Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform

Summary

Here we present a protocol to perform preclinical positron emission tomography-based radiotherapy in a rat glioblastoma model using algorithms developed in-house to optimize the accuracy and efficiency.

Abstract

A rat glioblastoma model to mimic chemo-radiation treatment of human glioblastoma in the clinic was previously established. Similar to the clinical treatment, computed tomography (CT) and magnetic resonance imaging (MRI) were combined during the treatment-planning process. Positron emission tomography (PET) imaging was subsequently added to implement sub-volume boosting using a micro-irradiation system. However, combining three imaging modalities (CT, MRI, and PET) using a micro-irradiation system proved to be labor-intensive because multimodal imaging, treatment planning, and dose delivery have to be completed sequentially in the preclinical setting. This also results in a workflow that is more prone to human error. Therefore, a user-friendly algorithm to further optimize preclinical multimodal imaging-based radiation treatment planning was implemented. This software tool was used to evaluate the accuracy and efficiency of dose painting radiation therapy with micro-irradiation by using an in silico study design. The new methodology for dose painting radiation therapy is superior to the previously described method in terms of accuracy, time efficiency, and intra- and inter-user variability. It is also an important step towards the implementation of inverse treatment planning on micro-irradiators, where forward planning is still commonly used, in contrast to clinical systems.

Introduction

Glioblastoma (GB) is a malignant and very aggressive primary brain tumor. GB is a solid heterogeneous tumor typically characterized by infiltrative boundaries, nuclear atypia, and necrosis¹. The presence of the blood-brain-barrier and the brain's status as an immune-privileged site makes the discovery of novel targets for chemo- and immunotherapy a daunting task^2,3,4. It is noteworthy that the treatment of GB patients has barely changed since the introduction, in 2005, of the Stupp protocol that combines external beam radiation therapy (RT) with concomitant temozolomide, usually followed by adjuvant temozolomide⁵. Typically, the Stupp protocol is preceded by maximal surgical resection. Therefore, alternative treatment approaches are of pivotal importance.

Current radiation therapy for glioblastoma patients delivers a uniform radiation dose to the defined tumor volume. In radiation oncology, there is an important dose-response correlation for glioblastoma with increasing dose, which seems to cap around 60 Gy, due to increased toxicity to the normal brain^6,7. However, tumors can be very (radiobiologically) heterogeneous, with gradients of oxygen level and/or large differences in cellular density. Metabolic imaging techniques, such as PET, can visualize these biological features and can be utilized to customize the dose prescription. This approach is known as dose painting RT. This term was introduced by Ling et al. in 2000. The authors defined dose painting RT as producing "exquisitely conformal dose distributions within the constraints of radiation propagation and scatter"⁸.

There are two types of dose painting RT, dose painting by contours (DPBC), by which a dose is prescribed to a set of nested sub-volumes, and dose painting by numbers (DPBN), whereby a dose is prescribed at the voxel level. The dose distribution for DPBN RT can be extracted from functional images. The dose in each voxel is determined by the intensity I of the corresponding voxel in the image, with a lower and upper limit, to make sure that, on the one hand, a sufficient dose is delivered to every part of the tumor. On the other hand, doses do not exceed an upper limit to protect organs at risk and avoid toxicity. The most straightforward method is a linear interpolation (see Eq. 1) between minimum dose D_min and maximum dose D_max, proportionally varying between minimum intensity I_max and maximum intensity within the target volume^9,10

 Eq. 1

Because there is some skepticism about the quality assurance of DPBN RT, the deposition of the dose should be verified through preclinical and clinical research¹⁰. However, only limited data can be acquired from clinical trials, and it has been hypothesized that more insights can be obtained by downscaling to laboratory animals^11,12. Hence, preclinical studies utilizing precision image-guided radiation research platforms that allow coupling with some very specific techniques, such as autoradiography, are suited for examining open issues and paving the way towards personalized medicine and novel treatment strategies, such as dose painting RT^13,14. However, the interpretation of preclinical data must be performed with caution, and drawbacks of these preclinical setups have to be considered¹⁴.

Micro-irradiation systems, such as the Small Animal Radiation Research Platform (SARRP), are equipped with similar technologies as their clinical counterpart. They include on-board cone-beam CT (CBCT) imaging, a preclinical treatment-planning system (PCTPS), and provide sub-millimeter precision. Clinical dose calculations are performed by inverse treatment planning, whereby one initiates from the desired dose distribution to determine the beams via an iterative algorithm. Preclinical irradiators often use forward planning. In forward planning, the required amount and angle of the beams are selected, and the PCTPS then calculates the dose distribution. The optimization of the plans is performed by manual iteration, which is labor-intensive¹⁵.

After 2009, novel developments have made the implementation of inverse planning on these research platforms possible^16,17,18. To increase the similarity with the clinical method, a motorized variable rectangular collimator (MVC) was developed as a preclinical counterpart of the multi-leaf collimator. A two-dimensional dose painting method utilizing a variable collimator was published by Cho et al.¹⁹. This research group implemented a three-dimensional (3D) inverse treatment-planning protocol on a micro-irradiator and determined minimum and maximum doses for the target volume and a maximum dose for the organs at risk. These techniques have mainly been evaluated in silico, and their preclinical applications need to be explored.

This paper presents an in silico study to compare two methodologies for [¹⁸F]-fluoro-ethyl-L-tyrosine ([¹⁸F]FET) PET-based dose painting in a GB rat model^20,21,22 using a small animal radiation research platform. These two methodologies are (1) sub-volume boosting using predefined beam sizes and (2) dose painting using a motorized variable collimator where jaw dimensions are modified based on the PET tracer uptake in the tumor volume. [¹⁸F]FET is a PET tracer often used in neuro-oncology because of its ability to detect brain tumors²³. [¹⁸F]FET is an artificial amino acid that is internalized into tumoral cells but not incorporated into cell proteins. [¹⁸F]FET uptake corresponds with cell proliferation rate, tumor cell density, and angiogenesis²⁴. As this is the most commonly used oncologic brain PET tracer in these authors' institute, this radiotracer was chosen to evaluate the new workflow.

Protocol

The study was approved by the local ethics committee for animal experiments (ECD 18/21). Anesthesia monitoring is performed by acquiring the respiratory rate of the animals using a sensor.

1. F98 GB rat cell model

1. Culture the F98 GB cells in a monolayer using Dulbecco's Modified Eagle Medium, supplemented with 10% calf serum, 1% penicillin, 1% streptomycin, and 1% L-glutamine, and place them in a CO₂ incubator (5% CO₂ and 37 °C).
2. Inoculate the glioma cells into the brain of female Fischer F344 rats (body weight 170 g).
   NOTE: Use sterile instruments and wear sterile gloves at all times.
   1. Anesthetize the rats through the inhalation of isoflurane (5% induction, 2% maintenance) mixed with oxygen (0.3 mL/min) through a nose cone. Confirm the anesthetization by the absence of withdrawal reflex of the limb, and immobilize the rats in a stereotactic device using fixation points for the nose and ears. Apply a carbomer eye gel to prevent dry eyes under anesthesia. Maintain the body temperature by a thermoregulated heating pad and rectal probe at 37 °C.
   2. Shave the rat from the eye level to the back of the skull, and disinfect the skin with isobetadine. Inject xylocaine (with adrenaline 1:200000, 0.1 mL) subcutaneously for local anesthesia.
   3. Expose the skull through a midline scalp incision and make a small hole with a drill tool 3 mm posterior and 3 mm lateral to the bregma in the right hemisphere.
   4. Insert a stereotactically guided insulin needle (29 G) and inject 5 µL of cell suspension (20,000 F98 GB cells) 3 mm deep using a microsyringe pump controller. Leave the needle in place for 5 min, giving the cell suspension time to diffuse into the tissue.
   5. Withdraw the syringe slowly and close the hole in the skull with bone wax. Suture the skin (polyamide 6, thickness 4-0) and inject meloxicam subcutaneously (1 mg/kg, 2 mg/mL). Apply xylocaine gel.
   6. Stabilize the body temperature of the animal post-surgery using a red lamp. Monitor the awakening of the rat until it has regained sufficient consciousness. Do not return the animal to the company of other animals until fully recovered. House all animals under environmentally controlled conditions (12 h light/dark cycle, 20-24 °C, and 40-70% relative humidity) with food and water ad libitum.
   7. Be sure to monitor the animals daily and maintain a daily health status log by checking their body weight, food, water intake, and their activity and behavior. Use a lethal dose of pentobarbital sodium to euthanize the animals (160 mg/kg) if a decline of 20% body weight is observed or when the normal behavior severely deteriorates (e.g., lack of grooming).

2. Confirmation of tumor growth

1. Evaluate tumor growth 8 days post-inoculation. Anesthetize the rats through the inhalation of isoflurane (5% induction, 2% maintenance) mixed with oxygen (0.3 mL/min) through a nose cone. Confirm the anesthetization by the absence of withdrawal reflex of the limb.
2. Inject a gadolinium-containing contrast agent (0.4 mL/kg) through an intravenously placed tubing in the lateral tail vein. Cover the animal with a warm water circulating heating blanket and place them in the MRI bed. Apply a carbomer eye gel to prevent dry eyes under anesthesia. Place the MRI bed in the holder with a Tx/Rx Rat brain volume coil.
3. Perform a localizer scan followed by a T₂-weighted spin-echo scan to assess tumor growth. Use these T₂-MRI sequence settings: repetition time (TR)/echo time (TE) 3661/37.1 ms, 109 µm isotropic in-plane resolution, slice thickness 600 µm, 4 averages, 30 slices, total acquisition time (TA) 9 min 45 s.
4. If a tumor is confirmed on the T₂-weighted acquisition, perform a T₁-weighted contrast-enhanced spin echo scan. Use these T₁-MRI sequence settings: TR/TE 1539/9.7 ms, 0.117 mm isotropic in-plane resolution, slice thickness 600 µm, 3 averages, 30 slices, TA 4 min 15 s.
5. After the MRI, continuously supervise the animal until it regains full consciousness.
6. When the tumor reaches a diameter of 7 to 8 mm, usually observed 12 days after inoculation, select the animal for therapy.

3. Multimodality imaging of target volume selection

NOTE: PET/MRI-guided irradiation requires the sequential acquisition of a multimodal dataset. After intravenous administration of the radiotracer, PET imaging is started, followed by contrast-enhanced T₁-weighted MRI and finally a treatment-planning CT.

1. Anesthetize the animal with isoflurane (5% induction, 2% maintenance) mixed with oxygen (0.3 L/min) using a nose cone. Confirm anesthetization when the rats do not exhibit any withdrawal reflex of the limb. Apply carbomer eye gel to prevent dry eyes under anesthesia.
2. Insert the tubing intravenously in the lateral tail vein, enabling the injection of 10-12 MBq of PET radioactive tracer dissolved in 200 µL of saline. Inject [¹⁸F]-FET, 1 h before PET acquisition. Let the animal regain consciousness while the tracer is distributed through the body.
3. Anesthetize the animal again, as described in step 3.1. Place the animal on a multimodality bed (here, made in-house) and secure it using hook-and-loop fasteners, maintaining a fixed position during the imaging and micro-irradiation. Fix a capillary filled with the MRI/PET agent (see the Table of Materials) for easier co-registration. Wrap the animal in bubble wrap to preserve its body temperature during the multimodality imaging and therapy.
4. Perform a PET scan 1 h after the injection of the PET tracer. Reconstruct the PET scan into a 3D volume (192 x 192 x 384 matrix) with 0.4 mm voxel size by applying a Maximum-Likelihood Expectation-Maximization (MLEM)-algorithm using 30 iterations.
   NOTE: A dedicated PET scanner for laboratory animal imaging was used with an axial field of view of 130 mm and a bore diameter of 72 mm. This system provides sub-mm (0.85 mm) spatial resolution.
5. Inject an MRI contrast agent (0.4 mL/kg) intravenously into the tail vein. Place the rat, still fixed on the multimodality bed, in the animal holder of the MRI scanner (Table of Materials). Perform a localizer scan followed by a contrast-enhanced T₁-weighted spin-echo sequence, analogous to step 2.4.
6. Place the animal, still fixed on the multimodality bed, on a plastic holder secured onto the four-axis robotic positioning table on the micro-irradiator. Perform a high-resolution treatment-planning cone-beam CT using a tube voltage of 70 kV, a tube current of 0.4 mA, a 1 mm aluminum filter, and a 20 x 20 cm (1024 x 1024 pixel) amorphous Si flat panel detector. Acquire a total of 360 projections over 360°. Reconstruct the CT images with an isotropic voxel size of 0.275 mm (411 x 411 x 251 matrix).

4. Image co-registration

NOTE: The co-registration is performed with a semi-automatic MATLAB code developed in-house. The code can be found on Github at https://github.com/sdonche/DosePainting. The different steps are described below.

1. Place the three image modalities ([¹⁸F]FET PET, contrast-enhanced T₁-weighted MRI, and cone-beam CT) into one folder. Convert DICOM images to the NIfTI format using the dcm2niix function from the mricron image viewer²⁴.
2. Import the converted images into MATLAB and filter the PET image with a Gaussian filter using a Full-Width Half-Max (FWHM) of 1 mm.
3. Reorient the images so that the cartesian axes from all imaging modalities correspond with each other.
   NOTE: For this setup, the CT image was flipped around the Y-axis; the MRI was flipped around the X-axis, and the PET was flipped around the Y-axis.
4. Crop the PET image to simplify automatic co-registration.
   NOTE: For this setup, 40 pixels were set to zero from both sides of the X-axis (left and right of the animal); on the dorsal and ventral side of the animal (Y-axis), 60 and 40 pixels were set to zero, respectively; along the longitudinal axis (or Z-axis), 170 and 30 pixels are set to zero for inferior and superior side, respectively.
5. Move the image centers close to each other to simplify automatic co-registration.
6. Perform the actual rigid-body co-registration using Statistical Parametric Mapping (SPM) in MATLAB²⁶. Use the following registration parameters (others on default): objective function: mutual information; separation: [4 1 0.2]; tolerances: [0.02 0.02 0.02 0.001 0.001 0.001 0.01 0.01 0.01 0.001 0.001 0.001]; histogram smoothing: [1 1]; interpolation: trilinear.

5. Radiation treatment planning

NOTE: A MATLAB app and multiple MATLAB scripts were written for the radiation treatment planning. The code can be found on Github at https://github.com/sdonche/DosePainting. The different steps are explained below.

1. Method 1
   1. Load the three different imaging modalities into the MATLAB app. Place a generous bounding box around the contrast enhancement on the T₁-weighted MRI scan (Figure 1). Determine the contrast-enhanced volume using a threshold (Figure 2). If multiple regions have been selected, select only the largest volume, the center of which is considered as the first isocenter to deliver a prescribed dose for RT (Figure 3).
   2. Expand the previously determined MRI contrast enhancement by 10 pixels in each direction. If multiple regions are detected, retain only the largest PET volume, the center of which is considered the second isocenter to deliver a prescribed dose for RT.
      NOTE: In this PET volume, the PET boost volume is defined by the pixels with a higher signal intensity than 0.90 × maximal signal intensity (in the bounding box) in this volume.
   3. Use the following irradiation settings for the calculated isocenters (Figure 4 and Table 1).
      1. For the first isocenter (MRI), give a prescribed dose of 2000 cGy using 3 non-coplanar arcs at couch positions 0°, -45°, and -90° with a gantry rotation of 120°, 120°, and 60°, respectively. Use a fixed collimator size of 10 x 10 mm, but use an appropriate collimator (e.g., a 5 x 5 mm collimator) when smaller tumor sizes need to be irradiated. Be careful in considering the animal's welfare when the tumor volumes are larger than 10 mm.
      2. For the second isocenter (PET), give a prescribed dose of 800 cGy using 3 non-coplanar arcs at couch positions 0°, -45°, and -90° with a gantry rotation of 120°, 120°, and 60°, respectively. Use a fixed collimator size of 3 x 3 mm.
   4. Calculate the dose distribution within the animal and the beam delivery parameters.
2. Method 2
   1. Load the three different imaging modalities into the MATLAB app. Place a generous bounding box around the contrast-enhancement on the [¹⁸F]FET PET image, analogous to step 5.1.1.
   2. Determine the volumes defined by the pixels with a signal intensity higher than A × maximal signal intensity (in the aforementioned bounding box), with A equal to 0.50, 0.60, 0.70, 0.80, and 0.90. Name these volumes V50, V60, V70, V80, and V90, respectively.
   3. Determine the isocenters and the jaw dimensions for each beam required to guide the motorized variable collimator using the MATLAB script (see Figure 5).
   4. Use the following settings for the calculated isocenters and jaw dimensions:
      1. For V50, give a prescribed dose of 2000 cGy distributed over 16 beams (each 125 cGy; couch and gantry positions in Table 2). Use the calculated jaw dimensions for the MVC.
         NOTE: Here, an additional margin of 1 mm has been included to account for microscopic tumor infiltration.
      2. For V60-V90, give a prescribed dose of 800 cGy distributed over 40 beams (each 20 cGy; couch and gantry positions in Table 2). Use the calculated jaw dimensions for the MVC.
   5. Calculate the dose distribution within the animal and the beam delivery parameters.

6. Plan evaluation

NOTE: To compare the two methods, calculate the dose-volume histograms (DVH) and Q-volume histogram (QVH) in the V50 PET volume. Here, a MATLAB script, developed in-house, was used. The code can be found on Github at https://github.com/sdonche/DosePainting.

1. Dose-volume histogram
   1. Generate DVH from the dose distribution that was obtained from the SARRP.
   2. Determine the maximum, mean, and minimum doses from the DVH by calculating the D₁₀, D₅₀, and D₉₀, where D_x stands for the dose received by x% of the volume.
2. Q-volume histogram
   1. Calculate an ideal dose for every pixel using Eq. 1, which is a linear interpolation between the minimum and maximum doses, proportionally varying between the minimum PET intensity and maximum PET intensity within the target volume to give an ideal dose map.
   2. Calculate the Q-value Q_p for every pixel using the following equation (Eq. 2):
       Eq. 2
      With D_p being the dose obtained by planning and D_i, the dose objective for planning.
   3. Generate QVH from the obtained Q-values.
   4. Calculate the quality factor (Q-factor, Q_F) to evaluate the difference between the planned and intended doses using Eq. 3:
       Eq. 3

Representative Results

The feasibility of PET- and MRI-guided irradiation in a glioblastoma rat model using the SARRP to mimic the human treatment strategy has been previously described^20,21,22. While the animal was fixed on a multimodality bed made in-house, it was possible to create an acceptable radiation treatment plan combining three imaging modalities: PET, MRI, and CT. In these methods, an external software package (see the Table of Materials) was used to co-register the images using rigid-body transformations manually. The contrast-enhanced T₁-weighted MRI and PET images were visually assessed from which the isocenters were manually selected. However, this methodology proved to be labor-intensive and certainly has an impact on the animals as they have to stay under general anesthesia during the multimodality imaging and the creation of a treatment plan. Therefore, the new methodology aims to automate specific steps in this process to reduce the overall variance and time required to create a radiation treatment plan.

In this paper, two methodologies are compared. Method 1 is very similar to the previously published methodology^20,21,22 with a few adjustments (Table 1). However, in contrast to the previously published methodology, most of the process is automated using a MATLAB code developed in-house. Method 2 is a more sophisticated method in which a series of isocenters and jaw dimensions for the MVC will be determined based on the [¹⁸F]FET PET uptake (Figure 5). The isocontours for V50, V60, V70, V80, and V90 are shown in Figure 6.

Both methods were applied to three different cases (Figure 7). These cases can be divided into two different types: [¹⁸F]FET PET uptake in the infiltrative tumor front and the presence of tumor necrosis and [¹⁸F]FET PET uptake indicating no tumor necrosis. Case 1 can be described as a spherical homogeneous PET uptake, while Cases 2 and 3 have a ring-shaped uptake where the reduced PET-uptake is most likely necrotic tissue. Case 3 also shows an additional region growing out towards the dorsal region.

After calculating the setup parameters for both methods, the dose distributions for each case (Figure 8) were determined using the SARRP's PCTPS. The DVHs (Figure 9) can be obtained from the dose distributions in the volumes defined by the pixels with signal intensity higher than 0.50 × maximal PET signal intensity (in the bounding box). One can observe that the DVHs for Method 2 are systematically closer to the ideal dose distribution than those for Method 1. A substantial tumor volume receives insufficient irradiation in Cases 2 and 3 when treated with Method 1. Table 3 confirms these conclusions: the D₉₀ and D₅₀ values are considerably lower for Method 1 than for Method 2. The QVHs (Figure 10) can also be obtained from these dose distributions. Ideally, these curves make a sharp drop at a Q-value equal to one. Method 2 always results in dose distributions that are closer to the dose objective. Table 4 also demonstrates superior overall Q-factors for Method 2. The minimal dose (D₉₀) of 2000 cGy has been achieved for all cases with Method 2, while it was not achieved with Method 1 in 2 cases. This means that the tumor volume received insufficient irradiation using Method 1.

Figure 1: Bounding box placement. The T₁-weighted contrast enhancement is visible in the F98 GB rat model, and a generous bounding box is placed around the tumor using the MATLAB code developed in-house. Please click here to view a larger version of this figure.

Figure 2: T₁-weighted contrast-enhancing tumor delineation: step 1. The tumor volume is delineated on the contrast-enhanced T₁-weighted MRI using thresholding. Abbreviation: MRI = magnetic resonance imaging. Please click here to view a larger version of this figure.

Figure 3: T₁-weighted contrast-enhancing tumor delineation: step 2. If multiple volumes are detected during the thresholding step, the largest volume is retained for further processing. Please click here to view a larger version of this figure.

Figure 4: Isocenter calculation for Method 1. Contrast-enhanced T₁-weighted MRI, CT, and PET images are depicted. The blue and red circles represent the MRI- and PET-based isocenters, respectively. Abbreviations: MRI = magnetic resonance imaging; CT = computed tomography; PET = positron emission tomography. Please click here to view a larger version of this figure.

Figure 5: Explanation of jaw setup calculation. Step 1: the tumor volume is determined (blue dots, top image). Step 2: a plane (black grid) is created perpendicular to the incident beam (magenta line, top image) at specific couch and gantry positions. Step 3: the tumor voxels (blue dots, top image) are perpendicularly projected onto the aforementioned plane, resulting in a set of projected voxels (red dots). Step 4: determine the isocenter and jaw dimensions (green lines, bottom image) so that all the projected voxels are included within the rectangular beam defined by the two symmetrical jaws of the variable collimator (bottom image). These figures were generated in MATLAB. Please click here to view a larger version of this figure.

Figure 6: Tumor isocontours. Transaxial, coronal, and sagittal slices through the brain tumor with tumor volumes V50, V60, V70, V80, and V90 determined by the isocontours corresponding to 50%, 60%, 70%, 80%, and 90% of the maximum tumor uptake in the PET images. Abbreviations: TV = transaxial; COR = coronal; SAG = sagittal; PET = positron emission tomography. Please click here to view a larger version of this figure.

Figure 7: [¹⁸F]FET PET imaging for the three cases. The sagittal, transverse, and frontal views are displayed for all three cases. Please click here to view a larger version of this figure.

Figure 8: Dose distributions for both methods. Sagittal, transverse, and frontal views for all three cases are displayed for both Method 1 and Method 2. The dose distribution is shown together with the cone-beam CT imaging from the SARRP. Abbreviations: CT = computed tomography; SARRP = small animal radiation research platform. Please click here to view a larger version of this figure.

Figure 9: DVH curves for all cases. DVH curves (in cGy) are shown for Method 1, Method 2, and the Ideal Dose Map. Abbreviation: DVH = dose-volume histogram. Please click here to view a larger version of this figure.

Figure 10: Q-volume histogram for all cases. QVH curves are shown for Method 1, Method 2, and the Ideal Dose Map. Ideally, the calculated QVH must have a sharp drop at Q-value = 1 (Ideal dose map, blue line). Abbreviation: QVH = Q-volume histogram. Please click here to view a larger version of this figure.

		Previous Method	Method 1	Method 2
Tumour	Diameter	5 mm	7-8 mm	7-8 mm
PET	Resolution (mm)	1.2	0.85	0.85
Base irradiation	Dose (cGy)	2000	2000	2000
	Target	CE T1 tumour	CE T1 tumour	V50
	Collimator (mm²)	5x5	10x10	MVC
	Delivery	3 non-coplanar arcs	3 non-coplanar arcs	16 beams
	Couch positions	-45°, 0°, 45°	0°, -45°, -90°	0°, -45°, -90°
Irradiation boost or dose painting	Dose (cGy)	500	800	800
	Target	Max PET uptake	Max PET uptake	V60-V90
	Collimator (mm²)	1x1	3x3	MVC
	Delivery	3 non-coplanar arcs	3 non-coplanar arcs	40 beams
	Couch positions	-45°, 0°, 45°	0°, -45°, -90°	0°, -45°, -90°

Table 1: Method comparison. This table further clarifies Method 1, Method 2, and the Previous Method (referring to the method that has already been published)^20,21,22. Methods 1 and 2 utilize a preclinical PET scanner²⁷ with sub-millimeter spatial resolution, making it possible to visualize the tumor heterogeneity more clearly. At couch position -90°, it is only possible to use 60° out of 120° to avoid collision with the animal. Despite this drawback, this couch position has easier access to the tumor because it is situated in the right hemisphere. The other couch positions can make the full 120° rotations. Abbreviations: CE T₁ = contrast-enhanced T1-weighted; MVC = motorized variable collimator; PET = positron emission tomography.

Couch Position	Gantry position
0°	-	20°	40°	60°	80°	100°	120°
-45°	-	20°	40°	60°	80°	100°	120°
-90°	0°	20°	40°	60°	-	-	-

Table 2: Beam setup for Method 2. The gantry and couch positions of all the different beams are displayed. V50 uses all configurations, whereas V60-V90 only use the configurations shown in bold.

		D90	D50	D10
Case 1	Ideal Dose Map	2336.94	2461.21	2745.63
	Method 1	2024.47	2389.75	2796.82
	Method 2	2164.21	2490.18	2747.64
Case 2	Ideal Dose Map	2391.76	2540.55	2752.56
	Method 1	1894.93	2127.86	2606.48
	Method 2	2322.11	2597.31	2848.03
Case 3	Ideal Dose Map	2377.47	2556.7	2761.38
	Method 1	1874.58	2103.78	2691.69
	Method 2	2354.03	2602.64	2907.41

Table 3: DVH values. D₁₀, D₅₀, and D₉₀ were calculated as substitutes for maximum, mean, and minimal doses, respectively. D_x stands for the dose received by x% of the volume. Abbreviation: DVH = dose-volume histogram.

Q-factor	Case 1	Case 2	Case 3
Method 1	0.0898	0.1573	0.1773
Method 2	0.0572	0.057	0.0778

Table 4: Q-factors. The table displays the overall Q-factors for Method 1 and Method 2 for each case. The Q-factor will be zero if the delivered dose and prescribed dose are equal.

Discussion

A rat GB model to mimic the chemo-radiation treatment in the clinic for glioblastoma patients was previously described²⁰. Similar to the clinical method, CT and MRI were combined during the treatment-planning process to obtain more precise irradiation. A multimodality bed to minimize (head) movement was used when the animal was moved from one imaging system to another. Subsequently, PET imaging was added to the treatment-planning process, and PET-based sub-volume boosting could be successfully implemented^21,22. The inclusion of a functional image modality, such as PET, in the treatment-planning process allows the visualization of the (biological) tumor heterogeneity. This facilitates the targeting of aggressive and/or radiation-resistant tumor regions. Although this method is feasible, it proved to be very labor-intensive because multimodal imaging, treatment planning, and dose delivery must be completed sequentially in a preclinical setting. Moreover, during this process, the animals have to stay under general anesthesia²². Therefore, it is essential to improve the efficiency of the preclinical treatment-planning process.

This paper presents a user-friendly semi-automatic algorithm to further optimize preclinical multimodal imaging-based radiation treatment planning. Co-registration between planning CT, MRI, and PET were automated, in combination with the detection of the target isocenters. Of note, the software tool should not be considered as a black box, and it is crucial to perform proper quality checks. The most critical step in this entire process is to evaluate the results of the automatic co-registration of planning CT, MRI, and PET that should be as accurate as possible. The output of the algorithm consists of the positions of the target isocenters and the jaw dimensions of the MVC for the different radiation beams. These values can be imported into the most recent version of the PCTPS.

This software tool was used to evaluate the accuracy and efficiency of PET-based dose painting on the micro-irradiator by using an in silico study design. The optimized treatment-planning process was superior to the previously described method^21,22 in terms of time efficiency, intra- and inter-user variability, and accuracy. While conventional preclinical treatment planning, including multimodal imaging, can require up to 180 min²², this time could be reduced to ~80 min with both the semi-automatic methods presented in this manuscript. Moreover, human errors are more likely in the conventional treatment-planning process during manual co-registration and visual determination of the isocenters, resulting in larger intra- and inter-user variability. The automatic co-registration and detection of the target isocenters by the algorithm will reduce these intra- and inter-user variabilities. In addition, the optimized and automated workflow provides more accurate irradiation of the tumor volume. This is illustrated by the lower Q-factors (Table 4), which assesses the difference between the dose calculated/delivered by the PCTPS and the prescribed dose.

It is also noteworthy that the use of an MVC results in a reduced dose to the surrounding normal brain tissue, compared to collimators with a fixed beam size. This is illustrated in Figure 7 and is important to narrow the gap between clinical trials evaluating DPBN RT strategy (where multi-leaf collimators are used) and laboratory animal radiation research. However, we assume that dose delivery might be slightly slower when using an MVC to switch between beam positions and adjust the jaw dimensions for each individual beam. Finally, preclinical treatment planning is most often done by forward planning. The methodology described in this paper is a crucial step towards inverse planning, which is generally used in the clinic, and further narrows the gap between preclinical radiation research and the clinic.

This study also has some limitations. For the experiments described in this manuscript, the most commonly used amino acid PET tracer [¹⁸F]FET was used. When using other PET tracers to guide radiation treatment, the semi-automatic workflow should be properly examined because co-registration might be less accurate. Further, the impact of using a different voxel size for PET and/or MRI on treatment planning and dose delivery should be further investigated. In conclusion, the methodology described here to optimize the preclinical treatment-planning process has many advantages compared to the previously described method^21,22. Using an in silico study design, it was proven that the novel workflow for preclinical multimodal treatment planning is more accurate in terms of dose delivery, more time-efficient, and shows less intra- and inter-user variability. These improvements are essential to narrow the gap between clinical and preclinical radiation research and for the development of new therapeutics and/or radiation therapy procedures for glioblastoma.

Materials

Name	Company	Catalog Number	Comments
Cell culture
F98 Glioblastoma Cell Line	ATCC	CRL-2397	https://www.lgcstandards-atcc.org/products/all/CRL-2397
Dulbeco's Modified Eagle Medium	Thermo Fisher Scientific	22320-030
Cell culture flasks	Thermo Fisher Scientific	178883	75 cm²
FBS	Thermo Fisher Scientific	10270106
L-Glutamine	Thermo Fisher Scientific	25030-032	200 mM
Penicilline-Streptomycin	Thermo Fisher Scientific	15140-148	10,000 U/mL
Phosphate-Buffered Saline (PBS)	Thermo Fisher Scientific	14040-224
Trypsin-EDTA	Thermo Fisher Scientific	25300-062	0.05%
GB Rat Model
Ball-shaped burr	Foredom	A-228	1.8 mm
Bone Wax	Aesculap	1029754	https://www.aesculapusa.com/en/healthcare-professionals/or-solutions/or-solutions-cranial-closure/hemostatic-bone-wax.html
Ethilon	Ethicon	662G/662H	FS-2, 4-0, 3/8, 19 mm
Fischer F344/Ico crl Rats	Charles River	-
Insulin Syringe Microfine	Beckton-Dickinson	320924	1 mL, 29 G
IR Lamp	Philips	HP3616/01
Meloxicam (Metacam)	Boehringer Ingelheim	-	2 mg/mL
Micromotor rotary tool	Foredom	K.1090-22
Micropump system	Stoelting Co.	53312	Stoelting Stereotaxic Injector
Stereotactic frame	Stoelting Co.	51600
Xylocaine (1%, with adrenaline 1:200,000)	Aspen	-	1%, with adrenaline 1:200,000
Xylocaine gel (2%)	Aspen	-	2%
Animal Irradiation
Micro-irradiator	X-Strahl	SARRP	Version 4.2.0
Software	X-Strahl	Muriplan	Preclinical treatment planning system (PCTPC), version 2.2.2
Small Animal PET
[18F]FET	Inhouse made	-	PET tracer; along with Prohance: MRI/PET agent
Micro-PET	Molecubes	Beta-Cube	https://www.molecubes.com/b-cube/
Small Animal MRI
Micro-MRI	Bruker Biospin	Pharmascan 70/16	https://www.bruker.com/products/mr/preclinical-mri/pharmascan.html
30 G Needle for IV injection	Beckton-Dickinson	305128
PE 10 Tubing	Instech Laboratories Inc	BTPE-10	BTPE-10, polyethylene tubing 0.011 x 0.024 in (0.28 x 60 mm), non sterile, 30 m (98 ft) spool, Instech laboratories, Inc Plymouth meeting PA USA- (800) 443-4227- http://www.instechlabs.com
Prohance contrast agent	Bracco Imaging	-	279.3 mg/mL, gadolinium-contrast agent (along with [18F]FET: MRI/PET agent)
Tx/Rx Rat Brain - Mouse Whole Body Volumecoil	Bruker Biospin	-	40 mm diameter
Water-based Heating Unit	Bruker Biospin	MT0125
Consumables
Isoflurane	Zoetis	B506	Anesthesia
Insulin Syringe Microfine	Beckton-Dickinson	320924	1 mL, 29 G
Image Analysis
MATLAB	Mathworks	-	Version R2019b
PMOD	PMOD technologies LLC		Preclinical and molecular imaging software