m+Medelevator.RU
← Поиск публикаций
Scientific reports · 2026

Radiomic profiling of chest CT in a cohort of sarcoidosis cases.

СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Carlson Nichole E, Lippitt Wren L, Ryan Sarah M, Mroz Margaret, Barkes Briana, Liao Shu-Yi, Maier Lisa A, Fingerlin Tasha E

Аннотация

Chest high resolution computed tomography (HRCT) is increasingly used in clinical practice for sarcoidosis. Visual assessment (VAS) remains standard even with its high inter- and intra-rater variation. Radiomics may be a less variable assessment. We developed radiomic profiles of HRCT and mapped them to radiologic, functional, and patient reported outcomes. Radiomics were calculated on HRCT for both lungs from sarcoidosis cases enrolled in the Genomic Research in Alpha-1 Antitrypsin Deficiency and Sarcoidosis (GRADS) study (N = 320). Cases were clustered using radiomics profiles via robust and sparse K-means. Differences in VAS by cluster were identified using chi-squared tests. Linear regression investigated how pulmonary function tests (PFT) and patient reported outcomes (PRO) differed between clusters with and without adjustment for other radiologic quantification. Sensitivity analyses were used for validation. Clustering produced four patient groups that were associated with, but did not mimic, Scadding stage and Oberstein score (p < 0.001). One cluster had markedly few abnormalities. Another cluster had consistently more abnormalities and fibrosis. Clusters explained 10-15% of PFT variation and significantly predicted PFT even after accounting for other radiologic findings (p < 0.001). Associations with PRO were less consistent. These findings provide early-stage evidence that radiomics may be a useful component in identifying disease phenotypes.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты