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Record W4237520672 · doi:10.5858/133.9.1362.a

Coronal Serial Sequential Sampling of Breast Specimen in the Assessment of the Extent of Ductal Carcinoma In Situ

2009· article· en· W4237520672 on OpenAlexaff
William A. Stinson, Bruce F. Burns

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2009
Typearticle
Languageen
FieldMedicine
TopicRadiomics and Machine Learning in Medical Imaging
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsCoronal planeMastectomyDuctal carcinomaFrozen section procedureMedicineRadiologyIn situPathologyBreast cancerCancerPhysicsInternal medicine

Abstract

fetched live from OpenAlex

To the Editor.—We read with interest the articles of Dadmanesh et al1 and Grin et al.2 As pointed out by the authors, the extent of ductal carcinoma in situ (DCIS) is an important prognostic factor for local recurrence after segmental resection. As noted, the method of measurement based on the mammographic findings is often inaccurate. Measuring directly from the slide is appropriate if the lesion is present in its entirety on a single slide. This is usually not the case, however, and there is as yet no standard method for measuring the extent of disease in more extensive lesions. The authors compared the number of involved blocks method with the “gold standard” method, in which specimens were serially sectioned perpendicular to the long axis of the specimen and then submitted in toto. Sectioning breast mastectomy and segmental specimens using this technique tends to divide the region of DCIS involvement into multiple segments. We believe this makes the measurement of the size of DCIS more difficult and prone to error.As reported in our previous studies, we have had occasion to examine breast specimens (both mastectomy and segmental resection) by coronal sectioning (ie, parallel to the chest wall).3–6 In this technique, each sequential section had a thickness of 5 mm and resulted in the largest surface possible per slice. The grossly suspicious regions of these large coronal sections were submitted for microscopic examination by dividing the area in a grid pattern. When cut this way, the tissue blocks were also in the coronal plane. The assembled glass slides from each plane of coronal section will likely represent the largest section of DCIS in that plane of section. When no gross lesion is discernable, the sampling of multiple regions without destroying the anatomic relationship of the remaining tissue is possible when the sections are large and intact. This facilitates revisiting the gross specimen to take additional samples from regions of microscopic involvement.Ductal carcinoma in situ is a preinvasive malignant lesion typically involving the one major duct and its branches, as demonstrated by a 3-dimensional study.3 The process most often involves the duct system by continuous or discontinuous spread (with skipped areas of uninvolved duct) along the duct and its attributor branches and acini. Occasionally, DCIS involves more than one duct system, thought to be due to either true multicentric origins or via spread to the nipple skin and secondary extension into other duct system.We believe that coronal serial sequential sampling offers the following advantages:With respect to the superficial and deep resection margins not visualized in a coronal plane, serial sections perpendicular to the inked resection margins of all suspicious areas should be taken.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0030.001
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0030.003

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.

Opus teacher head0.015
GPT teacher head0.320
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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