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Record W2052300234 · doi:10.1118/1.3358128

Intensity modulated radiotherapy of non-small-cell lung cancer incorporating SPECT ventilation imaging

2010· article· en· W2052300234 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMedical Physics · 2010
Typearticle
Languageen
FieldMedicine
TopicEffects of Radiation Exposure
Canadian institutionsOttawa HospitalLondon Health Sciences CentreWestern University
FundersCanadian Cancer SocietyVarian Medical Systems
KeywordsRadiation therapyMedicineLung cancerNuclear medicineMedical imagingImage-guided radiation therapyIntensity (physics)Intensity modulationSingle-photon emission computed tomographyRadiologyMedical physicsOncologyOpticsPhysics

Abstract

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PURPOSE: The authors performed this retrospective study to investigate the impact of using ventilation scans obtained from single photon emission computed tomography (SPECT) in selecting beam directions in intensity modulated radiation therapy (IMRT) planning in lung cancer radiotherapy to spare dosimetrically well ventilated lung. METHODS: For ten consecutive stage III non-small-cell lung cancer patients, the authors obtained both ventilation/perfusion SPECT scans and four-dimensional CT scans for treatment planning purposes. Each ventilation scan was registered with the corresponding planning CT and ventilation volumes corresponding to either > or = 50% (vv50) or > or = 70% (vv70) of the maximum SPECT count were automatically segmented. For each patient, three IMRT plans were generated: One using nine equally spaced beams optimized according to nonfunctional lung based mean lung dose and lung v20; a second using nine equally spaced beams optimized to avoid vv50 and vv70; and a third plan using only three beams with gantry angles chosen based on minimum mean ventilated lung dose calculated for each conformal beam at every 10 degrees gantry angle avoiding vv50 and vv70. Resultant dose volume histogram indices were calculated for each plan and were compared with respect to calculated SPECT-based ventilation parameters in order to quantify the potential utility of ventilation SPECT in this setting. RESULTS: Two patient groups were identified based on (i) the overlap volume between PTV and vv50 and (ii) the average angular mean ventilated lung dose (AAMvLD). The first parameter quantifies the proximity of the PTV to well ventilated lung and the second parameter quantifies the degree of ventilation that surrounds the PTV. For group 1 patients, < or = 5% of the vv50 overlapped with the PTV. For group 2 patients, > 5% of the vv50 overlapped the PTV. Group 1 was further classified into subgroups 1A and 1B: For subgroup 1A, AAMvLD is >18 Gy, implying that the functional lung surrounds the PTV; for subgroup 1B, AAMvLD is <18 Gy, implying that the well ventilated lung does not completely surround PTV. For subgroup 1A, the plans generated using ventilated lung avoidance reduced dose to vv50 and vv70, with below tolerance dose to normal lung and acceptable coverage of the PTV. For subgroup 1B, the dose to the total lung and well ventilated lung are reduced with the beam direction optimization for the three-beam plan. For group 2, there was no significant dosimetric advantage of using SPECT-based ventilation information in IMRT plan optimization. CONCLUSIONS: In conclusion, it is feasible to use SPECT ventilation scans to optimize IMRT beam direction and, subsequently, to reduce dose to ventilated lung when overlap of the PTV and the ventilated lung is minimal and that the PTV is not surrounded by the ventilated lung. The potential benefit of ventilation SPECT scanning can be determined by preplanning assessment of overlap volumes and the AAMvLD.

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.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.006
GPT teacher head0.275
Teacher spread0.269 · 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