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Record W2964326113 · doi:10.1177/1533033819853532

Changes in Volume and Density Parameters Measured on Computed Tomography Images Following Stereotactic Body Radiation Therapy of Nonspine Bone Metastases

2019· article· en· W2964326113 on OpenAlexaff
Samuel Finkelstein, Srinivas Raman, Joanne Van der Velden, Liying Zhang, Carolyn Michelle Tan, Amanpreet Dhillon, Frances Tonolete, Nicholas Chiu, Linda Probyn, Rachel McDonald, Arjun Sahgal, Edward Chow, Lee Chin

Bibliographic record

VenueTechnology in Cancer Research & Treatment · 2019
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineComputed tomographyRadiologyNuclear medicineBone densityRadiation therapyOsteoporosisPathology

Abstract

fetched live from OpenAlex

INTRODUCTION: Volumetric and density parameters measured from computed tomography scans were investigated for evaluating treatment response of nonspine bone lesions following stereotactic body radiation therapy. METHODS: Twenty-three patients treated with stereotactic body radiation therapy to nonspine bone metastases with pre- and post-treatment radiological follow-up with computed tomography imaging were identified in a retrospective review. An expert radiologist classified 26 lesions by type (lytic, sclerotic) and by response. Two independent radiation oncologists created separate contours of the bone and soft tissue lesion volumes. Density and volume were assessed relative to baseline values. RESULTS: For bone-only lesions, all lesions designated as local control decreased in volume or remained within 20% of baseline volumes. Lytic lesions classified as progressive disease exhibited much larger volume increases. Lytic bone lesions showed indications of remineralization with some exhibiting immediate increases in density (1-6 months) and others decreasing initially then increasing back toward baseline between 7 and 12 months. The majority of sclerotic lesions, all classified as local control, decreased slightly in both volume and density. Lesions with both soft tissue and boney involvement resulted in contradictory results when employing both radiological and size parameters for assessing treatment response. Classification was dominated by changes in soft tissue volume, despite associated volume or density changes in the corresponding boney lesion. In contrast, when soft tissue volume changes were minimal (<20% increase), classification appeared to be related primarily to density changes and not bone volume. CONCLUSIONS: Volume and density changes show promise as quantitative parameters for classifying treatment responses of nonspine osseous lesions. Further work is required for clarifying how these metrics can be applied to lesions with both boney and soft tissue components.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.087
Threshold uncertainty score0.645

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.373
Teacher spread0.316 · 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 teacher head, 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

Citations1
Published2019
Admission routes1
Has abstractyes

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