Morphological computed tomography phenotypes in pulmonary sarcoidosis at diagnosis: splitting and lumping based on predictors of clinical progression
Prerana Agarwal, Louis Jouanjan, Charlott Terschluse, Martin Feineis, Sebastian Wirtz, Daniel Soriano, Paula Kuss, Emil Wachenfeld, Fabian Bamberg, Christopher L. Schlett, Daiana Stolz, Björn C. Frye · 2026
Read Morphological computed tomography phenotypes in pulmonary sarcoidosis at diagnosis: splitting and lumping based on predictors of clinical progression by Prerana Agarwal, Louis Jouanjan, Charlott Terschluse, Martin Feineis, Sebastian Wirtz, Daniel Soriano, Paula Kuss, Emil Wachenfeld, Fabian Bamberg, Christopher L. Schlett, Daiana Stolz, Björn C. Frye (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13573217.txt.
Description
Prerana Agarwal and co-authors sort lung scans in sarcoidosis in a 2026 study. The disease grows small immune lumps in organs, and its lung form varies widely. A recent global consensus proposed scan-based types, but whether those types forecast the disease's course was unknown.
The team reviewed 232 patients with biopsy-proven lung disease treated from 2010 to 2020 at a referral center. Entry scans were grouped by scarring and by nodule patterns, and patients were followed for three years for progression. Testing which types predict decline could spare low-risk patients harsh drugs and push high-risk ones toward earlier treatment.
Catalog record
| CREATOR | Prerana Agarwal, Louis Jouanjan, Charlott Terschluse, Martin Feineis, Sebastian Wirtz, Daniel Soriano, Paula Kuss, Emil Wachenfeld, Fabian Bamberg, Christopher L. Schlett, Daiana Stolz, Björn C. Frye |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 35 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |