
==== Front
Neurooncol Adv
Neurooncol Adv
noa
Neuro-Oncology Advances
2632-2498
Oxford University Press US

10.1093/noajnl/vdae090.102
vdae090.102
Final Category: Radiation Therapy Advances
AcademicSubjects/MED00300
AcademicSubjects/MED00310
RADT-08 IMPACT OF ELEKTA LIGHTENING OPTIMIZER ON DOSIMETRIC AND CLINICAL OUTCOMES FOR INTACT LUNG AND BREAST METASTASES USING GAMMA KNIFE RADIOSURGERY
Yeoh Desmond Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, NY, USA

O’Carroll Kyle Northwell Health, NY, USA

Lima Jason Northwell Health, NY, USA

Calugaru Emel Northwell Health, NY, USA

Sreenivasan Sanjeev Northwell Health, NY, USA

Chitti Bhargava Northwell Health, NY, USA

Schulder Michael Northwell Health, NY, USA

Goenka Anuj Northwell Health, NY, USA

8 2024
02 8 2024
02 8 2024
6 Suppl 1 2024 SNO/ASCO CNS Metastases Conference i31i31
© The Author(s) 2024. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

Abstract

In 2022, we incorporated the Lightening optimizer software into our Gamma Knife treatment planning workflow. This allows for the rapid generation of treatment plans based on user selected parameters. We aimed to compare plans used for treatment before and after incorporation of the optimizer on patients with intact breast and lung metastases to identify dosimetric differences (gradient index, selectivity index, and coverage) and clinical outcomes (radionecrosis and local control). We also subdivided lesions by size, defining small as <1cc, medium as 1 to 4 cc, and large as >4 cc. We identified 317 metastases that were treated before Lightening and 284 metastases that were treated after Lightening. Using independent sample t-tests, we found that plans had a higher gradient index (p=<0.001), higher selectivity index (p=0.031), and similar coverage (p=0.082) following incorporation of the Lightening software. ANOVA demonstrated that both tumor size and Lightening influenced the gradient and selectivity indices. After size stratification, we found that only small lesions had different gradient indices and only medium lesions had different selectivity indices between pre- and post-Lightening groups. Before investigating clinical outcomes, we removed lesions that did not have at least a 9 month follow up, reducing pre- and post-Lightening cases to 106 and 90 respectively. Cox regressions showed that there were no significant differences in local failure rates (p=0.871) and radionecrosis (p=0.202) between pre- and post-Lightening plans. Interestingly, there was a marginally insignificant increase in the likelihood of radionecrosis for small lesions planned with Lightening (HR=7.75, p=0.062). Since the gradient index was also increased in small lesions for Lightening plans, this might indicate a clinically valuable correlation. Overall, these results suggest that while there were dosimetric differences between plans, clinical outcomes did not change. However, attention should be placed on small lesions to better understand the impact of gradient index on radionecrosis.
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pmc
