A method to correct for temperature dependence and measure simultaneously dose and temperature using a plastic scintillation detector

On the use of polychromatic cameras for high spatial resolution spectral dose measurements

Objective. Despite the demonstrated benefits of hyperspectral formalism for stem effect corrections in the context of fiber dose measurements, this approach has not been yet translated into volumetric measurements where cameras are typically used for their distinguishing spatial resolution. This work investigates demosaicing algorithms for polychromatic cameras based spectral imaging. Approach. The scintillation and Cherenkov signals produced in a radioluminescent phantom are imaged by a polychromatic camera and isolated using the spectral formalism. To do so, five demosaicing algorithms are investigated from calibration to measurements: a clustering method and four interpolation algorithms. The resulting accuracy of scintillation and Cherenkov images is evaluated with measurements of the differences (mean ± standard deviation) between the obtained and expected signals from profiles drawn across a scintillation spot. Signal-to-noise ratio and signal-to-background ratio are further measured and compared in the resulting scintillation images. Finally, the resulting differences on the scintillation signal from a 0.2 × 0.2 cm2 region-of-interest (ROI) were reported. Main results. Clustering, OpenCV, bilinear, Malvar and Menon demosaicing algorithms respectively yielded differences of 3 ± 5%, 1 ± 3%, 1 ± 3%, 1 ± 2% and 2 ± 4% in the resulting scintillation images. For the Cherenkov images, all algorithms provided differences below 1%. All methods enabled measurements over the detectability (SBR > 2) and sensitivity (SNR > 5) thresholds with the bilinear algorithm providing the best SNR value. Clustering, OpenCV, bilinear, Malvar and Menon demosaicing algorithms respectively provided differences on the ROI analysis of 7 ± 5%, 3 ± 2%, 3 ± 2%, 4 ± 2%, 7 ± 3%. Significance. Radioluminescent signals can accurately be isolated using a single polychromatic camera. Moreover, demosaicing using a bilinear kernel provided the best results and enabled Cherenkov signal subtraction while preserving the full spatial resolution of the camera.

On the use of machine learning methods for mPSD calibration in HDR brachytherapy

We sought to evaluate the feasibility of using machine learning (ML) algorithms for multipoint plastic scintillator detector (mPSD) calibration in high-dose-rate (HDR) brachytherapy. Dose measurements were conducted under HDR brachytherapy conditions. The dosimetry system consisted of an optimized 1-mm-core mPSD and a compact assembly of photomultiplier tubes coupled with dichroic mirrors and filters. An ¹⁹²Ir source was remotely controlled and sent to various positions in a homemade PMMA holder, ensuring 0.1-mm positional accuracy. Dose measurements covering a range of 0.5 to 12 cm of source displacement were carried out according to TG-43 U1 recommendations. Individual scintillator doses were decoupled using a linear regression model, a random forest estimator, and artificial neural network algorithms. The dose predicted by the TG-43U1 formalism was used as the reference for system calibration and ML algorithm training. The performance of the different algorithms was evaluated using different sample sizes and distances to the source for the mPSD system calibration. We found that the calibration conditions influenced the accuracy in predicting the measured dose. The decoupling methods' deviations from the expected TG-43 U1 dose generally remained below 20%. However, the dose prediction with the three algorithms was accurate to within 7% relative to the dose predicted by the TG-43 U1 formalism when measurements were performed in the same range of distances used for calibration. In such cases, the predictions with random forest exhibited minimal deviations (<2%). However, the performance random forest was compromised when the predictions were done beyond the range of distances used for calibration. Because the linear regression algorithm can extrapolate the data, the dose prediction by the linear regression was less influenced by the calibration conditions than random forest. The linear regression algorithm's behavior along the distances to the source was smoother than those for the random forest and neural network algorithms, but the observed deviations were more significant than those for the neural network and random forest algorithms. The number of available measurements for training purposes influenced the random forest and neural network models the most. Their accuracy tended to converge toward deviation values close to 1% from a number of dwell positions greater than 100. In performing HDR brachytherapy dose measurements with an optimized mPSD system, ML algorithms are good alternatives for precise dose reporting and treatment assessment during this kind of cancer treatment.

A high-Z inorganic scintillator-based detector for time-resolved in vivo dosimetry during brachytherapy

PURPOSE

High-dose rate (HDR) and pulsed-dose rate (PDR) brachytherapy would benefit from an independent treatment verification system to monitor treatment delivery and to detect errors in real time. This paper characterizes and provides an uncertainty budget for a detector based on a fiber-coupled high-Z inorganic scintillator capable of performing time-resolved in vivo dosimetry during HDR and PDR brachytherapy.

METHOD

The detector was composed of a detector probe and an optical reader. The detector probe consisted of either a 0.5 × 0.4 × 0.4 mm³ (HDR) or a 1.0 × 0.4 × 0.4 mm³ (PDR) cuboid ZnSe:O crystal glued onto an optical-fiber cable. The outer diameter of the detector probes was 1 mm, and fit inside standard brachytherapy catheters. The signal from the detector probe was read out at 20 Hz by a photodiode and a data acquisition device inside the optical reader. In order to construct an uncertainty budget for the detector, six characteristics were determined: (1) temperature dependence of the detector probe, (2) energy dependence as a function of the probe-to-source position in 2D (determined with 2 mm resolution using a robotic arm), (3) the signal-to-noise ratio (SNR), (4) short-term stability over 8 h, and (5) long-term stability of three optical readers and four probes used for in vivo monitoring in HDR and PDR treatments over 21 months (196 treatments and 189 detector calibrations, and (6) dose-rate dependence.

RESULTS

The total uncertainty of the detector at a 20 mm probe-to-source distance was < 5.1% and < 5.8% for the HDR and PDR versions, respectively. Regarding the above characteristics, (1) the sensitivity of the detector decreased by an average of 1.4%/°C for detector probe temperatures varying from 22 to 37°C; (2) the energy dependence of the detector was nonlinear and depended on both probe-to-source distance and the angle between the probe and the brachytherapy source; (3) the median SNRs were 187 and 34 at a 20 mm probe-to-source distance for the HDR and PDR versions, respectively (corresponding median source activities of 4.8 and 0.56 Ci, respectively); (4) the detector response varied by 0.6% in 11 identical irradiations over 8 h; (5) the sensitivity of the four detector probes decreased systematically by 0-1.2%/100 Gy of dose delivered to the probes, and random fluctuations of 4.8% in the sensitivity were observed for the three probes used in PDR and 1.9% for the probe used in HDR; and (6) the detector response was linear with dose rate.

CONCLUSION

ZnSe:O detectors can be used effectively for in vivo dosimetry and with high accuracy for HDR and PDR brachytherapy applications.

Optimization of a multipoint plastic scintillator dosimeter for high dose rate brachytherapy

PURPOSE

This study is devoted to optimizing and characterizing the response of a multipoint plastic scintillator detector (mPSD) for application to in vivo dosimetry in high dose rate (HDR) brachytherapy.

METHODS

An exhaustive analysis was carried out in order to obtain an optimized mPSD design that maximizes the scintillation light collection produced by the interaction of ionizing photons. More than 20 prototypes of mPSD were built and tested in order to determine the appropriate order of scintillators relative to the photodetector (distal, center, or proximal) as well as their length as a function of the scintillation light emitted. The available detecting elements are the BCF-60, BCF-12, and BCF-10 scintillators (Saint Gobain Crystals, Hiram, OH, USA), separated from each other by segments of Eska GH-4001 clear optical fibers (Mitsubishi Rayon Co., Ltd., Tokyo, Japan). The contribution of each scintillator to the total spectrum was determined by irradiations in the low energy range (<120 keV). For the best mPSD design, a numerical optimization was done in order to select the optical components [dichroic mirrors, filters, and photomultipliers tubes (PMTs)] that best match the light emission profile. Calculations were performed taking into account the measured scintillation spectrum and light yield, the manufacturer-reported transmission and attenuation of the optical components, and the experimentally characterized PMT noise. The optimized dosimetric system was used for HDR brachytherapy measurements. The system was independently controlled from the 192 Ir source via LabVIEW and read simultaneously using an NI-DAQ board. Dose measurements as a function of distance from the source were carried out according to TG-43U1 recommendations. The system performance was quantified in terms of signal to noise ratio (SNR) and signal to background ratio (SBR).

RESULTS

For best overall light-yield emission, it was determined that BCF-60 should be placed at the distal position, BCF-12 in the center, and BCF-10 at the proximal position with respect to the photodetector. This configuration allowed for optimized light transmission through the collecting fiber and avoided inter-scintillator excitation and self-absorption effects. The optimal scintillator length found was of 3, 6, and 7 mm for BCF-10, BCF- 12, and BCF-60, respectively. The optimized luminescence system allowed for signal deconvolution using a multispectral approach, extracting the dose to each element while taking into account the Cerenkov stem effect. Differences between the mPSD measurements and TG-43U1 remain below 5% in the range of 0.5 to 6.5 cm from the source. The dosimetric system can properly differentiate the scintillation signal from the background for a wide range of dose rate conditions; the SNR was found to be above 5 for dose rates above 22 mGy/s while the minimum SBR measured was 1.8 at 6 mGy/s.

CONCLUSION

Based on the spectral response at different conditions, an mPSD was constructed and optimized for HDR brachytherapy dosimetry. It is sensitive enough to allow multiple simultaneous measurements over a clinically useful distance range, up to 6.5 cm from the source. This study constitutes a baseline for future applications enabling real-time dose measurements and source position reporting over a wide range of dose rate conditions.