Detection of dose delivery variations on TomoTherapy using on-board detector based verification

Cheukkai Hui, Quan Chen, Shiv Khandelwal, Brian Neal, William Watkins

Research output: Contribution to journalArticlepeer-review

3 Scopus citations


A clinical case of delivery dose deviations on a TomoTherapy treatment was discovered during a patient specific treatment quality assurance (QA) verification. An in-house developed QA system, MCLogQA, for TomoTherapy has been implemented in our clinic for patient specific treatment QA. The MCLogQA system utilizes the log file and detector-based multileaf collimator (MLC) leaf opening time (LOT) to assess accuracy of treatment plan delivery. Recently, the MCLogQA system discovered >10% dose deviation for a low dose/fraction treatment plan. To verify the adequacy of the MCLogQA result, a delivery quality assurance (DQA) plan was created and performed. The treatment plan was also transferred to a second TomoTherapy unit and planning system to investigate if the plan-delivery deviation was unit dependent. Further testing was carried out in phantom plans. MCLogQA showed MLC LOT was on average 2.4% higher than the planned LOT, resulting in 3.5% increase in mean dose, and 14% increase in dose to 1 cc volume of max dose in PTV. Independent DQA verification confirmed the MCLogQA result. For the transferred treatment plan delivery, the MCLogQA also showed an average increase of 6.6% in MLC LOT, resulting in increases in mean dose by 9.3% and dose to 1 cc volume of max dose in PTV by 16%. The inaccurate MLC LOT was a result of a poor latency model at very small LOT. Phantom testing confirmed low LOT will result in relatively large dosimetric variation, and detector-based MCLogQA will detect differences in planned and measured LOT. Accuracy in TomoTherapy treatment delivery can be susceptible to LOT uncertainty. Using MCLogQA for QA verification not only validates the treatment delivery, but also provides information on LOT variation and comprehensive dose distribution. This information can help decision making when large plan-delivery deviation occurs.

Original languageEnglish
Article number14NT02
JournalPhysics in Medicine and Biology
Issue number14
StatePublished - Jul 16 2018


  • detector-based QA
  • MLC latency
  • patient specific QA
  • TomoTherapy QA

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging


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