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Record W3206265812 · doi:10.5858/arpa.2021-0234-le

Fibroblast Foci and Patchy Fibrosis Do Not Separate Usual Interstitial Pneumonia From Fibrotic Hypersensitivity Pneumonitis in Transbronchial Cryobiopsies

2021· letter· en· W3206265812 on OpenAlexaff
Andrew Churg, Christopher J. Ryerson

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2021
Typeletter
Languageen
FieldMedicine
TopicInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis
Canadian institutionsSt. Paul's HospitalVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsUsual interstitial pneumoniaHypersensitivity pneumonitisMedicinePathologyFibrosisIdiopathic pulmonary fibrosisSarcoidosisMetaplasiaContext (archaeology)PulmonologistsPulmonary fibrosisBiopsyGiant cellExtrinsic Allergic AlveolitisLung biopsyLungBiologyInternal medicine

Abstract

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To the Editor.—Although many pulmonologists are adopting transbronchial cryobiopsy, there is a remarkable dearth of information on the specific pathologic features used to diagnose various forms of interstitial lung disease in such specimens. Cooper et al1 have recently published pathologic criteria for usual interstitial pneumonia (UIP); they suggest that the combination of fibroblast foci and patchy fibrosis, along with the absence of features suggesting an alternative diagnosis, strongly support a diagnosis of UIP in a cryobiopsy.We2 reported in Archives of Pathology & Laboratory Medicine an in-silico exercise in which we created “cryobiopsies” by outlining multiple circles on the pathology slides of 15 video-assisted thoracoscopic surgery (VATS) biopsies from cases that had been given a 60% or greater probability of fibrotic hypersensitivity pneumonitis (fibrotic HP) during a specialty devised multidisciplinary discussion exercise.3 We found a low probability of detecting granulomas or giant cells, features acknowledged to be markers in this context of fibrotic HP and not UIP. However, the probability of finding peribronchiolar metaplasia affecting 50% or greater of bronchioles, a feature that also supports a diagnosis of fibrotic HP,3 was considerably higher, and the frequency of these features within an individual case generally increased with increasing numbers of “cryobiopsies.”Here, we went back to our previously used VATS biopsy slides and asked whether the features described by Cooper et al1 as favoring a diagnosis of UIP could be found in our fibrotic HP-derived “cryobiopsies.” We used the same “cryobiopsies” previously selected for analysis of granulomas/giant cells and peribronchiolar metaplasia, and counted the number of samples showing fibroblast foci, and patchy fibrosis in 1 to 8 “cryobiopsies” for each case; these features had not been evaluated in our previous study.2 For comparison, the total biopsy area of 86.4 mm2 for 4 of our “cryobiopsies” is identical to the mean total area of 87 mm2 reported in the COLDICE study.4Results are shown in the Table. Fibroblast foci were frequently found, from 8 of 15 (53%) cases if a single “cryobiopsy” was evaluated for each case, to 12 of 15 (80%) if 4 biopsies were evaluated, and 12 of 13 (92%) with 8 biopsies (2 cases did not have enough VATS biopsy area to create 8 “cryobiopsies”). Patchy fibrosis ranged from 4 of 15 (27%) single biopsies, to 8 of 15 (53%) with 4 biopsies, and 12 of 13 (92%) with 8 biopsies. The combination of fibroblast foci and patchy fibrosis was found in 1 of 15 (6.7%) cases with a single biopsy and increased to 7 of 15 (47%) cases when 4 biopsies were reviewed and 10 of 13 (77%) with 8 biopsies, suggesting the potential to misclassify almost half of fibrotic HP biopsies as UIP with 4 biopsies and the majority of patients with 8 biopsies using these criteria alone. This situation is improved by also looking for giant cells/granulomas or peribronchiolar metaplasia affecting more than 50% of bronchioles, but still leaves a significant number of fibrotic HP cases misclassified as UIP (Table).This is obviously a small series that uses a somewhat artificial system. Nonetheless, these data emphasize the idea that a combination of fibroblast foci and patchy fibrosis is a feature not only of UIP but also of fibrotic HP, and used by themselves, these features will lead to misclassification of a proportion of fibrotic HP cases as UIP.Although it may be surprising to nonspecialist pathologists (and to many clinicians), the exact pathologic features that define UIP, even in VATS biopsies, are not universally agreed upon, as discussed in detail in 2 recent position papers,5,6 and this is a problem that needs to be addressed. That being so, it is even harder to determine the features that should be used to separate conditions, such as fibrotic HP, which often have considerable morphologic overlap with UIP.Granulomas/giant cells are generally accepted as features against a diagnosis of UIP; extensive peribronchiolar metaplasia, in our view, favors fibrotic HP,3 and fibrosis that is predominantly peribronchiolar rather than subpleural also is in favor of fibrotic HP. But how to quantify and apply these criteria to actual cryobiopsies, and where one draws the line between UIP and fibrotic HP in such biopsies, is an important unanswered question, a problem also acknowledged by Cooper et al.1

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)0.029
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: Commentary · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0030.002
Open science0.0030.001
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0030.002

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 head0.012
GPT teacher head0.250
Teacher spread0.237 · 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
GenreCommentary

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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Citations7
Published2021
Admission routes1
Has abstractyes

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