Evaluate the value of Curved Planar Reconstruction of 3D high-resolution T2WI for the Detection of Deep Infiltrative Endometriosis

In: ISMRM Annual Meeting · 2024 · doi:10.58530/2023/2964 · W4401571746
article OA: closed CC0
Full text JSON View on OpenAlex View at publisher
AI-generated summary by qwen3.7-flash, 2026-09-07

Researchers compared diagnostic accuracy between ordinary and curved planar reconstruction of 3D high-resolution T2WI in 22 deep infiltrative endometriosis patients, finding that curved images improved detection of ectopic lesions in pelvic floor ligaments.

One-sentence paraphrase of the abstract; not a substitute for reading it. No clinical advice. How this works

AI-generated deep summary by qwen3.7-flash, 2026-09-07 · read from full text

This study evaluated the diagnostic accuracy of curved planar reconstruction (CPR) applied to 3D high-resolution T2-weighted imaging for detecting deep infiltrative endometriosis. The researchers compared standard image reconstructions against CPR techniques in a cohort of twenty-two patients with confirmed deep infiltrative disease. Results demonstrated that using curved planar images significantly improved the visualization and detection of ectopic lesions located within various pelvic floor ligaments. This paper is centrally about endometriosis — specifically the radiological assessment and detection of deep infiltrating endometriosis lesions using advanced MRI reconstruction techniques.

Read from the paper's body, not the abstract. Not a substitute for reading the paper. No clinical advice. How this works

Abstract

22 DIE patients were scanned for comparison of diagnostics accuracy between ordinary reconstruction and curved planar reconstruction image of 3D-CS-HR T2WI sequence. Results indicate that Curve images improved the detection of ectopic lesions in each ligament of the pelvic floor.
Full text 1,212 characters · extracted from oa-doi-fallback · 2 sections · click to expand

Abstract

#2964 DOI: https://doi.org/10.58530/2023/2964 Ye Li1, Ailian Liu1, Jiazheng Wang2, and Liangjie Lin2 1The First Affiliated Hospital of Dalian Medical University, Dalian, China, 2Clinical and Technical Support, Philips Healthcare, Beijing, China

Keywords

Pelvis, Image Reconstruction22 DIE patients were scanned for comparison of diagnostics accuracy between ordinary reconstruction and curved planar reconstruction image of 3D-CS-HR T2WI sequence. Results indicate that Curve images improved the detection of ectopic lesions in each ligament of the pelvic floor. How to access this content: For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library. After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library. After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers. Keywords

Text is read by the "Ask this paper" AI Q&A widget below. Extraction quality varies by source — PMC NXML preserves structure cleanly, OA-HTML may include some navigation residue, and OA-PDF can have broken hyphenation. The publisher copy (via DOI) is the canonical version.

My notes (saved in your browser only)

Ask this paper AI returns verbatim quotes from the full text · source: oa-doi-fallback

Answers must be backed by verbatim quotes from this paper's full text. Hallucinated quotes are dropped automatically; if no verbatim passage answers the question, we say so. How this works

Condition tags

endometriosisdie_deep_infiltrating

Citation neighborhood (no data yet)

We don't have any in-corpus citations linked to this paper yet. This is a recent paper (2024) — citers typically take a year or two to land, and the OpenAlex reference graph may still be filling in.

Source provenance

openalex
last seen: 2026-06-10T17:14:06.276822+00:00
unpaywall
last seen: 2026-09-09T06:31:01.691765+00:00
License: CC0 · commercial use OK