Algorithm development for intrafraction radiotherapy beam edge verification from Cherenkov imaging

Direct in-water radiation dose measurements using Cherenkov emission corrected signals from polarization imaging for a clinical radiotherapy application

Cherenkov emission (CE) is a visible blueish light emitted in water mediums irradiated by most radiotherapy treatment beams. However, CE is produced anisotropically which currently imposes a geometrical constraint uncertainty for dose measurements. In this work, polarization imaging is proposed and described as a method enabling precise 2D dose measurements using CE. CE produced in a water tank is imaged from four polarization angles using a camera coupled to a rotating polarizer. Using Malus’ law, the polarized component of CE is isolated and corrected with Monte Carlo calculated CE polar and azimuthal angular distributions. Projected dose measurements resulting from polarization-corrected CE are compared to equivalent radiochromic film measurements. Overall, agreement between polarized corrected CE signal and films measurements is found to be within 3%, for projected percent depth dose (PPDD) and profiles at the different tested energies (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\gamma$$\end{document}γ: 6 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$18\,\hbox {MV}$$\end{document}18MV, e\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{-}$$\end{document}-: 6 and 18\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\,\hbox {MeV}$$\end{document}MeV). In comparison, raw Cherenkov emission presented deviations up 60% for electron beam PPDDs and 20% for photon beams PPDDs. Finally, a degree of linear polarization between 29% and 47% was measured for CE in comparison to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0.2\pm 0.3$$\end{document}0.2±0.3% for scintillation. Hence, polarization imaging is found to be a promising and powerful method for improved radio-luminescent dose measurements with possible extensions to signal separation.

Cherenkov Luminescence in Tumor Diagnosis and Treatment: A Review

Malignant tumors rank as a leading cause of death worldwide. Accurate diagnosis and advanced treatment options are crucial to win battle against tumors. In recent years, Cherenkov luminescence (CL) has shown its technical advantages and clinical transformation potential in many important fields, particularly in tumor diagnosis and treatment, such as tumor detection in vivo, surgical navigation, radiotherapy, photodynamic therapy, and the evaluation of therapeutic effect. In this review, we summarize the advances in CL for tumor diagnosis and treatment. We first describe the physical principles of CL and discuss the imaging techniques used in tumor diagnosis, including CL imaging, CL endoscope, and CL tomography. Then we present a broad overview of the current status of surgical resection, radiotherapy, photodynamic therapy, and tumor microenvironment monitoring using CL. Finally, we shed light on the challenges and possible solutions for tumor diagnosis and therapy using CL.

Color Cherenkov imaging of clinical radiation therapy

Color vision is used throughout medicine to interpret the health and status of tissue. Ionizing radiation used in radiation therapy produces broadband white light inside tissue through the Cherenkov effect, and this light is attenuated by tissue features as it leaves the body. In this study, a novel time-gated three-channel camera was developed for the first time and was used to image color Cherenkov emission coming from patients during treatment. The spectral content was interpreted by comparison with imaging calibrated tissue phantoms. Color shades of Cherenkov emission in radiotherapy can be used to interpret tissue blood volume, oxygen saturation and major vessels within the body.

Optical emission-based phantom to verify coincidence of radiotherapy and imaging isocenters on an MR-linac

Purpose

Demonstrate a novel phantom design using a remote camera imaging method capable of concurrently measuring the position of the x‐ray isocenter and the magnetic resonance imaging (MRI) isocenter on an MR‐linac.

Methods

A conical frustum with distinct geometric features was machined out of plastic. The phantom was submerged in a small water tank, and aligned using room lasers on a MRIdian MR‐linac (ViewRay Inc., Cleveland, OH). The phantom physical isocenter was visualized in the MR images and related to the DICOM coordinate isocenter. To view the x‐ray isocenter, an intensified CMOS camera system (DoseOptics LLC., Hanover, NH) was placed at the foot of the treatment couch, and centered such that the optical axis of the camera was coincident with the central axis of the treatment bore. Two or four 8.3mm x 24.1cm beams irradiated the phantom from cardinal directions, producing an optical ring on the conical surface of the phantom. The diameter of the ring, measured at the peak intensity, was compared to the known diameter at the position of irradiation to determine the Z‐direction offset of the beam. A star‐shot method was employed on the front face of the frustum to determine X‐Y alignment of the MV beam. Known shifts were applied to the phantom to establish the sensitivity of the method.

Results

Couch translations, demonstrative of possible isocenter misalignments, on the order of 1mm were detectable for both the radiotherapy and MRI isocenters. Data acquired on the MR‐linac demonstrated an average error of 0.28mm(N=10, R²=0.997, σ=0.37mm) in established Z displacement, and 0.10mm(N=5, σ=0.34mm) in XY directions of the radiotherapy isocenter.

Conclusions

The phantom was capable of measuring both the MRI and radiotherapy treatment isocenters. This method has the potential to be of use in MR‐linac commissioning, and could be streamlined to be valuable in daily constancy checks of isocenter coincidence.

Cherenkov imaging for Total Skin Electron Therapy - an evaluation of dose uniformity

Total Skin Electron Therapy (TSET) utilizes high-energy electrons to treat cancers on the entire body surface. The otherwise invisible radiation beam can be observed via the optical Cherenkov photons emitted from interaction between the high-energy electron beam and tissue. Cherenkov emission can be used to evaluate the dose uniformity on the surface of the patient in real-time using a time-gated intensified camera system. Each patient was monitored during TSET by in-vivo detectors (IVD) as well as Scintillators. Patients undergoing TSET in various conditions (whole body and half body) were imaged and analyzed. A rigorous methodology for converting Cherenkov intensity to surface dose as products of correction factors, including camera vignette correction factor, incident radiation correction factor, and tissue optical properties correction factor. A comprehensive study has been carried out by inspecting various positions on the patients such as vertex, chest, perineum, shins, and foot relative to the umbilicus point (the prescription point).

Cherenkov imaging for total skin electron therapy (TSET)

BACKGROUND

Total skin electron therapy (TSET) utilizes high-energy electrons to treat malignancies on the entire body surface. The otherwise invisible radiation beam can be observed via the optical Cherenkov photons emitted from interactions between the high-energy electron beam and tissue.

METHODS AND MATERIALS

With a time-gated intensified camera system, the Cherenkov emission can be used to evaluate the dose uniformity on the surface of the patient in real time. Fifteen patients undergoing TSET in various conditions (whole body and half body) were imaged and analyzed. Each patient was monitored during TSET via in vivo detectors (IVD) in nine locations. For accurate Cherenkov imaging, a comparison between IVD and Cherenkov profiles was conducted using a polyvinyl chloride board to establish the perspective corrections.

RESULTS AND DISCUSSION

With proper corrections developed in this study including the perspective and inverse square corrections, the Cherenkov imaging provided two-dimensional maps proportional to dose and projected on patient skin. The results of ratio between chest and umbilicus points were in good agreement with in vivo point dose measurements, with a standard deviation of 2.4% compared to OSLD measurements.

CONCLUSIONS

Cherenkov imaging is a viable tool for validating patient-specific dose distributions during TSET.

Space-variant deconvolution of Cerenkov light images acquired from a curved surface

PURPOSE

Cerenkov photons are generated by high-energy radiation used in external beam radiation therapy (EBRT). This study expands upon the Cerenkov light dosimetry formula previously developed to relate an image of Cerenkov photons to the primary beam fluence. Extension of this formulation allows for deconvolution to be performed on images acquired from curved geometries.

METHODS

The integral equation, which represented the formation of Cerenkov photon image from an incident high-energy photon beam, was expanded to allow for space-variance of the convolution kernel called as the Cerenkov scatter function (CSF). The GAMOS (Geant4-based Architecture for Medicine-Oriented Simulations) Monte Carlo (MC) particle simulation software was used to obtain the CSF for different incident beam angles. The image of a curved surface was first projected to a flat plane by using a perspective correction method. Then, the planar image was partitioned into small segments (or blocks), where a CSF corresponding to a specific beam incident angle was applied for deconvolution. The block size and the margin around the block were optimized by studying the effects of those parameters on the deconvolution accuracy for a test image. We evaluated three deconvolution techniques: Richardson-Lucy, Blind, and Total Variation minimization (TV/L2) algorithms, to select the most accurate method for the current applications.

RESULTS

Analysis of deconvolution algorithms showed that the TV/L2 method provided the most accurate solution to the deconvolution problem for Cerenkov imaging. Optimization of space-variant deconvolution parameters showed that including a margin that is at least 42.9% of the image width provided the most accurate product image. There was no optimal size for the deconvolution area and should be chosen based on the presence of unique CSF kernels within an image. Space-variant deconvolution improved measured field size in Cerenkov photon images by 7.37%, as compared with 1.74% by space-invariant deconvolution. Space-variant deconvolution improved measured penumbra by 99.3%, as compared with 76.7% by space-invariant deconvolution. Space-variant deconvolution introduced artifacts in flat regions of the beam. Artifacts were avoided through selective space-variant deconvolution in only the penumbra region.

CONCLUSIONS

Primary photon fluence distributions of a curved surface can be obtained by using space-variant deconvolution methods in Cerenkov light dosimetry. The TV/L2 algorithm is the best method for deconvolution of Cerenkov photon images from an open-field beam derived from either a flat or curved surface. The partition size chosen for space-variant deconvolution should be at least six times the full width at half maximum (FWHM) of the corresponding scatter kernel used in deconvolution. Space-variant deconvolution is necessary if the incident beam angle difference is larger than 6 ∘ between regions of an image.

Improvements to an optical scintillator imaging-based tissue dosimetry system

Previous work has shown that capturing optical emission from plastic discs attached directly to the skin can be a viable means to accurately measure surface dose during total skin electron therapy. This method can provide accurate dosimetric information rapidly and remotely without the need for postprocessing. The objective of this study was to: (1) improve the robustness and usability of the scintillators and (2) enhance sensitivity of the optical imaging system to improve scintillator emission detection as related to tissue surface dose. Baseline measurements of scintillator optical output were obtained by attaching the plastic discs to a flat tissue phantom and simultaneously irradiating and imaging them. Impact on underlying surface dose was evaluated by placing the discs on-top of the active element of an ionization chamber. A protective coating and adhesive backing were added to allow easier logistical use, and they were also subjected to disinfection procedures, while verifying that these changes did not affect the linearity of response with dose. The camera was modified such that the peak of detector quantum efficiency better overlapped with the emission spectra of the scintillating discs. Patient imaging was carried out and surface dose measurements were captured by the updated camera and compared to those produced by optically stimulated luminescence detectors (OSLD). The updated camera was able to measure surface dose with < 3 %   difference compared to OSLD–Cherenkov emission from the patient was suppressed and scintillation detection was enhanced by 25 × and 7 ×  , respectively. Improved scintillators increase underlying surface dose on average by 5.2  ±  0.1 %   and light output decreased by 2.6  ±  0.3 %  . Disinfection had < 0.02 %   change on scintillator light output. The enhanced sensitivity of the imaging system to scintillator optical emission spectrum can now enable a reduction in physical dimensions of the dosimeters without loss in ability to detect light output.

Cherenkov imaging for linac beam shape analysis as a remote electronic quality assessment verification tool

PURPOSE

A remote imaging system tracking Cherenkov emission was analyzed to verify that the linear accelerator (linac) beam shape could be quantitatively measured at the irradiation surface for Quality Audit (QA).

METHODS

The Cherenkov camera recorded 2D dose images delivered on a solid acrylonitrile butadiene styrene (ABS) plastic phantom surface for a range of square beam sizes, and 6 MV photons. Imaging was done at source to surface distance (SSD) of 100 cm and compared to GaF film images and linac light fields of the same beam sizes, ranging over 5 × 5 cm² up to 20 × 20 cm² . Line profiles of each field were compared in both X and Y jaw directions. Each measurement was repeated on two different Clinac2100 machines. An interreader comparison of the beam width interpretation was completed using procedures commonly employed for beam to light field coincidence verification. Cherenkov measurements are also done for beams of complex treatment plan and isocenter QA.

RESULTS

The Cherenkov image widths matched with the measured GaF images and light field images, with accuracy in the range of ±1 mm standard deviation. The differences between the measurements were minor and within tolerance of geometrical requirement of standard linac QA procedures conducted by human setup verification, which had a similar error range. The measurement made by the remote imaging system allowed for beam shape extraction of radiation fields at the SSD location of the beam.

CONCLUSIONS

The proposed Cherenkov image acquisition system provides a valid way to remotely confirm radiation field sizes and provides similar information to that obtained from the linac light field or GaF film estimates of the beam size. The major benefit of this approach is that with a fixed installation of the camera, testing could be done completely under software control with automated image analysis, potentially simplifying conventional QA procedures with appropriate calibration of boundary definitions, and the natural extension to capturing dynamic treatment beamlets at SSD could have future value, such as verification of beam plans with complex beam shapes, like IMRT or "star-shot" QA for the isocenter.