Treatment planning optimization based on response-surface modeling of cost function versus multiple constraints

Liu, H.H.; Rosen, Isaac I.; Janjan, Nora A.; Pollack, Alan

doi:10.1109/iembs.2000.900684

Cited by 1 publication

(1 citation statement)

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“…123 Data describing the sensitivity of the objective to changes in the constraints over a wide range of values have been recently reported for clinical cases in the abdomen and prostate. 127,128 The sensitivity problem is not eliminated by the introduction of score functions that rate the dose distributions in different structures rather than demand that a set of constraints be satisfied. The score functions themselves have errors whose sizes are seldom estimated.…”

Section: Mark Langermentioning

confidence: 99%

Methodological issues in radiation dose–volume outcome analyses: Summary of a joint AAPM/NIH workshop

et al. 2002

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This report represents a summary of presentations at a joint workshop of the National Institutes of Health and the American Association of Physicists in Medicine (AAPM). Current methodological issues in dose-volume modeling are addressed here from several different perspectives. Areas of emphasis include (a) basic modeling issues including the equivalent uniform dose framework and the bootstrap method, (b) issues in the valid use of statistics, including the need for meta-analysis, (c) issues in dealing with organ deformation and its effects on treatment response, (d) evidence for volume effects for rectal complications, (e) the use of volume effect data in liver and lung as a basis for dose escalation studies, and (f) implications of uncertainties in volume effect knowledge on optimized treatment planning. Taken together, these approaches to studying volume effects describe many implications for the development and use of this information in radiation oncology practice. Areas of significant interest for further research include the meta-analysis of clinical data; interinstitutional pooled data analyses of volume effects; analyses of the uncertainties in outcome prediction models, minimal parameter number outcome models for ranking treatment plans (e.g., equivalent uniform dose); incorporation of the effect of motion in the outcome prediction; dose-escalation/isorisk protocols based on outcome models; the use of functional imaging to study radioresponse; and the need for further small animal tumor control probability/normal tissue complication probability studies.

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Section: Mark Langermentioning

confidence: 99%