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Standardization of Nodal Counting in the Obturator Fossa of Cadaveric Specimens

2016· article· en· W4389033963 on OpenAlexaffabout
Tyler S. Beveridge, Marjorie Johnson, Nicholas Power, Brian L. Allman

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicColorectal Cancer Surgical Treatments
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsLymphatic systemMedicineLymphadenectomyNODALLymph nodeAnatomyLymphCadaveric spasmRadiologyPathology

Abstract

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It is well accepted that the total number of lymph nodes removed during pelvic lymphadenectomy increases the accuracy of cancer staging, possibly improving the long‐term survival of patients. Because of this, the nodal count has been adopted as a measure of surgical performance; however, this presupposes that nodal counting is a reproducible and standardized process. At present, reported nodal counts are extremely variable, and inconsistency between institutions is common because of differing operational protocols. Furthermore, significant inter‐ and intra‐observer variability between pathologists at the same/similar institutions is common because it is not unanimously agreed whether non‐capsulated lymphoid aggregates (lymphatic nodules) should be considered in the total nodal count. Despite the disparate variations reported in the literature, it is our hypothesis that standardized lymphoid tissue counts can be achieved when evaluating: (1) the gross distribution of lymphatic elements (nodes and/or aggregations) within the tissue; (2) the number of capsulated nodes; and/or (3) the number of non‐capsulated lymphoid aggregations. To achieve this, we examined the distribution and number of all organized lymphatic elements present in the obturator fossa (bordered by the external iliac vein, superior; obturator nerve, inferior; pelvic brim and obturator internus, lateral; confluence of the common iliac vein, cranial; and the lymph node of Cloquet, caudal) of human cadavers with no known history of pelvic disease. Counts were obtained by gross evaluation of left (n=5) and right (n=5) obturator fossae tissue packets that had been removed en bloc and subjected to fat clearing with xylene. In order to confirm the gross identification of lymph nodes versus lymphoid aggregations, six samples were examined microscopically after being stained with Haematoxylin and Eosin (H&E) using standard histological protocols. Gross examination revealed the lymphatic elements were typically organized into three regions of the tissue packet: a small round collection at the cranial and caudal aspects, in addition to a large, elongated collection within the central portion. Despite a consistent topographic distribution, the total count (lymph nodes and lymphoid aggregations) demonstrate that the obturator fossa packet contains a varying number of lymphoid elements [overall mean = 7.1 ± 3.2; left mean = 8.8 ± 3.2; right mean = 5.4 ± 2.3], ranging from 3 to 13. Moreover, the number of lymphoid elements between sides was not correlated (r= −0.16; p>0.05). Standard H&E staining revealed four capsulated lymph nodes and two non‐capsulated lymphoid aggregations that were not distinguishable from one another by gross anatomic features. Given this result, additional histology will be completed on the remaining samples to quantify the number of lymph nodes versus lymphoid aggregations. Importantly, the present study has identified consistencies in the gross anatomical appearance of the lymphatic tissue within the obturator fossa despite inconsistent total nodal counts. Our future work is directed at gross and histological identification/differentiation of capsulated lymph nodes from non‐capsulated lymphoid aggregations present in the obturator fossa. Support or Funding Information Frederick Banting and Charles Best Canada Graduate Scholarship Doctoral Awards (CGS‐D)

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)0.003
metaresearch head score (Gemma)0.003
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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.020
GPT teacher head0.277
Teacher spread0.257 · 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".

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Citations0
Published2016
Admission routes2
Has abstractyes

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