Incidental Extraspinal Findings at Lumbar Spine Magnetic Resonance Imaging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In Brief Study Design. Retrospective study of a consecutive series of patients undergoing lumbar spine magnetic resonance imaging (MRI) for low back pain at a single institution. Objective. To determine the prevalence and nondetection rate of incidental extraspinal findings (IESFs) in adult patients undergoing MRI of the lumbar spine performed for low back pain by using a structured approach. Summary of Background Data. Extraspinal findings are depicted on lumbar spine magnetic resonance image. There is limited evidence concerning their prevalence, importance, how often they are missed by interpreting physician, and how to improve their detection. Methods. Our study was approved by our institutional review board committee, which waived informed consent because it was retrospective. Lumbar spine magnetic resonance images obtained for low back pain at our institution from January 2011 to December 2013 were assessed by 3 readers for IESFs using a structured approach and their results compared with the archived reports. Repeat lumbar spine MRI and cases with a history of trauma were excluded. A total of 3024 lumbar spine magnetic resonance images were included. IESFs were classified according to the organ involved and to the model adopted by the modified CT Colonography Reporting and Data System (C-RADS). Nondetection rates were determined by comparing the results of our structured approach with the archived MRI reports. Results. A total of 859 IESFs were found in 671 of 3024 lumbar spine patients undergoing MRI (22%). A total of 623 out of them (73%) were categorized E2 (clinically unimportant finding), 192 (22%) were categorized E3 (likely unimportant finding), and 44 (5%) were categorized E4 (potentially important finding). A total of 347 of 859 findings were not mentioned in the archived reports for a nondetection rate of 40%. The nondetection rate for E4 category findings was 38.6% (17/44). Conclusion. IESFs on lumbar spine MRI are common with a significant nondetection rate of 40% using a nonstructured approach. Specifically, there was a significant nondetection rate of 38.6% for potentially important (E4) findings. Level of Evidence: 3 Retrospective study of 3024 patients undergoing lumbar spine magnetic resonance imaging to evaluate the prevalence, importance, nondetection rate of incidental extraspinal findings, and the benefits of reading lumbar spine magnetic resonance images using a structured approach. Extraspinal findings were common. Clinically important findings were missed. Many additional extraspinal findings were identified using a structured approach.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it