Prognostic Implications of the Periaortic Fat Attenuation Index in Uncomplicated Type B Aortic Dissection

Purpose To evaluate the prognostic value of the periaortic fat attenuation index (FAI), which noninvasively captures vascular inflammation on noncontrast CT images, in managing uncomplicated type B aortic dissection (TBAD). Materials and Methods In this retrospective multicenter study (January 2011-December 2022), an automated machine learning algorithm measured periaortic FAI of the descending thoracic aorta at noncontrast CT. Patients who underwent CT for chest or back pain were included to compare FAI between those with acute aortic dissection, including both type A and B, and those without. Further, prognostic evaluation of patients with uncomplicated TBAD was conducted using multivariable Cox proportional hazards regression. Results A total of 688 patients (median age, 69 years [IQR, 56-79]; 400 male patients), including 380 with acute aortic dissection and 308 without, were analyzed for the diagnostic characteristics of FAI, and 135 patients with uncomplicated TBAD (median age, 70 years [IQR, 59-79]; 90 male patients) were followed up for prognosis. FAI values at initial presentation were higher in patients with acute aortic dissection than in those without (median, -74.5 vs -78.7 HU; <i>P</i> < .001). In patients with uncomplicated TBAD, FAI values peaked on the 6th day after onset. These patients were divided into two groups according to the median peak FAI value of -64 HU. During a median follow up of 529 days, those with higher peak FAI values (≥-64 HU) had higher rates of all-cause death and aortic events (log-rank <i>P</i> < .001). High peak FAI independently predicted these events (adjusted hazard ratio, 4.54 [95% CI: 1.69, 12.21]; <i>P</i> = .003). Conclusion A higher peak FAI value was an independent risk factor for adverse events in patients with uncomplicated TBAD. <b>Keywords:</b> Acute Aortic Dissection, Fat Attenuation Index, Noncontrast CT, Perivascular Adipose Tissue, Prognosis UMIN Clinical Trials Registry (AIDFAI study no. UMIN000053435). <i>Supplemental material is available for this article.</i> © The Author(s) 2025. Published by the Radiological Society of North America under a CC BY 4.0 license.

Authors

Institutions

Publication Details

Journal
Radiology Cardiothoracic Imaging
Published
2025-10-01
DOI
https://doi.org/10.1148/ryct.240521
Citations
1
Primary Topic
Aortic Disease and Treatment Approaches
Type
article
Field-Weighted Citation Impact
1.52
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prognostic Implications of the Periaortic Fat Attenuation Index in Uncomplicated Type B Aortic Dissection

Masae Uehara, Hideo Fujita, Shun Nakamura, Naoyuki Kimura et al.
1 citations
Radiology Cardiothoracic Imaging
Aortic Disease and Treatment Approaches
1.52
article

Prognostic Implications of the Periaortic Fat Attenuation Index in Uncomplicated Type B Aortic Dissection

Masae Uehara, Hideo Fujita, Shun Nakamura, Naoyuki Kimura, Tetsuo Ushiku, Hiroyuki Morita, Jiro Sato, Mitsuaki Isobe, Genri Numata, Haruo Yamauchi, Nobuhiko Itoh, Victor Cheng, Tomohiro Iwakura, Atsuko Nakayama, Takuya Kawahara, Yoshiyuki Mizutani, Eiki Takimoto, Issei Komuro, Yusuke Adachi, Hideaki Sowa, Kenichi Sakakura, Atsushi Yamaguchi, Minoru Ōno, Yosuke Inaba, Munetoshi Hinata, Kazutaka Ueda, Nobuo Iguchi, Masaki Hashimoto, Kaori Takada, Yuka Otaki, Masashi Kasao
article en
1 citations

Abstract

Purpose To evaluate the prognostic value of the periaortic fat attenuation index (FAI), which noninvasively captures vascular inflammation on noncontrast CT images, in managing uncomplicated type B aortic dissection (TBAD). Materials and Methods In this retrospective multicenter study (January 2011-December 2022), an automated machine learning algorithm measured periaortic FAI of the descending thoracic aorta at noncontrast CT. Patients who underwent CT for chest or back pain were included to compare FAI between those with acute aortic dissection, including both type A and B, and those without. Further, prognostic evaluation of patients with uncomplicated TBAD was conducted using multivariable Cox proportional hazards regression. Results A total of 688 patients (median age, 69 years [IQR, 56-79]; 400 male patients), including 380 with acute aortic dissection and 308 without, were analyzed for the diagnostic characteristics of FAI, and 135 patients with uncomplicated TBAD (median age, 70 years [IQR, 59-79]; 90 male patients) were followed up for prognosis. FAI values at initial presentation were higher in patients with acute aortic dissection than in those without (median, -74.5 vs -78.7 HU; <i>P</i> < .001). In patients with uncomplicated TBAD, FAI values peaked on the 6th day after onset. These patients were divided into two groups according to the median peak FAI value of -64 HU. During a median follow up of 529 days, those with higher peak FAI values (≥-64 HU) had higher rates of all-cause death and aortic events (log-rank <i>P</i> < .001). High peak FAI independently predicted these events (adjusted hazard ratio, 4.54 [95% CI: 1.69, 12.21]; <i>P</i> = .003). Conclusion A higher peak FAI value was an independent risk factor for adverse events in patients with uncomplicated TBAD. <b>Keywords:</b> Acute Aortic Dissection, Fat Attenuation Index, Noncontrast CT, Perivascular Adipose Tissue, Prognosis UMIN Clinical Trials Registry (AIDFAI study no. UMIN000053435). <i>Supplemental material is available for this article.</i> © The Author(s) 2025. Published by the Radiological Society of North America under a CC BY 4.0 license.

Radiology Cardiothoracic ImagingVol. 7(5)
Abbott Northwestern Hospital (US), Jichi Medical University (JP), Tokyo University of Science (JP), University of Tokyo Hospital (JP), Kanto Central Hospital (JP), Sakakibara Hospital (JP), Tokyo Metropolitan Police Hospital (JP), Jichi Medical University Saitama Medical Center (JP), The University of Tokyo (JP), International University of Health and Welfare (JP)
Openalex Percentile: Top 13%
Aortic Disease and Treatment Approaches
1.52
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.