Hypoxia-informed RBE-weighted beam orientation optimization for intensity modulated proton therapy.

BACKGROUND: Variable relative biological effectiveness (RBE) models in treatment planning have been proposed to optimize the therapeutic ratio of proton therapy. It has been reported that proton RBE decreases with increasing tumor oxygen level, offering an opportunity to address hypoxia-related radioresistance with RBE-weighted optimization. PURPOSE: Here, we obtain a voxel-level estimation of partial oxygen pressure to weigh RBE values in a single biologically informed beam orientation optimization (BOO) algorithm. METHODS: Three glioblastoma patients with [18 F]-fluoromisonidazole (FMISO)-PET/CT images were selected from the institutional database. Oxygen values were derived from tracer uptake using a nonlinear least squares curve fitting. McNamara RBE, calculated from proton dose, was then weighed using oxygen enhancement ratios (OER) for each voxel and incorporated into the dose fidelity term of the BOO algorithm. The nonlinear optimization problem was solved using a split-Bregman approach, with FISTA as the solver. The proposed hypoxia informed RBE-weighted method (HypRBE) was compared to dose fidelity terms using the constant RBE of 1.1 (cRBE) and the normoxic McNamara RBE model (RegRBE). Tumor homogeneity index (HI), maximum biological dose (Dmax), and D95%, as well as OAR therapeutic index (TI = gEUDCTV /gEUDOAR ) were evaluated along with worst-case statistics after normalization to normal tissue isotoxicity. RESULTS: Compared to [cRBE, RegRBE], HypRBE increased tumor HI, Dmax, and D95% across all plans by on average [31.3%, 31.8%], [48.6%, 27.1%], and [50.4%, 23.8%], respectively. In the worst-case scenario, the parameters increase on average by [12.5%, 14.7%], [7.3%,-8.9%], and [22.3%, 2.1%]. Despite increased OAR Dmean and Dmax by [8.0%, 3.0%] and [13.1%, -0.1%], HypRBE increased average TI by [22.0%, 21.1%]. Worst-case OAR Dmean, Dmax, and TI worsened by [17.9%, 4.3%], [24.5%, -1.2%], and [9.6%, 10.5%], but in the best cases, HypRBE escalates tumor coverage significantly without compromising OAR dose, increasing the therapeutic ratio. CONCLUSIONS: We have developed an optimization algorithm whose dose fidelity term accounts for hypoxia-informed RBE values. We have shown that HypRBE selects bE:\Alok\aaeams better suited to deliver high physical dose to low RBE, hypoxic tumor regions while sparing the radiosensitive normal tissue.

A unified path seeking algorithm for IMRT and IMPT beam orientation optimization.

Objective. Fully automated beam orientation optimization (BOO) for intensity-modulated radiotherapy and intensity modulated proton therapy (IMPT) is gaining interest, since achieving optimal plan quality for an unknown number of fixed beam arrangements is tedious. Fast group sparsity-based optimization methods have been proposed to find the optimal orientation, but manual tuning is required to eliminate the exact number of beams from a large candidate set. Here, we introduce a fast, automated gradient descent-based path-seeking algorithm (PathGD), which performs fluence map optimization for sequentially added beams, to visualize the dosimetric benefit of one added field at a time.Approach. Several configurations of 2-4 proton and 5-15 photon beams were selected for three head-and-neck patients using PathGD, which was compared to group sparsity-regularized BOO solved with the fast iterative shrinkage-thresholding algorithm (GS-FISTA), and manually selected IMPT beams or one coplanar photon VMAT arc (MAN). Once beams were chosen, all plans were compared on computational efficiency, dosimetry, and for proton plans, robustness.Main results. With each added proton beam, Clinical Target Volume (CTV) and organs at risk (OAR) dosimetric cost improved on average across plans by [1.1%, 13.6%], and for photons, [0.6%, 2.0%]. Comparing algorithms, beam selection for PathGD was faster than GS-FISTA on average by 35%, and PathGD matched the CTV coverage of GS-FISTA plans while reducing OAR mean and maximum dose in all structures by an average of 13.6%. PathGD was able to improve CTV [Dmax, D95%] by [2.6%, 5.2%] and reduced worst-case [max, mean] dose in OARs by [11.1%, 13.1%].Significance. The benefit of a path-seeking algorithm is the beam-by-beam analysis of dosimetric cost. PathGD was shown to be most efficient and dosimetrically desirable amongst group sparsity and manual BOO methods, and highlights the sensitivity of beam addition for IMPT in particular.

Analytical HDR prostate brachytherapy planning with automatic catheter and isotope selection.

BACKGROUND: High dose rate (HDR) brachytherapy is commonly used to treat prostate cancer. Existing HDR planning systems solve the dwell time problem for predetermined catheters and a single energy source. PURPOSE: Additional degrees of freedom can be obtained by relaxing the catheters' pre-designation and introducing more source types, and may have a dosimetric benefit, particularly in improving conformality to spare the urethra. This study presents a novel analytical approach to solving the corresponding HDR planning problem. METHODS: The catheter and dual-energy source selection problem was formulated as a constrained optimization problem with a non-convex group sparsity regularization. The optimization problem was solved using the fast-iterative shrinkage-thresholding algorithm (FISTA). Two isotopes were considered. The dose rates for the HDR 4140 Ytterbium (Yb-169) source and the Elekta Iridium (Ir-192) HDR Flexisource were modeled according to the TG-43U1 formalism and benchmarked accordingly. Twenty-two retrospective HDR prostate brachytherapy patients treated with Ir-192 were considered. An Ir-192 only (IRO), Yb-169 only (YBO), and dual-source (DS) plan with optimized catheter location was created for each patient with N catheters, where N is the number of catheters used in the clinically delivered plans. The DS plans jointly optimized Yb-169 and Ir-192 dwell times. All plans and the clinical plans were normalized to deliver a 15 Gy prescription (Rx) dose to 95% of the clinical treatment volume (CTV) and evaluated for the CTV D90%, V150%, and V200%, urethra D0.1cc and D1cc, bladder V75%, and rectum V75%. Dose-volume histograms (DVHs) were generated for each structure. RESULTS: The DS plans ubiquitously selected Ir-192 as the only treatment source. IRO outperformed YBO in organ at risk (OARs) OAR sparing, reducing the urethra D0.1cc and D1cc by 0.98% ( p = 2.22 ∗ 10 - 9 $p\ = \ 2.22*{10^{ - 9}}$ ) and 1.09% ( p = 1.22 ∗ 10 - 10 $p\ = \ 1.22*{10^{ - 10}}$ ) of the Rx dose, respectively, and reducing the bladder and rectum V75% by 0.09 ( p = 0.0023 $p\ = \ 0.0023$ ) and 0.13 cubic centimeters (cc) ( p = 0.033 $p\ = \ 0.033$ ), respectively. The YBO plans delivered a more homogenous dose to the CTV, with a smaller V150% and V200% by 3.20 ( p = 4.67 ∗ 10 - 10 $p\ = \ 4.67*{10^{ - 10}}$ ) and 1.91 cc ( p = 5.79 ∗ 10 - 10 $p\ = \ 5.79*{10^{ - 10}}$ ), respectively, and a lower CTV D90% by 0.49% ( p = 0.0056 $p\ = \ 0.0056$ ) of the prescription dose. The IRO plans reduce the urethral D1cc by 2.82% ( p = 1.38 ∗ 10 - 4 $p\ = \ 1.38*{10^{ - 4}}$ ) of the Rx dose compared to the clinical plans, at the cost of increased bladder and rectal V75% by 0.57 ( p = 0.0022 $p\ = \ 0.0022$ ) and 0.21 cc ( p = 0.019 $p\ = \ 0.019$ ), respectively, and increased CTV V150% by a mean of 1.46 cc ( p = 0.010 $p\ = \ 0.010$ ) and CTV D90% by an average of 1.40% of the Rx dose ( p = 8.80 ∗ 10 - 8 $p\ = \ 8.80*{10^{ - 8}}$ ). While these differences are statistically significant, the clinical differences between the plans are minimal. CONCLUSIONS: The proposed analytical HDR planning algorithm integrates catheter and isotope selection with dwell time optimization for varying clinical goals, including urethra sparing. The planning method can guide HDR implants and identify promising isotopes for specific HDR clinical goals, such as target conformality or OAR sparing.

Technical note: Multi-MATE, a high-throughput platform for automated image-guided small-animal irradiation.

BACKGROUND: Small animal irradiation is essential to study the radiation response of new interventions before or parallel to human therapy. Image-guided radiotherapy (IGRT) and intensity-modulated radiotherapy (IMRT) are recently adopted in small animal irradiation to more closely mimic human treatments. However, sophisticated techniques require exceedingly high time, resources, and expertize that are often impractical. PURPOSE: We propose a high throughput and high precision platform named Multiple Mouse Automated Treatment Environment (Multi-MATE) to streamline image-guided small animal irradiation. METHODS: Multi-MATE consists of six parallel and hexagonally arranged channels, each equipped with a transfer railing, a 3D-printed immobilization pod, and an electromagnetic control unit, computer-controlled via an Arduino interface. The mouse immobilization pods are transferred along the railings between the home position outside the radiation field and the imaging/irradiation position at the irradiator isocenter. All six immobilization pods are transferred to the isocenter in the proposed workflow for parallel CBCT scans and treatment planning. The immobilization pods are then sequentially transported to the imaging/therapy position for dose delivery. The positioning reproducibility of Multi-MATE are evaluated using CBCT and radiochromic films. RESULTS: While parallelizing and automating the image-guided small animal radiation delivery, Multi-MATE achieved the average pod position reproducibility of 0.17 ± 0.04 mm in the superior-inferior direction, 0.20 ± 0.04 mm in the left-right direction, and 0.12 ± 0.02mm in the anterior-posterior direction in repeated CBCT tests. Additionally, in image-guided dose delivery tasks, Multi-MATE demonstrated the positioning reproducibility of 0.17 ± 0.06 mm in the superior-inferior direction, 0.19 ± 0.06 mm in the left-right direction. CONCLUSIONS: We designed, fabricated, and tested a novel automated irradiation platform, Multi-MATE to accelerate and automate image-guided small animal irradiation. The automated platform minimizes human operation and achieves high setup reproducibility and image-guided dose delivery accuracy. Multi-MATE thus removes a major barrier to implementing high-precision preclinical radiation research.

Dose and dose rate objectives in Bragg peak and shoot-through beam orientation optimization for FLASH proton therapy.

PURPOSE: The combined use of Bragg peak (BP) and shoot-through (ST) beams has previously been shown to increase the normal tissue volume receiving FLASH dose rates while maintaining dose conformality compared to conventional intensity-modulated proton therapy (IMPT) methods. However, the fixed beam optimization method has not considered the effects of beam orientation on the dose and dose rates. To maximize the proton FLASH effect, here, we incorporate dose rate objectives into our beam orientation optimization framework. METHODS: From our previously developed group-sparsity dose objectives, we add upper and lower dose rate terms using a surrogate dose-averaged dose rate definition and solve using the fast-iterative shrinking threshold algorithm. We compare the dosimetry for three head-and-neck cases between four techniques: (1) spread-out BP IMPT (BP), (2) dose rate optimization using BP beams only (BP-DR), (3) dose rate optimization using ST beams only (ST-DR), and (4) dose rate optimization using combined BP and ST (BPST-DR), with the goal of sparing organs at risk without loss of tumor coverage and maintaining high dose rate within a 10 mm region of interest (ROI) surrounding the clinical target volume (CTV). RESULTS: For BP, BP-DR, ST-DR, and BPST-DR, CTV homogeneity index and Dmax were found to be on average 0.886, 0.867, 0.687, and 0.936 and 107%, 109%, 135%, and 101% of prescription, respectively. Although ST-DR plans were not able to meet dosimetric standards, BPST-DR was able to match or improve either maximum or mean dose in the right submandibular gland, left and right parotids, constrictors, larynx, and spinal cord compared to BP plans. Volume of ROIs receiving greater than 40 Gy/s ( V γ 0 ) ${V_{\gamma 0}})$ was 51.0%, 91.4%, 95.5%, and 92.1% on average. CONCLUSIONS: The dose rate techniques, particularly BPST-DR, were able to significantly increase dose rate without compromising physical dose compared with BP. Our algorithm efficiently selects beams that are optimal for both dose and dose rate.

Fixed Beamline Optimization for Intensity Modulated Carbon-Ion Therapy.

A major obstacle for the adoption of heavy ion therapy is the cost and technical difficulties to construct and maintain a rotational gantry. Many heavy ion treatment facilities instead choose to construct fixed beamlines as a compromise, which we propose to mitigate with optimized treatment couch angle. We formulate the integrated beam orientation and scanning spot optimization problem as a quadratic cost function with a group sparsity regularization term. The optimization problem is efficiently solved using fast iterative shrinkage-thresholding algorithm (FISTA). To test the method, we created the fixed beamline plans with couch rotation (FBCR) and without couch rotation (FB) for intensity modulated carbon-ion therapy (IMCT) and compared with the ideal scenario where both the couch and gantry have 360 degrees of freedom (GCR). FB, FBCR, and GCR IMCT plans were compared for ten pancreas cases. The FBCR plans show comparable PTV coverage and OAR doses for each pancreas case. In conclusion, the dosimetric limitation of fixed beams in heavy ion radiotherapy may be largely mitigated with integrated beam orientation optimization of the couch rotation.

Reformulated McNamara RBE-weighted beam orientation optimization for intensity modulated proton therapy.

PURPOSE: Empirical relative biological effectiveness (RBE) models have been used to estimate the biological dose in proton therapy but do not adequately capture the factors influencing RBE values for treatment planning. We reformulate the McNamara RBE model such that it can be added as a linear biological dose fidelity term within our previously developed sensitivity-regularized and heterogeneity-weighted beam orientation optimization (SHBOO) framework. METHODS: Based on our SHBOO framework, we formulated the biological optimization problem to minimize total McNamara RBE dose to OARs. We solve this problem using two optimization algorithms: FISTA (McNam-FISTA) and Chambolle-Pock (McNam-CP). We compare their performances with a physical dose optimizer assuming RBE = 1.1 in all structures (PHYS-FISTA) and an LET-weighted dose model (LET-FISTA). Three head and neck patients were planned with the four techniques and compared on dosimetry and robustness. RESULTS: Compared to Phys-FISTA, McNam-CP was able to match CTV [HI, Dmax, D95%, D98%] by [0.00, 0.05%, 1.4%, 0.8%]. McNam-FISTA and McNam-CP were able to significantly improve overall OAR [Dmean, Dmax] by an average of [36.1%,26.4%] and [29.6%, 20.3%], respectively. Regarding CTV robustness, worst [Dmax, V95%, D95%, D98%] improvement of [-6.6%, 6.2%, 6.0%, 4.8%] was reported for McNam-FISTA and [2.7%, 2.7%, 5.3%, -4.3%] for McNam-CP under combinations of range and setup uncertainties. For OARs, worst [Dmax, Dmean] were improved by McNam-FISTA and McNam-CP by an average of [25.0%, 19.2%] and [29.5%, 36.5%], respectively. McNam-FISTA considerably improved dosimetry and CTV robustness compared to LET-FISTA, which achieved better worst-case OAR doses. CONCLUSION: The four optimization techniques deliver comparable biological doses for the head and neck cases. Besides modest CTV coverage and robustness improvement, OAR biological dose and robustness were substantially improved with both McNam-FISTA and McNam-CP, showing potential benefit for directly incorporating McNamara RBE in proton treatment planning.

Automatic measurement of air gap for proton therapy using orthogonal x-ray imaging with radiopaque wires.

PURPOSE: The main objective of this study was to develop a technique to accurately determine the air gap between the end of the proton beam compensator and the body of the patient in proton radiotherapy. METHODS: Orthogonal x-ray image-based automatic coordinate reconstruction was used to determine the air gap between the patient body surface contour and the end of beam nozzle in proton radiotherapy. To be able to clearly identify the patient body surface contour on the orthogonal images, a radiopaque wire was placed on the skin surface of the patient as a surrogate. In order to validate this method, a Rando® head phantom was scanned and five proton plans were generated on a Mevion S250 Proton machine with various air gaps in Varian Eclipse Treatment Planning Systems (TPS). When setting up the phantom in a treatment room, a solder wire was placed on the surface of the phantom closest to the beam nozzle with the knowledge of the beam geometry in the plan. After the phantom positioning was verified using orthogonal kV imaging, the last pair of setup kV images was used to segment the solder wire and the in-room coordinates of the wire were reconstructed using a back-projection algorithm. Using the wire as a surrogate of the body surface, we calculated the air gaps by finding the minimum distance between the reconstructed wire and the end of the compensator. The methodology was also verified and validated on clinical cases. RESULTS: On the phantom study, the air gap values derived with the automatic reconstruction method were found to be within 1.1 mm difference from the planned values for proton beams with air gaps of 85.0, 100.0, 150.0, 180.0, and 200.0 mm. The reconstruction technique determined air gaps for a patient in two clinical treatment sessions were 38.4 and 41.8 mm, respectively, for a 40 mm planned air gap, and confirmed by manual measurements. There was strong agreement between the calculated values and the automatically measured values, and between the automatically and manually measured values. CONCLUSIONS: An image-based automatic method has been developed to conveniently determine the air gap of a proton beam, directly using the orthogonal images for patient positioning without adding additional imaging dose to the patient. The method provides an objective, accurate, and efficient way to confirm the target depth at treatment to ensure desired target coverage and normal tissue sparing.