Objectives: Our study used a radiomics method to differentiate bone marrow signal abnormality (BMSA) between Charcot neuroarthropathy (CN) and osteomyelitis (OM). Materials and Method: The records of 166 patients with diabetic foot suspected CN or OM between January 2020 and March 2022 were retrospectively examined. A total of 41 patients with BMSA on MRI were included in this study. The diagnosis of OM was confirmed histologically in 24 of 41 patients. We clinically followed 17 patients as CN with laboratory tests. We also included 29 nondiabetic patients with traumatic (TR) BMSA on MRI as the third group. Contours of all BMSA on T1 and T2-weighted images in three patient groups were segmented semi-automatically on ManSeg (v.2.7d). The T1 and T2 features of three groups in radiomics were statistically evaluated. We applied multi-class classification (MCC) and binary-class classification (BCC) methodology to compare classification results. Results: For MCC, the accuracy of Multi-Layer Perceptron (MLP) was 76.92% and 84.38% for T1 and T2, respectively. According to BCC, for CN, OM and TR BMSA, the sensitivity of MLP is 74%, 89.23%, and 76.19% for T1, and 90.57%, 85.92%, 86.81% for T2, respectively. For CN, OM, and TR BMSA, the specificity of MLP is 89.16%, 87.57%, and 90.72% for T1 and 93.55%, 89.94%, and 90.48% for T2 images, respectively. Conclusion: In the diabetic foot, the radiomics method can differentiate the BMSA of CN and OM with high accuracy. Advances in knowledge: The radiomics method can differentiate the BMSA of CN and OM with high accuracy.
Yazar |
Gökalp Tulum |
Yayın Türü | Makale |
Tek Biçim Adres | https://hdl.handle.net/20.500.14081/1904 |
Konu Başlıkları |
Charcot
neuroarthropathy osteomyelitis diabetic foot radiomics |
Koleksiyonlar |
Fakülteler Mühendislik Fakültesi |
Dergi | The British journal of radiology |
Sayfalar | 1 - 11 |
Yayın Yılı | 2023 |
Eser Adı [dc.title] | Radiomics method in the differential diagnosis of diabetic foot osteomyelitis and charcot neuroarthropathy |
Yazar [dc.contributor.author] | Gökalp Tulum |
Yayın Yılı [dc.date.issued] | 2023 |
Yayın Türü [dc.type] | Makale |
Özet [dc.description.abstract] | Objectives: Our study used a radiomics method to differentiate bone marrow signal abnormality (BMSA) between Charcot neuroarthropathy (CN) and osteomyelitis (OM). Materials and Method: The records of 166 patients with diabetic foot suspected CN or OM between January 2020 and March 2022 were retrospectively examined. A total of 41 patients with BMSA on MRI were included in this study. The diagnosis of OM was confirmed histologically in 24 of 41 patients. We clinically followed 17 patients as CN with laboratory tests. We also included 29 nondiabetic patients with traumatic (TR) BMSA on MRI as the third group. Contours of all BMSA on T1 and T2-weighted images in three patient groups were segmented semi-automatically on ManSeg (v.2.7d). The T1 and T2 features of three groups in radiomics were statistically evaluated. We applied multi-class classification (MCC) and binary-class classification (BCC) methodology to compare classification results. Results: For MCC, the accuracy of Multi-Layer Perceptron (MLP) was 76.92% and 84.38% for T1 and T2, respectively. According to BCC, for CN, OM and TR BMSA, the sensitivity of MLP is 74%, 89.23%, and 76.19% for T1, and 90.57%, 85.92%, 86.81% for T2, respectively. For CN, OM, and TR BMSA, the specificity of MLP is 89.16%, 87.57%, and 90.72% for T1 and 93.55%, 89.94%, and 90.48% for T2 images, respectively. Conclusion: In the diabetic foot, the radiomics method can differentiate the BMSA of CN and OM with high accuracy. Advances in knowledge: The radiomics method can differentiate the BMSA of CN and OM with high accuracy. |
Açık Erişim Tarihi [dc.date.available] | 2023-05-12 |
Yayıncı [dc.publisher] | British Institute of Radiology |
Dil [dc.language.iso] | İngilizce |
Konu Başlıkları [dc.subject] | Charcot |
Konu Başlıkları [dc.subject] | neuroarthropathy |
Konu Başlıkları [dc.subject] | osteomyelitis |
Konu Başlıkları [dc.subject] | diabetic foot |
Konu Başlıkları [dc.subject] | radiomics |
Tek Biçim Adres [dc.identifier.uri] | https://hdl.handle.net/20.500.14081/1904 |
Dergi [dc.relation.journal] | The British journal of radiology |
Esere Katkı Sağlayan [dc.contributor.other] | Ferhat Cuce |
Esere Katkı Sağlayan [dc.contributor.other] | Kerim Bora Yılmaz |
Esere Katkı Sağlayan [dc.contributor.other] | Onur Osman |
Esere Katkı Sağlayan [dc.contributor.other] | Ayse Aralasmak |
DOI [dc.identifier.doi] | 10.1259/bjr.20220758 |
Orcid [dc.identifier.orcid] | 0000-0003-1906-0401 |
Bitiş Sayfası [dc.identifier.endpage] | 11 |
Başlangıç Sayfası [dc.identifier.startpage] | 1 |