MRI of the Rectum: A Decade into DISTANCE, Moving to DISTANCED
Bibliographic record
Abstract
Over the past decade, advancements in rectal cancer research have reshaped treatment paradigms. Historically, treatment for locally advanced rectal cancer has focused on neoadjuvant long-course chemoradiotherapy, followed by total mesorectal excision. Interest in organ preservation strategies has been strengthened by the introduction of total neoadjuvant therapy with improved rates of complete clinical response. The administration of systemic induction chemotherapy and consolidation chemoradiotherapy in the neoadjuvant setting has introduced a new dimension to the treatment landscape and patients now face a more intricate decision-making process, given the expanded therapeutic options. This complexity underlines the importance of shared decision-making and brings to light the crucial role of radiologists. MRI, especially high-spatial-resolution T2-weighted imaging, is heralded as the reference standard for rectal cancer management because of its exceptional ability to provide staging and prognostic insights. A key evolution in MRI interpretation for rectal cancer is the transition from the DISTANCE mnemonic to the more encompassing DISTANCED-DIS, distal tumor boundary; T, T stage; A, anal sphincter complex; N, nodal status; C, circumferential resection margin; E, extramural venous invasion; D, tumor deposits. This nuanced shift in the mnemonic captures a wider range of diagnostic indicators. It also emphasizes the escalating role of radiologists in steering well-informed decisions in the realm of rectal cancer care.
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.
How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".