ESTRO 2024 - Abstract Book

S4942

Physics - Quality assurance and auditing

ESTRO 2024

Boost Reference Point

Not Integrated

1

1

Linac3 Couch Angle

Clearance issue

1

2

Gating

Not Activated

6

2

RefPointDose

Incorrect (Lower than expected)

1

2

Linac

Incorrect Model Used

6

3

Dmax

Not Aligned with Target

5

4

Modulation

Excessively High

6

4

MLC

Overtravel

3

4

Dmax Value

Exceeds 107% of prescribed dose

5

4

Couch

Not Inserted

4

4

Energy for Pacemaker/ICD Patient Exceeds 6MV or FFF is used

3

5

CT Reconstruction

Incorrect Type Used

1

5

Tab.1: Overview of Radiation Therapy Planning Errors: This table categorizes specific issues encountered during treatment planning, listing their occurrences and assessing their impact based on a severity scale. Severity levels range from 1 (Confusing/Disruptive) to 5 (Dangerous for the Patient), with intermediate levels indicating issues like treatment delays (2), unexecutable first treatment session (3), and dosimetric inaccuracies (<5% deviation in PTV mean) (4).

Conclusion:

In conclusion, the data clearly indicate that automated PCR can detect both minor and significant errors early in the planning process. This not only streamlines the PCR process but also saves time and minimizes the risk of errors reaching the patient. Crucially, our study underscores the necessity of incorporating these automated checks at the earliest stages of the workflow. Such proactive implementation can significantly elevate patient care quality, allowing for the prompt detection and correction of errors before they proceed to more crucial phases of treatment planning and delivery.

Keywords: Automation, Plan Evaluation, ESAPI

References:

[1] Ford EC, Terezakis S, Souranis A, Harris K, Gay H, Mutic S. Quality Control Quantification (QCQ): A Tool to Measure the Value of Quality Control Checks in Radiation Oncology. International Journal of Radiation Oncology*Biology*Physics 2012;84:e263–9. https://doi.org/10.1016/j.ijrobp.2012.04.036.

[2] Gopan O, Zeng J, Novak A, Nyflot M, Ford E. The effectiveness of pretreatment physics plan review for detecting errors in radiation therapy. Med Phys 2016;43:5181. https://doi.org/10.1118/1.4961010.

[3] Holdsworth C, Kukluk J, Molodowitch C, Czerminska M, Hancox C, Cormack RA, et al. Computerized System for Safety Verification of External Beam Radiation Therapy Planning. Int J Radiat Oncol Biol Phys 2017;98:691–8. https://doi.org/10.1016/j.ijrobp.2017.03.001.