Assessment of the alpha/beta ratio of the optic pathway to adjust hypofractionated stereotactic radiosurgery regimens for perioptic lesions

Obtaining organ-specific radiobiological parameters from clinical data for radiation therapy planning of head and neck cancers

Objective.Different radiation therapy (RT) strategies, e.g. conventional fractionation RT (CFRT), hypofractionation RT (HFRT), stereotactic body RT (SBRT), adaptive RT, and re-irradiation are often used to treat head and neck (HN) cancers. Combining and/or comparing these strategies requires calculating biological effective dose (BED). The purpose of this study is to develop a practical process to estimate organ-specific radiobiologic model parameters that may be used for BED calculations in individualized RT planning for HN cancers.Approach.Clinical dose constraint data for CFRT, HFRT and SBRT for 5 organs at risk (OARs) namely spinal cord, brainstem, brachial plexus, optic pathway, and esophagus obtained from literature were analyzed. These clinical data correspond to a particular endpoint. The linear-quadratic (LQ) and linear-quadratic-linear (LQ-L) models were used to fit these clinical data and extract relevant model parameters (alpha/beta ratio, gamma/alpha,dTand BED) from the iso-effective curve. The dose constraints in terms of equivalent physical dose in 2 Gy-fraction (EQD2) were calculated using the obtained parameters.Main results.The LQ-L and LQ models fitted clinical data well from the CFRT to SBRT with the LQ-L representing a better fit for most of the OARs. The alpha/beta values for LQ-L (LQ) were found to be 2.72 (2.11) Gy, 0.55 (0.30) Gy, 2.82 (2.90) Gy, 6.57 (3.86) Gy, 5.38 (4.71) Gy, and the dose constraint EQD2 were 55.91 (54.90) Gy, 57.35 (56.79) Gy, 57.54 (56.35) Gy, 60.13 (59.72) Gy and 65.66 (64.50) Gy for spinal cord, optic pathway, brainstem, brachial plexus, and esophagus, respectively. Additional two LQ-L parametersdTwere 5.24 Gy, 5.09 Gy, 7.00 Gy, 5.23 Gy, and 6.16 Gy, and gamma/alpha were 7.91, 34.02, 8.67, 5.62 and 4.95.Significance.A practical process was developed to extract organ-specific radiobiological model parameters from clinical data. The obtained parameters can be used for biologically based radiation planning such as calculating dose constraints of different fractionation regimens.

Single fraction and hypofractionated radiosurgery for perioptic meningiomas-tumor control and visual outcomes: a systematic review and meta-analysis

Perioptic meningiomas, defined as those that are less than 3 mm from the optic apparatus, are challenging to treat with stereotactic radiosurgery (SRS). Tumor control must be weighed against the risk of radiation-induced optic neuropathy (RION), as both tumor progression and RION can lead to visual decline. We performed a systematic review and meta-analysis of single fraction SRS and hypofractionated radiosurgery (hfRS) for perioptic meningiomas, evaluating tumor control and visual preservation rates. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we reviewed articles published between 1968 and December 8, 2022. We retained 5 studies reporting 865 patients, 438 cases treated in single fraction, while 427 with hfRS. For single fraction SRS, the overall rate of tumor control was 95.1%, with actuarial rates at 5 and 10 years of 96% and 89%, respectively; tumor progression was 7.7%. The rate of visual stability was 90.4%, including visual improvement in 29.3%. The rate of visual decline was 9.6%, including blindness in 1.2%. For hfRS, the overall rate of tumor control was 95.6% (range 92.1-99.1, p < 0.001); tumor progression was 4.4% (range 0.9-7.9, p = 0.01). Overall rate of visual stability was 94.9% (range 90.9-98.9, p < 0.001), including visual improvement in 22.7% (range 5.0-40.3, p = 0.01); visual decline was 5.1% (range 1.1-9.1, p = 0.013). SRS is an effective and safe treatment option for perioptic meningiomas. Both hypofractionated regimens and single fraction SRS can be considered.

Brain Re-Irradiation Robustly Accounting for Previously Delivered Dose

(1) Background: The STRIDeR (Support Tool for Re-Irradiation Decisions guided by Radiobiology) planning pathway aims to facilitate anatomically appropriate and radiobiologically meaningful re-irradiation (reRT). This work evaluated the STRIDeR pathway for robustness compared to a more conservative manual pathway. (2) Methods: For ten high-grade glioma reRT patient cases, uncertainties were applied and cumulative doses re-summed. Geometric uncertainties of 3, 6 and 9 mm were applied to the background dose, and LQ model robustness was tested using α/β variations (values 1, 2 and 5 Gy) and the linear quadratic linear (LQL) model δ variations (values 0.1 and 0.2). STRIDeR robust optimised plans, incorporating the geometric and α/β uncertainties during optimisation, were also generated. (3) Results: The STRIDeR and manual pathways both achieved clinically acceptable plans in 8/10 cases but with statistically significant improvements in the PTV D98% (p < 0.01) for STRIDeR. Geometric and LQ robustness tests showed comparable robustness within both pathways. STRIDeR plans generated to incorporate uncertainties during optimisation resulted in a superior plan robustness with a minimal impact on PTV dose benefits. (4) Conclusions: Our results indicate that STRIDeR pathway plans achieved a similar robustness to manual pathways with improved PTV doses. Geometric and LQ model uncertainties can be incorporated into the STRIDeR pathway to facilitate robust optimisation.

Can Apparent Diffusion Coefficient (ADC) maps replace Diffusion Tensor Imaging (DTI) maps to predict the volumetric response of meningiomas to Gamma Knife Radiosurgery?

PURPOSE

Noninvasive methods are desired to predict the treatment response to Stereotactic Radiosurgery (SRS) to improve individual tumor management. In a previous study, we demonstrated that Diffusion Tensor Imaging (DTI)-derived parameter maps significantly correlate to SRS response. This study aimed to analyze and compare the predictive value of intratumoral ADC and DTI parameters in patients with meningiomas undergoing radiosurgery.

METHODS

MR images of 70 patients treated with Gamma Knife SRS for WHO grade I meningiomas were retrospectively reviewed. MR acquisition included pre- and post-treatment DWI and DTI sequences, and subtractions were calculated to assess for radiation-induced changes in the parameter values.

RESULTS

After a mean follow-up period (FUP) of 52.7 months, 69 of 70 meningiomas were controlled, with a mean volume reduction of 34.9%. Whereas fractional anisotropy (FA) values of the initial exam showed the highest correlation to tumor volume change at the last FU (CC = - 0.607), followed by the differences between first and second FU values of FA (CC = - 0.404) and the first longitudinal diffusivity (LD) value (CC = - 0.375), the correlation coefficients of all ADC values were comparably low. Nevertheless, all these correlations, except for ADC measured at the first follow-up, reached significance.

CONCLUSION

For the first time, the prognostic value of ADC maps measured in meningiomas before and at first follow-up after Gamma Knife SRS, was compared to simultaneously acquired DTI parameter maps. Quantities assessed from ADC maps present significant correlations to the volumetric meningioma response but are less effective than correlations with DTI parameters.

MRI radiomics in the prediction of the volumetric response in meningiomas after gamma knife radiosurgery

PURPOSE

This report presents the first investigation of the radiomics value in predicting the meningioma volumetric response to gamma knife radiosurgery (GKRS).

METHODS

The retrospective study included 93 meningioma patients imaged by three Tesla MRI. Tumor morphology was quantified by calculating 337 shape, first- and second-order radiomic features from MRI obtained before GKRS. Analysis was performed on original 3D MR images and after their laplacian of gaussian (LoG), logarithm and exponential filtering. The prediction performance was evaluated by Pearson correlation, linear regression and ROC analysis, with meningioma volume change per month as the outcome.

RESULTS

Sixty calculated features significantly correlated with the outcome. The feature selection based on LASSO and multivariate regression started from all available 337 radiomic and 12 non-radiomic features. It selected LoG-sigma-1-0-mm-3D_firstorder_InterquartileRange and logarithm_ngtdm_Busyness as the predictively most robust and non-redundant features. The radiomic score based on these two features produced an AUC = 0.81. Adding the non-radiomic karnofsky performance status (KPS) to the score has increased the AUC to 0.88. Low values of the radiomic score defined a homogeneous subgroup of 50 patients with consistent absence (0%) of tumor progression.

CONCLUSION

This is the first report of a strong association between MRI radiomic features and volumetric meningioma response to radiosurgery. The clinical importance of the early and reliable prediction of meningioma responsiveness to radiosurgery is based on its potential to aid individualized therapy decision making.

Stereotactic Radiosurgery for Perioptic Meningiomas: An International, Multicenter Study

BACKGROUND

Stereotactic radiosurgery (SRS) is increasingly used for management of perioptic meningiomas.

OBJECTIVE

To study the safety and effectiveness of SRS for perioptic meningiomas.

METHODS

From 12 institutions participating in the International Radiosurgery Research Foundation (IRRF), we retrospectively assessed treatment parameters and outcomes following SRS for meningiomas located within 3 mm of the optic apparatus.

RESULTS

A total of 438 patients (median age 51 yr) underwent SRS for histologically confirmed (29%) or radiologically suspected (71%) perioptic meningiomas. Median treatment volume was 8.01 cm3. Median prescription dose was 12 Gy, and median dose to the optic apparatus was 8.50 Gy. A total of 405 patients (93%) underwent single-fraction SRS and 33 patients (7%) underwent hypofractionated SRS. During median imaging follow-up of 55.6 mo (range: 3.15-239 mo), 33 (8%) patients experienced tumor progression. Actuarial 5-yr and 10-yr progression-free survival was 96% and 89%, respectively. Prescription dose of ≥12 Gy (HR: 0.310; 95% CI [0.141-0.679], P = .003) and single-fraction SRS (HR: 0.078; 95% CI [0.016-0.395], P = .002) were associated with improved tumor control. A total of 31 (10%) patients experienced visual decline, with actuarial 5-yr and 10-yr post-SRS visual decline rates of 9% and 21%, respectively. Maximum dose to the optic apparatus ≥10 Gy (HR = 2.370; 95% CI [1.086-5.172], P = .03) and tumor progression (HR = 4.340; 95% CI [2.070-9.097], P < .001) were independent predictors of post-SRS visual decline.

CONCLUSION

SRS provides durable tumor control and quite acceptable rates of vision preservation in perioptic meningiomas. Margin dose of ≥12 Gy is associated with improved tumor control, while a dose to the optic apparatus of ≥10 Gy and tumor progression are associated with post-SRS visual decline.

Evaluation and comparison of global-feature-based and local-feature-based segmentation algorithms in intracranial visual pathway delineation

Intracranial visual pathway is related to the effective transmission of visual signals to brain. It was not only the target organ of diseases but also the organs at risk in radiotherapy thus its delineation plays an important role in both diagnosis and treatment planning. Traditional manual segmentation method suffered from time- and labor- consuming as well as intra- and inter- variability. In order to overcome these problems, state-of-the-art segmentation models were designed and various features were extracted and utilized, but it's hard to tell their effectiveness on intracranial visual pathway delineation. It's because that these methods worked on different dataset and accompanied with different training tricks. This study aimed to research the contribution of global features and local features in delineating the intracranial visual pathway from MRI scans. The two typical segmentation models, 3D UNet and DeepMedic, were chosen since they focused on global features and local features respectively. We constructed the hybrid model through serially connecting the two mentioned models to validate the performance of combined global and local features. Validation results showed that the hybrid model outperformed the individual ones. It proved that multi scale feature fusion was important in improving the segmentation performance.