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2 Polish Journal of Medical Physics and Engineering

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Complexity analysis of VMAT prostate plans: insights from dimensionality reduction and information theory techniques

Kamperis Efstathios, Kodona Chionia, Papalexandrou Apostolia, Arsos Georgios, Heidich Anna-Bettina, Hatziioannou Konstantinos, Giannouzakos Vasileios, Papanastasiou Emmanouil

Polish Journal of Medical Physics and Engineering

2023

Vol. 29, Iss. 3

143--150

Introduction: Volumetric Modulated Arc Therapy (VMAT) is a state-of-the-art prostate cancer treatment, defined by high dose gradients around targets. Its unique dose shaping incurs hidden complexity, impacting treatment deliverability, carcinogenesis, and machine strain. This study compares various aperture-based VMAT complexity indices in prostate cases using principal component and mutual information analyses. It suggests essential properties for an ideal complexity index from an information-theoretic viewpoint. Material and methods: The following ten complexity indices were calculated in 217 VMAT prostate plans: circumference over area (CoA), edge metric (EM), equivalent square field (ESF), leaf travel (LT), leaf travel modulation complexity score for VMAT (LTMCSV), mean-field area (MFA), modulation complexity score (standard MCS and VMAT variant MCSV), plan irregularity (PI), and small aperture score (SAS5mm). Principal component analysis (PCA) was applied to explore the correlations between the metrics. The differential entropy of all metrics was also calculated, along with the mutual information for all 45 metric pairs. Results: Whole-pelvis plans had greater complexity across all indices. The first three principal components explained 96.2% of the total variance. The complexity metrics formed three groups with similar conceptual characteristics, particularly ESF, LT, MFA, PI, and EM, SAS5. The differential entropy varied across the complexity metrics (PI having the smallest vs. EM the largest). Mutual information analysis (MIA) confirmed some metrics’ interdependence, although other pairs, such as LTMCSV/SAS5mm, LT/MCSV, and EM/SAS5mm, were found to share minimal MI. Conclusions: There are many complexity indices for VMAT described in the literature. PCA and MIA analyses can uncover significant overlap among them. However, this is not entirely reducible through dimensionality reduction techniques, suggesting that there also exists some reciprocity. When designing predictive models of quality assurance metrics, PCA and MIA may prove useful for feature engineering.

Design of a Monte Carlo model based on dual-source computed tomography (DSCT) scanners for dose and image quality assessment using the Monte Carlo N-Particle (MCNP5) code

Chantzi Stefania, Papanastasiou Emmanouil, Athanasopoulou Christina, Molyvda-Athanasopoulou Elisavet, Bamidis Panagiotis, Siountas Anastasios

Polish Journal of Medical Physics and Engineering

2020

Vol. 26, Iss. 1

11--20

The purpose of this work was to develop and validate a Monte Carlo model for a Dual Source Computed Tomography (DSCT) scanner based on the Monte Carlo N-particle radiation transport computer code (MCNP5). The geometry of the Siemens Somatom Definition CT scanner was modeled, taking into consideration the x-ray spectrum, bowtie filter, collimator, and detector system. The accuracy of the simulation from the dosimetry point of view was tested by calculating the Computed Tomography Dose Index (CTDI) values. Furthermore, typical quality assurance phantoms were modeled in order to assess the imaging aspects of the simulation. Simulated projection data were processed, using the MATLAB software, in order to reconstruct slices, using a Filtered Back Projection algorithm. CTDI, image noise, CT-number linearity, spatial and low contrast resolution were calculated using the simulated test phantoms. The results were compared using several published values including IMPACT, NIST and actual measurements. Bowtie filter shapes are in agreement with those theoretically expected. Results show that low contrast and spatial resolution are comparable with expected ones, taking into consideration the relatively limited number of events used for the simulation. The differences between simulated and nominal CT-number values were small. The present attempt to simulate a DSCT scanner could provide a powerful tool for dose assessment and support the training of clinical scientists in the imaging performance characteristics of Computed Tomography scanners.