Objective. We propose a criterion of biological effectiveness of nonuniform hypoxia-targeted dose distributions in heterogeneous hypoxic tumors based on equivalent uniform aerobic dose (EUAD). We demonstrate the utility of this criterion by applying it to the model problems in radiotherapy for tumors with different levels of oxygen enhancement ratio (OER) and different degrees of dose nonuniformity. Approach. The EUAD is defined as the uniform dose that, under well-oxygenated conditions, produces equal integrated survival of clonogenic cells in radiotherapy for heterogeneous hypoxic tumors with a non-uniform dose distribution. We define the dose nonuniformity effectiveness (DNE) in heterogeneous tumors as the ratio of the EUAD(D-N) for a non-uniform distribution D-N and the reference EUAD(D-U) for the uniform dose distribution D-U with equal integral tumor dose. The DNE concept is illustrated in a radiotherapy model problem for non-small cell lung cancer treated with hypoxia targeted dose escalation. A two-level cell population tumor model was used to consider the hypoxic and oxygenated tumor cells. Results. Theoretical analysis of the DNE shows that the entire region of the OER can be separated in two regions by a threshold OERth: (1) OER > OERth where DNE > 1 indicating higher effectiveness of nonuniform dose distributions and (2) OER < OERth where DNE < 1 indicating higher effectiveness of uniform dose distributions. Our simulations show that the value of the threshold OERth in radiotherapy with conventional fractionation is significant in the range of about 1.2-1.6 depending on selected radiotherapy parameters. In general, the OERth increases with reoxygenation rate, relative hypoxic volume and dose escalation factor. The threshold value of OERth is smaller of about 1.1 for hypofractionated radiotherapy. Significance. The analysis of dose distributions using the DNE shows that the uniform dose distributions may improve biological cell killing effect in heterogeneous tumors with intermediate oxygen levels compared to targeted nonuniform dose distribution.

Abstract Glioblastoma is the most common and aggressive form of primary brain tumor in adults. Standard of care gadolinium-enhanced MRI (Gd-MRI) fails to capture hypoxia, a disease-defining feature of glioblastoma. Hypoxia potentiates resistance to chemo-radiation therapy (CRT) but is not extensively observed with therapy-induced pseudoprogression (PSP). This neuroinflammatory response to CRT occurs in approximately 40% of patients and is indistinguishable from disease progression by Gd-MRI, potentially causing unnecessary termination of effective therapy in patients with PSP. Additionally, delayed second line-therapy can occur in patients with resistance to CRT. This research evaluated whether [18F]-fluoromisonidazole (FMISO) positron emission tomography (PET), a noninvasive metric of tissue hypoxia, improves diagnostic accuracy in this context. Clinically, PET quantification employs the standardized uptake value (SUV), representing summed counts over an acquisition period. To add accuracy to this assessment, static 40-minute PET data acquired starting 90 minutes after FMISO injection was reconstructed into 20x2-minute frames and a relative Patlak model was applied. This technique forgoes blood sampling and extensive examination times required by traditional dynamic PET studies. The model produces two parameters that separately characterize the FMISO relative influx rate (Ki') and blood volume (VB'). In a cohort of 16 patients (3 IDH-mutated) imaged at a time of presumed disease progression, results showed that Ki' within the Gd-MRI enhancing lesion predicts future diagnosis of true progression (n = 11) or inflammation (n =5 ) with a sensitivity and specificity of 91% and 80% respectively. This outperforms diagnosis made with Gd-MRI alone, achieving ~70% for the same metrics. A t-test assuming unequal variance of cohort-wide mean Ki' tended toward significance (p = 0.07) for differentiating progressive disease (0.0036 ± 0.0016 min-1) from PSP (0.0011 ± 0.0017 min-1). RESULTS: from this study suggest relative Patlak analysis adds specificity to Gd-MRI and provides clinically relevant information regarding disease status.

The aim of this study was to report a single-institution experience and commissioning data for Elekta VersaHD linear accelerators (LINACs) for photon beams in the Eclipse treatment planning system (TPS). Two VersaHD LINACs equipped with 160-leaf collimators were commissioned. For each energy, the percent-depth-dose (PDD) curves, beam profiles, output factors, leaf transmission factors and dosimetric leaf gaps (DLGs) were acquired in accordance with the AAPM task group reports No. 45 and No. 106 and the vendor-supplied documents. The measured data were imported into Eclipse TPS to build a VersaHD beam model. The model was validated by creating treatment plans spanning over the full-spectrum of treatment sites and techniques used in our clinic. The quality assurance measurements were performed using MatriXX, ionization chamber, and radiochromic film. The DLG values were iteratively adjusted to optimize the agreement between planned and measured doses. Mobius, an independent LINAC logfile-based quality assurance tool, was also commissioned both for routine intensity-modulated radiation therapy (IMRT) QA and as a secondary check for the Eclipse VersaHD model. The Eclipse-generated VersaHD model was in excellent agreement with the measured PDD curves and beam profiles. The measured leaf transmission factors were less than 0.5% for all energies. The model validation study yielded absolute point dose agreement between ionization chamber measurements and Eclipse within +/- 4% for all cases. The comparison between Mobius and Eclipse, and between Mobius and ionization chamber measurements lead to absolute point dose agreement within +/- 5%. The corresponding 3D dose distributions evaluated with 3%global/2mm gamma criteria resulted in larger than 90% passing rates for all plans. The Eclipse TPS can model VersaHD LINACs with clinically acceptable accuracy. The model validation study and comparisons with Mobius demonstrated that the modeling of VersaHD in Eclipse necessitates further improvement to provide dosimetric accuracy on par with Varian LINACs.

To demonstrate feasibility of using mobile CT for CT-simulation and in-room image guidance for external beam radiation therapy (EBRT). An electron density (ED) phantom was scanned using mobile CT to create a ED-HU table for TPS commissioning. A custom lock-bar was fabricated to allow for attachment of radiation therapy immobilization devices to the mobile CT table. To address larger table sag of the mobile CT compared to that of conventional CT simulators, a bubble level was attached to the inferior end of the table so that an operator could correct the table rotation (pitch and roll) after a patient is loaded. Due to the lack of external moving lasers, a traditional three points-setup was utilized for CT simulation. To test feasibility of in-room image guidance using mobile CT, the mobile CT was detached from its table and moved into a linac treatment room where it was positioned beside the linac couch. With the column rotated 90 degrees, the mobile CT was used to acquire a set of volumetric images (CTmobile). Thereafter, the couch was rotated back to the default position and a reference CBCT image was acquired (CBCTref). The first rigid body image registration was performed to register CTmobile to CBCTref, thus placing the CTmobile into the treatment room coordinates (CTmobile-reg). Benefiting from high soft tissue contrast of CTmobile-reg, the second image registration was performed between the planning CT and CTmobile-reg to compute the couch shift values. In-house sequential registration software was developed to perform three-image registration as described above and to calculate couch shifts. The ED-HU table generated by the mobile CT was very similar to those generated by the conventional CT simulators in our clinic. CT simulations using mobile CT were successfully performed for 83 patients with various treatment sites such as brain (13 patients), head and neck (7), thorax (11), spine (21), abdomen (3) and pelvis (28), where a moving laser system and 4D imaging were not required. A phantom test of in-room image guidance using the mobile CT demonstrated that the proposed three-image registration-based workflow is feasible and results in improved soft tissue contrast when compared to CBCT. Our in-house registration software can calculate the couch shift values accurately (< 1 mm and < 0.3° difference compared to commercial localization software). With minor customization, mobile CT can successfully be used for CT simulation in external beam radiation therapy. In-room image guidance using mobile CT allows for improvement of soft tissue contrast and is feasible if combined with a daily CBCT imaging used for the intermediate registration. In future, we plan to develop an optical tracking system to geometrically correlate the mobile CT with the treatment coordinates which will remove the need of the intermediate CBCT scan.

PURPOSE:The purpose of this educational report is to provide an overview of the present state-of-the-art PET auto-segmentation (PET-AS) algorithms and their respective validation, with an emphasis on providing the user with help in understanding the challenges and pitfalls associated with selecting and implementing a PET-AS algorithm for a particular application. APPROACH:A brief description of the different types of PET-AS algorithms is provided using a classification based on method complexity and type. The advantages and the limitations of the current PET-AS algorithms are highlighted based on current publications and existing comparison studies. A review of the available image datasets and contour evaluation metrics in terms of their applicability for establishing a standardized evaluation of PET-AS algorithms is provided. The performance requirements for the algorithms and their dependence on the application, the radiotracer used and the evaluation criteria are described and discussed. Finally, a procedure for algorithm acceptance and implementation, as well as the complementary role of manual and auto-segmentation are addressed. FINDINGS:A large number of PET-AS algorithms have been developed within the last 20 years. Many of the proposed algorithms are based on either fixed or adaptively selected thresholds. More recently, numerous papers have proposed the use of more advanced image analysis paradigms to perform semi-automated delineation of the PET images. However, the level of algorithm validation is variable and for most published algorithms is either insufficient or inconsistent which prevents recommending a single algorithm. This is compounded by the fact that realistic image configurations with low signal-to-noise ratios (SNR) and heterogeneous tracer distributions have rarely been used. Large variations in the evaluation methods used in the literature point to the need for a standardized evaluation protocol. CONCLUSIONS:Available comparison studies suggest that PET-AS algorithms relying on advanced image analysis paradigms provide generally more accurate segmentation than approaches based on PET activity thresholds, particularly for realistic configurations. However, this may not be the case for simple shape lesions in situations with a narrower range of parameters, where simpler methods may also perform well. Recent algorithms which employ some type of consensus or automatic selection between several PET-AS methods have potential to overcome the limitations of the individual methods when appropriately trained. In either case, accuracy evaluation is required for each different PET scanner and scanning and image reconstruction protocol. For the simpler, less robust approaches, adaptation to scanning conditions, tumor type, and tumor location by optimization of parameters is necessary. The results from the method evaluation stage can be used to estimate the contouring uncertainty. All PET-AS contours should be critically verified by a physician. A standard test, i.e., a benchmark dedicated to evaluating both existing and future PET-AS algorithms needs to be designed, to aid clinicians in evaluating and selecting PET-AS algorithms and to establish performance limits for their acceptance for clinical use. The initial steps toward designing and building such a standard are undertaken by the task group members.

Purpose In radiotherapy, PET images can be used to guide the delivery of selectively escalated doses to biologically relevant tumour subvolumes. Validation of PET for such applications requires demonstration of spatial coincidence between PET tracer uptake pattern and the histopathologically confirmed target. This study introduces a novel approach to histopathological validation of PET image segmentation for radiotherapy guidance. Methods and materials Sequential tissue sections from surgically excised whole-tumour specimens were used to acquire full 3D-sets of both histopathological images (microscopy) and PET tracer distribution images (autoradiography). After these datasets were accurately registered, a full 3D autoradiographic distribution of PET tracer was reconstructed and used to obtain synthetic PET images (sPET) by simulating the image deterioration induced by processes involved in PET image formation. To illustrate the method, sPET images were used in this study to investigate spatial coincidence between high FDG uptake areas and the distribution of viable tissue in two small animal tumour models. Results The reconstructed 3D autoradiographic distribution of the PET tracer was spatially coherent, as indicated by the high average value of the normalised pixel-by-pixel correlation of intensities between successive slices (0.84 ± 0.05 and 0.94 ± 0.02). The loss of detail in the sPET images versus the 3D autoradiography was significant as indicated by Dice coefficient values corresponding to the two tumours (0 and 0.1 at 70% threshold). The maximum overlap between the FDG segmented volumes and the extent of the viable tissue as indicated by Dice coefficient values, was 0.8 for one tumour (for the image thresholded at 22% of max intensity) and 0.88 for the other (threshold of 14% of max intensity). Conclusion It was demonstrated that the use of synthetic PET images for histopathological validation allows for bypassing a technically challenging and error-prone step of registering non-invasive PET images with histopathology.

Purpose: To develop methods for pre‐clinical validation of PET image‐guided selective dose escalation in IMRT treatment using the Small Animal Radiation Research Platform (SARRP, Xstrahl). Methods: Nude mice bearing subcutaneous FaDu human head and neck tumor xenografts were imaged with 18F‐FDG using a Siemens Inveon PET/CT. The PET image was used to create an image‐guided radiation treatment plan treating the entirety of the tumor with a 10Gy uniform radiation dose while sparing as much normal tissue as possible using a 15mm collimator. A dose escalation of 10 Gy was planned to treat the volume of highest FDG uptake within the tumor. To ensure localized dose distribution, the boost was to be delivered using dynamic arc techniques with a 5mm collimator. The isocenters for both fields were recorded on the planning PET image. The following day, the animals were anaesthetized, positioned in the SARRP irradiator, and imaged using on‐board cone‐beam to obtain an image in the treatment position. The planning CT was then deformably registered to the treatment CT using the BRAINSFit b‐spline algorithm in SLICER 3D. Finally, the transform was applied to the planning PET and isocenters for the treatment fields were transferred to the treatment CT while the animal was still under anesthesia. The animal was then irradiated according to the original PET/CT‐guided treatment plan. Results: SARRP allows for selective dose escalation treatments to small animal tumor models. In this study a subcutaneously grown tumor of 12mm in diameter was irradiated to 10Gy. The volume of the tumor characterized by increased FDG uptake received an additional 10Gy in the form of a 5mm‐diameter boost delivered with non‐coplanar arc field. Conclusion: The Small Animal Radiation Research Platform (SARRP) combined with a dedicated small animal PET/CT scanner enables pre‐clinical validation of PET image‐guided selective dose escalation in IMRT treatment.

The purpose of this study was to investigate the increase in cell kill that can be achieved by tumor irradiation with heterogeneous dose distributions targeting hypoxic regions that can be visualized with non-invasive imaging. Starting with a heterogeneous distribution of microvessels, a microscopic two-dimensional model of tumor oxygenation was developed using planar simulation of oxygen diffusion. Non-invasive imaging of hypoxia was simulated taking partial volume effect into account. A dose-modulation scheme was implemented with the goal of delivering higher doses to the hypoxic pixels, as seen in simulated hypoxia images. To determine the relative cell kill in response to hypoxia-targeting irradiation, tumor cell survival fractions were compared to those resulting from treatments delivering the same average dose to the lesion in a spatially uniform fashion. It was shown that hypoxia-targeting dose modulation may be better suited for tumors with low α/β, low hypoxic fraction and spatially aggregated hypoxic features. Most importantly, it was determined that at low fraction doses there is no cell kill increase from targeting hypoxic regions alone versus escalating the total tumor dose. However, for higher doses per fraction (≥8 Gy/fraction), the effectiveness of hypoxia-targeting irradiation increases, resulting in the tumoricidal effect of up to 30% higher than that of uniform tumor irradiation delivering the same average tumor dose.

Background and purposePET imaging with 18F-fluorothymidine (18F-FLT) can potentially be used to identify tumour subvolumes for selective dose escalation in radiation therapy. The purpose of this study is to analyse the co-localization of intratumoural patterns of cell proliferation with 18F-FLT tracer uptake.Materials and methodsMice bearing FaDu or SQ20B xenograft tumours were injected with 18F-FLT, and bromodeoxyuridine (proliferation marker). Ex vivo images of the spatial pattern of intratumoural 18F-FLT uptake and that of bromodeoxyuridine DNA incorporation were obtained from thin tumour tissue sections. These images were segmented by thresholding and Relative Operating Characteristic (ROC) curves and Dice similarity indices were evaluated.ResultsThe thresholds at which maximum overlap occurred between FLT-segmented areas and areas of active cell proliferation were significantly different for the two xenograft tumour models, whereas the median Dice values were not. However, ROC analysis indicated that segmented FLT images were more specific at detecting the proliferation pattern in FaDu tumours than in SQ20B tumours.ConclusionHighly dispersed patterns of cell proliferation observed in certain tumours can affect the perceived spatial concordance between the spatial pattern of 18F-FLT uptake and that of cell proliferation even when high-resolution ex vivo autoradiography imaging is used for 18F-FLT imaging.

PURPOSE:PET imaging allows for the visualization of tumor microenvironment and identification of aggressive or radioresistant tumor subvolumes that can be targeted with an escalated radiation dose. Multiple PET tracers have been developed for visualization of different aspects of tumor microenvironment; however, the spatial distribution of tracers in tumors is equally affected by tumor tissue viability and tracer delivery limitations. Given these issues and the low resolution associated with PET imaging, two different PET tracers can produce very similar images. Therefore, it is important to demonstrate that a novel PET tracer does provide additional useful information to that obtained with other tracers. This study investigates the added value of performing 18F-FLT PET imaging as well as 18F-FDG imaging.METHODS:Head and neck tumor xenografts grown in nude mice were used to study intratumoral tracerdistributions. 18F-FDG and 18F-FLT PET images were obtained on subsequent days using a small animal PET/CT. Pinnacle 9 was used to deformably register the CT image from the FLT PET/CT to the FDG PET/CT image set. The generated deformation was applied to the FLT PET image to achieve an unbiased FLT to FDG PET image registration. The Pearson correlation coefficient between FDG and FLT was calculated voxel- by-voxel within a tumor contour. Overlap analysis of thresholded tracer distributions was carried out by comparing Dice similarity coefficients.RESULTS:Both SQ20B and FaDu tumors showed a moderate voxel-by-voxel correlation between FDG and FLT intratumoral patterns of uptake with an average rho value of .56 and .63 respectively (range .37-.76) despite significant differences in tumor morphology. The average volumes under thedice coefficient surface for SQ20B and FaDu tumors were not significantly different.CONCLUSIONS:Despite being equally affected by the issues of tracer delivery, necrosis and PET resolution, FDG and FLT PET images displayed an observable difference at clinically relevant thresholds.

Purpose: It has been proposed that PET images can be used to guide the delivery of selectively escalated doses to biologically-relevant tumor subvolumes. Histopathological validation of PET imaging is challenging due to difficulties associated with precise registration of non-invasive in-vivo images to histopathological ex-vivo images. The aim of this study is to develop an alternative method of PET imaging validation for image-guidance applications. The method is applied to evaluation of the feasibility of FDG PET-based delineation of viable tissue in animal tumor models. Methods: Tumor-bearing mice were injected with 14C-FDG. Whole-tumor specimens were sectioned, obtaining 8μm thick sections every 120μm throughout the tumor. These sections were used to obtain 14C-FDG autoradiography and H&E microscopy images. Viable tumor tissue was delineated on each H&E image. Based on sequential digital photography images of the tissue block acquired during sectioning, the true 3D distributions of 14C-FDG and viable tissue were reconstituted. To simulate generation of a PET image, the 3D activity map was convolved with a 3D point-spread-function of Siemens Inveon small-animal PET scanner. Threshold-based analysis was used to evaluate the degree of coincidence between the areas of high FDG uptake in the simulated PET image and 3D distribution of viable tissue. Results: Averaging effects associated with PET imaging altered the true 3D spatial pattern of FDG intratumoral uptake. ROC analysis indicated good sensitivity of FDG PET image-segmentation for the detection of the viable tissue (AUC = 0.74). However, the specificity was low, as indicated by the low threshold value at which the maximum overlap occurred (22% of maximum uptake). Conclusion: A novel method of histopathological validation of PET imaging for image-guidance in radiotherapy was developed. Using this method, it was demonstrated that for the tumors with high viable tissue content, FDG-thresholding can be used for viable tissue detection.

Positron Emission Tomography (PET) imaging of the fluorodeoxyglucose (18F‐FDG) has been the workhorse of oncologic nuclear medicine as it allows for the detection of most cancer lesions with high sensitivity and specificity. However, for the purpose of radiation therapy treatment planning, it is important not only to detect the disease but also to define its extent and, potentially, the subvolumes characterized by different levels of radioresistance. Correspondingly, for PET‐based treatment planning it is not the uptake of the tracer in the lesion as a whole but rather the spatial pattern of the tracer uptake that is used to derive the spatial characteristics of the prescribed dose. Therefore, demonstration of positive correlation between PET SUV value and a certain histopathological measure across a cohort of patients is not sufficient to validate the use of PET tracer for treatment planning. Instead, validation of PET tracers has to include a step demonstrating spatial concordance of the tracer uptake pattern with the distribution of the feature of interest, i.e. hypoxia, proliferation, etc. The presentation will demonstrate that direct imaging of any tumor microenvirionmental parameter in detail is not achievable with any clinically‐relevant non‐invasive imaging modality, as the required resolution would have to be under 100micron. Instead, PET image obtained with any tracer represents a convolution of the point spread function of the imaging device with the tissue viability, PET tracer delivery (availability), and, finally, the specificity of the tracer. Correspondingly, utilization of “functional PET volume” delineation techniques for defining therapeutic targets should be approached carefully. A non‐binary dose‐painting approach using a well characterized tracer might constitute a more robust method of utilization of biological information that can be obtained with PET.Learning objectives:1. Become aware of the role played by the highly heterogeneous nature of tumor microenvironment in the formation of PET image.2. Understand the importance of the spatial distribution of the tracer as opposed to a single‐value characteristic such as maximum or average SUV when PET image is to be used for radiation treatment planning.3. Learn about alternative non‐binary ways of utilization of PET imaging in radiation treatment planning.

Histopathologic validation of a PET tracer requires assessment of colocalization of the tracer with its intended biologic target. Using thin tissue section autoradiography, it is possible to visualize the spatial distribution of the PET tracer uptake and compare it with the distribution of the intended biologic target (as visualized with immunohistochemistry). The purpose of this study was to develop and evaluate an objective methodology for deformable coregistration of autoradiography and microscopy images acquired from a set of sequential tissue sections. Methods: Tumor-bearing animals were injected with 3′-deoxy-3′-18F-fluorothymidine (18F-FLT), 14C-FDG, and other markers of tumor microenvironment including Hoechst 33342 (blood-flow surrogate). After sacrifice, tumors were excised, frozen, and sectioned. Multiple stacks of sequential 8 μm sections were collected from each tumor. From each stack, the middle (reference) sections were used to obtain images of 18F-FLT and 14C-FDG uptake distributions using dual-tracer autoradiography. Sections adjacent to the reference were used to acquire all histopathologic data (e.g., images of cell proliferation, hematoxylin and eosin). Hoechst images were acquired from all sections. To correct for deformations and misalignments induced by tissue processing and image acquisition, the Hoechst image of each nonreference section was deformably registered to the reference Hoechst image. This transformation was then applied to all images acquired from the same tissue section. In this way, all microscopy images were registered to the reference Hoechst image. The Hoechst-to-autoradiography image registration was done using rigid point-set registration based on external markers visible in both images. Results: The mean error of Hoechst to 18F-FLT autoradiography registration (both images acquired from the same section) was 30.8 ± 20.1 μm. The error of Hoechst-based deformable registration of histopathologic images (acquired from sequential tissue sections) was 23.1 ± 17.9 μm. Total error of registration of autoradiography images to the histopathologic images acquired from adjacent sections was evaluated at 44.9 μm. This coregistration precision supersedes current rigid registration methods with reported errors of 100–200 μm. Conclusion: Deformable registration of autoradiography and histopathology images acquired from sequential sections is feasible and accurate when performed using corresponding Hoechst images.