364db690f3480c$$aKächele, Jessica$$b1$$udkfz
000302832 7001_ $$0P:(DE-He78)b05a293a4cd1e8f09cdbc953de8ed6d1$$avon Salomon, Arvin$$b2$$udkfz
000302832 7001_ $$0P:(DE-HGF)0$$aNonnenmacher, Tobias$$b3
000302832 7001_ $$0P:(DE-He78)d52d4217d38d20b78d1bc8014e2b0c35$$aBujotzek, Markus$$b4$$udkfz
000302832 7001_ $$0P:(DE-He78)d2bf7126723ea8f6005ba141ea3c3e2c$$aXiao, Shuhan$$b5$$udkfz
000302832 7001_ $$0P:(DE-He78)ec69b596ea6cd55401413c047f15db31$$aMartinez Mora, Andres$$b6$$udkfz
000302832 7001_ $$0P:(DE-He78)743a4a82daab55306a2c88b9f6bf8c2f$$aHielscher, Thomas$$b7$$udkfz
000302832 7001_ $$aHajiyianni, Marina$$b8
000302832 7001_ $$aMenis, Ekaterina$$b9
000302832 7001_ $$0P:(DE-He78)cf4656ab05919cc784af4e9812f5a9fa$$aGrözinger, Martin$$b10$$udkfz
000302832 7001_ $$0P:(DE-He78)adc25b1dbf85abdffe5d2300d1265031$$aBauer, Fabian$$b11
000302832 7001_ $$aRiebl, Veronika$$b12
000302832 7001_ $$0P:(DE-He78)d7135c1486ffd923f71735d40a3d7a0c$$aRotkopf, Lukas Thomas$$b13$$udkfz
000302832 7001_ $$0P:(DE-He78)b542df279437ced507cda1a8c93a2d4d$$aZhang, Kevin Sun$$b14$$udkfz
000302832 7001_ $$aAfat, Saif$$b15
000302832 7001_ $$aBesemer, Britta$$b16
000302832 7001_ $$aHoffmann, Martin$$b17
000302832 7001_ $$aRingelstein, Adrian$$b18
000302832 7001_ $$aGraeven, Ullrich$$b19
000302832 7001_ $$aFedders, Dieter$$b20
000302832 7001_ $$aHänel, Mathias$$b21
000302832 7001_ $$aAntoch, Gerald$$b22
000302832 7001_ $$aFenk, Roland$$b23
000302832 7001_ $$aMahnken, Andreas H$$b24
000302832 7001_ $$aMann, Christoph$$b25
000302832 7001_ $$aMokry, Theresa$$b26
000302832 7001_ $$aRaab, Marc-Steffen$$b27
000302832 7001_ $$aWeinhold, Niels$$b28
000302832 7001_ $$aMai, Elias Karl$$b29
000302832 7001_ $$aGoldschmidt, Hartmut$$b30
000302832 7001_ $$aWeber, Tim Frederik$$b31
000302832 7001_ $$0P:(DE-He78)3e76653311420a51a5faeb80363bd73e$$aDelorme, Stefan$$b32$$udkfz
000302832 7001_ $$0P:(DE-He78)64313331bb3bdc0902ff88697f402c92$$aNeher, Peter$$b33$$udkfz
000302832 7001_ $$0P:(DE-He78)3d04c8fee58c9ab71f62ff80d06b6fec$$aSchlemmer, Heinz-Peter$$b34$$eLast author$$udkfz
000302832 7001_ $$0P:(DE-He78)33c74005e1ce56f7025c4f6be15321b3$$aMaier-Hein, Klaus$$b35$$eLast author$$udkfz
000302832 773__ $$0PERI:(DE-600)2050425-1$$a10.1016/j.acra.2025.06.034$$gp. S1076633225006142$$n10$$p6012-6026$$tAcademic radiology$$v32$$x1076-6332$$y2025
000302832 909CO $$ooai:inrepo02.dkfz.de:302832$$pVDB
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)e7c860fe438c12cbe5f071b3f86d5738$$aDeutsches Krebsforschungszentrum$$b0$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)05779b8fc2a612fdf8364db690f3480c$$aDeutsches Krebsforschungszentrum$$b1$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)b05a293a4cd1e8f09cdbc953de8ed6d1$$aDeutsches Krebsforschungszentrum$$b2$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)d52d4217d38d20b78d1bc8014e2b0c35$$aDeutsches Krebsforschungszentrum$$b4$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)d2bf7126723ea8f6005ba141ea3c3e2c$$aDeutsches Krebsforschungszentrum$$b5$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)ec69b596ea6cd55401413c047f15db31$$aDeutsches Krebsforschungszentrum$$b6$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)743a4a82daab55306a2c88b9f6bf8c2f$$aDeutsches Krebsforschungszentrum$$b7$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)cf4656ab05919cc784af4e9812f5a9fa$$aDeutsches Krebsforschungszentrum$$b10$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)adc25b1dbf85abdffe5d2300d1265031$$aDeutsches Krebsforschungszentrum$$b11$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)d7135c1486ffd923f71735d40a3d7a0c$$aDeutsches Krebsforschungszentrum$$b13$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)b542df279437ced507cda1a8c93a2d4d$$aDeutsches Krebsforschungszentrum$$b14$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)3e76653311420a51a5faeb80363bd73e$$aDeutsches Krebsforschungszentrum$$b32$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)64313331bb3bdc0902ff88697f402c92$$aDeutsches Krebsforschungszentrum$$b33$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)3d04c8fee58c9ab71f62ff80d06b6fec$$aDeutsches Krebsforschungszentrum$$b34$$kDKFZ
000302832 9101_ $$0I:(DE-588b)2036810-0$$6P:(DE-He78)33c74005e1ce56f7025c4f6be15321b3$$aDeutsches Krebsforschungszentrum$$b35$$kDKFZ
000302832 9131_ $$0G:(DE-HGF)POF4-315$$1G:(DE-HGF)POF4-310$$2G:(DE-HGF)POF4-300$$3G:(DE-HGF)POF4$$4G:(DE-HGF)POF$$aDE-HGF$$bGesundheit$$lKrebsforschung$$vBildgebung und Radioonkologie$$x0
000302832 9141_ $$y2025
000302832 915__ $$0StatID:(DE-HGF)0200$$2StatID$$aDBCoverage$$bSCOPUS$$d2025-01-07
000302832 915__ $$0StatID:(DE-HGF)0300$$2StatID$$aDBCoverage$$bMedline$$d2025-01-07
000302832 915__ $$0StatID:(DE-HGF)0199$$2StatID$$aDBCoverage$$bClarivate Analytics Master Journal List$$d2025-01-07
000302832 915__ $$0StatID:(DE-HGF)0160$$2StatID$$aDBCoverage$$bEssential Science Indicators$$d2025-01-07
000302832 915__ $$0StatID:(DE-HGF)1110$$2StatID$$aDBCoverage$$bCurrent Contents - Clinical Medicine$$d2025-01-07
000302832 915__ $$0StatID:(DE-HGF)0113$$2StatID$$aWoS$$bScience Citation Index Expanded$$d2025-01-07
000302832 915__ $$0StatID:(DE-HGF)0150$$2StatID$$aDBCoverage$$bWeb of Science Core Collection$$d2025-01-07
000302832 915__ $$0StatID:(DE-HGF)0100$$2StatID$$aJCR$$bACAD RADIOL : 2022$$d2025-01-07
000302832 915__ $$0StatID:(DE-HGF)9900$$2StatID$$aIF < 5$$d2025-01-07
000302832 9202_ $$0I:(DE-He78)E230-20160331$$kE230$$lE230 Medizinische Bildverarbeitung$$x0
000302832 9202_ $$0I:(DE-He78)E010-20160331$$kE010$$lE010 Radiologie$$x1
000302832 9201_ $$0I:(DE-He78)E230-20160331$$kE230$$lE230 Medizinische Bildverarbeitung$$x0
000302832 9201_ $$0I:(DE-He78)C060-20160331$$kC060$$lC060 Biostatistik$$x1
000302832 9201_ $$0I:(DE-He78)HD01-20160331$$kHD01$$lDKTK HD zentral$$x2
000302832 9201_ $$0I:(DE-He78)E010-20160331$$kE010$$lE010 Radiologie$$x3
000302832 9200_ $$0I:(DE-He78)E010-20160331$$kE010$$lE010 Radiologie$$x0
000302832 980__ $$ajournal
000302832 980__ $$aVDB
000302832 980__ $$aI:(DE-He78)E230-20160331
000302832 980__ $$aI:(DE-He78)C060-20160331
000302832 980__ $$aI:(DE-He78)HD01-20160331
000302832 980__ $$aI:(DE-He78)E010-20160331
000302832 980__ $$aUNRESTRICTED