Differentiation of physiologic versus pathologic basal septal fibrosis: Proposed diagnostic criteria and associations with clinical and CMR-based markers of cardiovascular disease
Bibliographic record
Abstract
Abnormal late gadolinium enhancement (LGE) is commonly identified in the basal septum of patients with dilated cardiomyopathy, hypertrophic cardiomyopathy and sarcoidosis, and has been associated with major adverse events. However, basal septal LGE may also be seen in otherwise normal individuals (Figure 1 ) and may be "physiologic". No diagnostic criteria to differentiate the latter have been established, and both its prevalence and clinical significance remain uncertain. In this study we propose such criteria and examine its prevalence and association with markers of cardiovascular disease. (A) Apical long axis 3-chamber late gadolinium enhancement (LGE) image in a patient with "physiologic basal septal LGE" according to the criteria of; (1) direct contact with the aortic root, and (2) decreasing signal intensity apically . (B) Basal short axis view with mid myocardial late gadolinium enhancement. A total of 615 consecutive LGE CMR studies were evaluated. Patients with prior valvular surgery (n = 91) or congenital heart disease (n = 94) were excluded, resulting in 430 studies. All were blindly scored for the presence of "physiologic septal LGE" according to pre-defined criteria, as follows; (1) LGE in direct contact with the aortic root, AND (2) decreasing in signal intensity towards the apex (see Figure 1 ). Baseline clinical and CMR-based measures of structural heart disease, inclusive of total LGE volume (> 5SD threshold) were compared between those with and without diagnostic criteria being met. Mean age and LVEF of the entire population were 55.8 ± 14.5 years and 49.1 ± 21.7%, respectively. A total of 73 patients (20.4%) met criteria for "physiologic basal septal LGE". As shown in Table 1 no association of this finding with any other clinical or CMR markers of cardiovascular disease was identified. The only identified difference identified among those with the finding was a slightly higher LV ejection fraction (53.8 ± 19.4 vs. 48.1 ± 22.2, p = 0.045) and age at time of imaging (59.2 ± 12.7 vs. 55.1 ± 14.9, p = 0.030). No association was seen between the presence of "physiologic basal septal LGE" and total LGE (inclusive of all patterns of disease), measuring 10.9 ± 14.3% by signal-threshold based quantification. By comparison, those patients having basal septal LGE but not meeting "physiologic" criteria showed a significantly lower mean LVEF of (30.2 ± 14.6% (p < 0.001) and higher total burden of LGE (13.4 ± 14.9%, p = 0.025). A similar prevalence of "physiologic basal septal LGE" was found in a population of 35 healthy volunteers. Among a large CMR referral population "physiologic basal septal LGE" was identified in 20% of all patients. This finding does not show association with any clinical or CMR-based marker of cardiovascular disease. While outcome-based studies are both preferred and required, the proposed criteria for "physiologic basal septal LGE" provides a practical tool for the differentiation of benign versus pathologic septal LGE in patients referred for CMR.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".