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Record W1973715126 · doi:10.1118/1.3276775

A new metric for assessing IMRT modulation complexity and plan deliverability

2010· article· en· W1973715126 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.

Bibliographic record

VenueMedical Physics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicAdvanced Radiotherapy Techniques
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsPinnacleDosimetryQuality assuranceMetric (unit)Radiation treatment planningNuclear medicineProstateMedicineMathematicsMedical physicsRadiation therapyStatisticsRadiologyEngineeringOperations management

Abstract

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PURPOSE: To evaluate the utility of a new complexity metric, the modulation complexity score (MCS), in the treatment planning and quality assurance processes and to evaluate the relationship of the metric with deliverability. METHODS: A multisite (breast, rectum, prostate, prostate bed, lung, and head and neck) and site-specific (lung) dosimetric evaluation has been completed. The MCS was calculated for each beam and the overall treatment plan. A 2D diode array (MapCHECK, Sun Nuclear, Melbourne, FL) was used to acquire measurements for each beam. The measured and planned dose (PINNACLE3, Phillips, Madison, WI) was evaluated using different percent differences and distance to agreement (DTA) criteria (3%/ 3 mm and 2%/ 1 mm) and the relationship between the dosimetric results and complexity (as measured by the MCS or simple beam parameters) assessed. RESULTS: For the multisite analysis (243 plans total), the mean MCS scores for each treatment site were breast (0.92), rectum (0.858), prostate (0.837), prostate bed (0.652), lung (0.631), and head and neck (0.356). The MCS allowed for compilation of treatment site-specific statistics, which is useful for comparing different techniques, as well as for comparison of individual treatment plans with the typical complexity levels. For the six plans selected for dosimetry, the average diode percent pass rate was 98.7% (minimum of 96%) for 3%/3 mm evaluation criteria. The average difference in absolute dose measurement between the planned and measured dose was 1.7 cGy. The detailed lung analysis also showed excellent agreement between the measured and planned dose, as all beams had a diode percentage pass rate for 3%/3 mm criteria of greater than 95.9%, with an average pass rate of 99.0%. The average absolute maximum dose difference for the lung plans was 0.7 cGy. There was no direct correlation between the MCS and simple beam parameters which could be used as a surrogate for complexity level (i.e., number of segments or MU). An evaluation criterion of 2%/ 1 mm reliably allowed for the identification of beams that are dosimetrically robust. In this study we defined a robust beam or plan as one that maintained a diode percentage pass rate greater than 90% at 2%/ 1 mm, indicating delivery that was deemed accurate when compared to the planned dose, even under stricter evaluation criterion. MCS and MU threshold criteria were determined by defining a required specificity of 1.0. A MCS threshold of 0.8 allowed for identification of robust deliverability with a sensitivity of 0.36. In contrast, MU had a lower sensitivity of 0.23 for a threshold of 50 MU. CONCLUSIONS: The MCS allows for a quantitative assessment of plan complexity, on a fixed scale, that can be applied to all treatment sites and can provide more information related to dose delivery than simple beam parameters. This could prove useful throughout the entire treatment planning and QA process.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.919
Threshold uncertainty score0.365

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 integrity0.0000.000
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 head0.032
GPT teacher head0.336
Teacher spread0.303 · 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