A novel dose fall-off index and preliminary application in brain and lung stereotactic radiotherapy

Med Phys. 2023 May;50(5):3127-3136. doi: 10.1002/mp.16383. Epub 2023 Apr 3.

Abstract

Background: Stereotactic radiotherapy (SRT) has been widely used for the treatment of brain metastases and early stage non-small-cell lung cancer (NSCLC). Excellent SRT plans are characterized by steep dose fall-off, making it critical to accurately and comprehensively predict and evaluate dose fall-off.

Purpose: A novel dose fall-off index was proposed to ensure high-quality SRT planning.

Methods: The novel gradient index (NGI) had two different modes: NGIx V for three-dimensions and NGIx r for one-dimension. NGIx V and NGIx r were defined as the ratios of the decreased percentage dose (x%) to the corresponding isodose volume and equivalent sphere radii, respectively. A total of 243 SRT plans at our institution between April 2020 and March 2022 were enrolled, including 126 brain and 117 lung SRT plans. Measurement-based verifications were performed using SRS MapCHECK. Ten plan complexity indexes were calculated. Dosimetric parameters related to radiation injuries were also extracted, including the normal brain volume exposed to 12 Gy (V12 ) and 18 Gy (V18 ) during single-fraction SRT (SF-SRT) and multi-fraction SRT (MF-SRT), respectively, and the normal lung volume exposed to 12 Gy (V12 ). The performance of NGI and other common dose fall-off indexes, gradient index (GI), R50% and D2cm were evaluated using Spearman correlation analysis to explore their correlations with the PTV size, gamma passing rate (GPR), plan complexity indexes, and dosimetric parameters.

Results: There were statistically significant correlations between NGI and PTV size (r = -0.98, P < 0.01 for NGI50 V and r = -0.93, P < 0.01 for NGI50 r), which were the strongest correlations compared with GI (r = 0.11, P = 0.13), R50% (r = -0.08, P = 0.19) and D2cm (r = 0.84, P < 0.01). The fitted formulas of NGI50 V = 23.86V-1.00 and NGI50 r = 113.5r-1.05 were established. The GPRs of enrolled SRT plans were 98.6 ± 1.7%, 94.2 ± 4.7% and 97.1 ± 3.1% using the criteria of 3%/2 mm, 3%/1 mm, and 2%/2 mm, respectively. NGI50 V achieved the strongest correlations with various plan complexity indexes (|r| ranged from 0.67 to 0.91, P < 0.01). NGI50 V also showed the highest r values with V12 (r = -0.93, P < 0.01) and V18 (r = -0.96, P < 0.01) of the normal brain during SF-SRT and MF-SRT, respectively, and V12 (r = -0.86, P < 0.01) of the normal lung during lung SRT.

Conclusions: Compared with GI, R50% and D2cm , the proposed dose fall-off index, NGI, had the strongest correlations with the PTV size, plan complexity and V12 /V18 of the normal tissues. These correlations established on NGI are more helpful and reliable for SRT planning, quality control, and reducing the risk of radiation injuries.

Keywords: dose fall-off; novel gradient index; plan complexity; radiation injuries; stereotactic radiotherapy.

MeSH terms

  • Brain
  • Carcinoma, Non-Small-Cell Lung*
  • Humans
  • Lung
  • Lung Neoplasms* / radiotherapy
  • Lung Neoplasms* / surgery
  • Radiation Injuries*
  • Radiosurgery* / methods
  • Radiotherapy Dosage
  • Radiotherapy Planning, Computer-Assisted / methods
  • Radiotherapy, Intensity-Modulated* / methods