Szczegóły publikacji
Opis bibliograficzny
Performance of fully automated algorithm detecting bone marrow edema in sacroiliac joints / Joanna Ożga, Michał Wyka, Agata Raczko, Zbisław TABOR, Zuzanna Oleniacz, Michał Korman, Wadim Wojciechowski // Journal of Clinical Medicine [Dokument elektroniczny]. — Czasopismo elektroniczne ; ISSN 2077-0383. — 2023 — vol. 12 iss. 14 art. no. 4852, s. 1–19. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 18–19, Abstr. — Publikacja dostępna online od: 2023-07-24
Autorzy (7)
- Ożga Joanna
- Wyka Michał
- Raczko Agata
- AGHTabor Zbisław
- Oleniacz Zuzanna
- Korman Michał
- Wojciechowski Wadim
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 148820 |
|---|---|
| Data dodania do BaDAP | 2023-11-08 |
| Tekst źródłowy | URL |
| DOI | 10.3390/jcm12144852 |
| Rok publikacji | 2023 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Journal of Clinical Medicine |
Abstract
This study evaluates the performance of a fully automated algorithm to detect active inflammation in the form of bone marrow edema (BME) in iliac and sacral bones, depending on the quality of the coronal oblique plane in patients with axial spondyloarthritis (axSpA). The results were assessed based on the technical correctness of MRI examination of the sacroiliac joints (SIJs). A total of 173 patients with suspected axSpA were included in the study. In order to verify the correctness of the MRI, a deviation angle was measured on the slice acquired in the sagittal plane in the T2-weighted sequence. This angle was located between the line drawn between the posterior edges of S1 and S2 vertebrae and the line that marks the actual plane in which the slices were acquired in T1 and STIR sequences. All examinations were divided into quartiles according to the deviation angle measured in degrees as follows: 1st group [0; 2.2], 2nd group (2.2; 5.7], 3rd group (5.7; 10] and 4th group (10; 29.2]. Segmentations of the sacral and iliac bones were acquired manually and automatically using the fully automated algorithm on the T1 sequence. The Dice coefficient for automated bone segmentations with respect to reference manual segmentations was 0.9820 (95% CI [0.9804, 0.9835]). Examinations of BME lesions were assessed using the SPARCC scale (in 68 cases SPARCC > 0). Manual and automatic segmentations of the lesions were performed on STIR sequences and compared. The sensitivity of detection of BME ranged from 0.58 (group 1) to 0.83 (group 2) versus 0.76 (total), while the specificity was equal to 0.97 in each group. The study indicates that the performance of the algorithm is satisfactory regardless of the deviation angle.
