Ultra-hypofractionated prostate cancer radiotherapy: Dosimetric impact of real-time intrafraction prostate motion and daily anatomical changes.

PURPOSE: To retrospectively assess the differences between planned and delivered dose during ultra-hypofractionated (UHF) prostate cancer treatments, by evaluating the dosimetric impact of daily anatomical variations alone, and in combination with prostate intrafraction motion. METHODS: Prostate intrafraction motion was recorded with a transperineal ultrasound probe in 15 patients treated by UHF radiotherapy (36.25 Gy/5 fractions). The dosimetric objective was to cover 99 % of the clinical target volume with the 100 % prescription isodose line. After treatment, planning CT (pCT) images were deformably registered onto daily Cone Beam CT to generate pseudo-CT for dose accumulation (accumulated CT, aCT). The interplay effect was accounted by synchronizing prostatic shifts and beam geometry. Finally, the shifted dose maps were accumulated (moved-accumulated CT, maCT). RESULTS: No significant change in daily CTV volumes was observed. Conversely, CTV V100% was 98.2 ± 0.8 % and 94.7 ± 2.6 % on aCT and maCT, respectively, compared with 99.5 ± 0.2 % on pCT (p < 0.0001). Bladder volume was smaller than planned in 76 % of fractions and D5cc was 33.8 ± 3.2 Gy and 34.4 ± 3.4 Gy on aCT (p = 0.02) and maCT (p = 0.01) compared with the pCT (36.0 ± 1.1 Gy). The rectum was smaller than planned in 50.3 % of fractions, but the dosimetric differences were not statistically significant, except for D1cc, found smaller on the maCT (33.2 ± 3.2 Gy, p = 0.02) compared with the pCT (35.3 ± 0.7 Gy). CONCLUSIONS: Anatomical variations and prostate movements had more important dosimetric impact than anatomical variations alone, although, in some cases, the two phenomena compensated. Therefore, an efficient IGRT protocol is required for treatment implementation to reduce setup errors and control intrafraction motion.

Performance study of a 360° CZT camera for monitoring 177Lu-PSMA treatment.

BACKGROUND: The aim of this study was to investigate the quantification performance of a 360° CZT camera for 177Lu-based treatment monitoring. METHODS: Three phantoms with known 177Lu activity concentrations were acquired: (1) a uniform cylindrical phantom for calibration, (2) a NEMA IEC body phantom for analysis of different-sized spheres to optimise quantification parameters and (3) a phantom containing two large vials simulating organs at risk for tests. Four sets of reconstruction parameters were tested: (1) Scatter, (2) Scatter and Point Spread Function Recovery (PSFR), (3) PSFR only and (4) Penalised likelihood option and Scatter, varying the number of updates (iterations × subsets) with CT-based attenuation correction only. For each, activity concentration (ARC) and contrast recovery coefficients (CRC) were estimated as well as root mean square. Visualisation and quantification parameters were applied to reconstructed patient image data. RESULTS: Optimised quantification parameters were determined to be: CT-based attenuation correction, scatter correction, 12 iterations, 8 subsets and no filter. ARC, CRC and RMS results were dependant on the methodology used for calculations. Two different reconstruction parameters were recommended for visualisation and for quantification. 3D whole-body SPECT images were acquired and reconstructed for 177Lu-PSMA patients in 2-3 times faster than the time taken for a conventional gamma camera. CONCLUSION: Quantification of whole-body 3D images of patients treated with 177Lu-PSMA is feasible and an optimised set of parameters has been determined. This camera greatly reduces procedure time for whole-body SPECT.

Evaluation of different algorithms for automatic segmentation of head-and-neck lymph nodes on CT images.

PURPOSE: To investigate the performance of 4 atlas-based (multi-ABAS) and 2 deep learning (DL) solutions for head-and-neck (HN) elective nodes (CTVn) automatic segmentation (AS) on CT images. MATERIAL AND METHODS: Bilateral CTVn levels of 69 HN cancer patients were delineated on contrast-enhanced planning CT. Ten and 49 patients were used for atlas library and for training a mono-centric DL model, respectively. The remaining 20 patients were used for testing. Additionally, three commercial multi-ABAS methods and one commercial multi-centric DL solution were investigated. Quantitative evaluation was assessed using volumetric Dice Similarity Coefficient (DSC) and 95-percentile Hausdorff distance (HD95%). Blind evaluation was performed for 3 solutions by 4 physicians. One recorded the time needed for manual corrections. A dosimetric study was finally conducted using automated planning. RESULTS: Overall DL solutions had better DSC and HD95% results than multi-ABAS methods. No statistically significant difference was found between the 2 DL solutions. However, the contours provided by multi-centric DL solution were preferred by all physicians and were also faster to correct (1.1 min vs 4.17 min, on average). Manual corrections for multi-ABAS contours took on average 6.52 min Overall, decreased contour accuracy was observed from CTVn2 to CTVn3 and to CTVn4. Using the AS contours in treatment planning resulted in underdosage of the elective target volume. CONCLUSION: Among all methods, the multi-centric DL method showed the highest delineation accuracy and was better rated by experts. Manual corrections remain necessary to avoid elective target underdosage. Finally, AS contours help reducing the workload of manual delineation task.

OpenSpyrit: an ecosystem for open single-pixel hyperspectral imaging.

This paper describes OpenSpyrit, an open access and open source ecosystem for reproducible research in hyperspectral single-pixel imaging, composed of SPAS (a Python single-pixel acquisition software), SPYRIT (a Python single-pixel reconstruction toolkit) and SPIHIM (a single-pixel hyperspectral image collection). The proposed OpenSpyrit ecosystem responds to the need for reproducibility and benchmarking in single-pixel imaging by providing open data and open software. The SPIHIM collection, which is the first open-access FAIR dataset for hyperspectral single-pixel imaging, currently includes 140 raw measurements acquired using SPAS and the corresponding hypercubes reconstructed using SPYRIT. The hypercubes are reconstructed by both inverse Hadamard transformation of the raw data and using the denoised completion network (DC-Net), a data-driven reconstruction algorithm. The hypercubes obtained by inverse Hadamard transformation have a native size of 64 × 64 × 2048 for a spectral resolution of 2.3 nm and a spatial resolution that is comprised between 182.4 µm and 15.2 µm depending on the digital zoom. The hypercubes obtained using the DC-Net are reconstructed at an increased resolution of 128 × 128 × 2048. The OpenSpyrit ecosystem should constitute a reference to support benchmarking for future developments in single-pixel imaging.

Management of reirradiations: A clinical and technical overview based on a French survey.

INTRODUCTION: The reirradiation number increased due to systemic therapies and patient survival. Few guidelines regarding acceptable cumulative doses to organs at risk (OARs) and appropriate dose accumulation tools need, made reirradiation challenging. The survey objective was to present the French current technical and clinical practices in reirradiations. METHODS: A group of physician and physicists developed a survey gathering major issues of the topic. The questionnaire consisted in 4 parts: data collection, demographic, clinical and technical aspects. It was delivered through the SFRO and the SFPM. Data collection lasted 2 months and were gathered to compute statistical analysis. RESULTS: 48 institutions answered the survey. Difficulties about patient data collection were related to patient safety, administrative and technical limitations. Half of the institutions discussed reirradiation cases during a multidisciplinary meeting. It mainly aimed at discussing the indication and the new treatment total dose (92%). 79% of the respondents used various references but only 6% of them were specific to reirradiations. Patients with pain and clinical deficit were ranked as best inclusion criteria. 54.2% of the institutions considered OARs recovery, especially for spinal cord and brainstem. A commercial software was used for dose accumulation for 52% of respondents. Almost all institutions performed equivalent dose conversion (94%). A quarter of the institutions estimated not to have the appropriate equipment for reirradiation. CONCLUSION: This survey showed the various approaches and tools used in reirradiation management. It highlighted issues in collecting data, and the guidelines necessity for safe practices, to increase clinicians confidence in retreating patients.

Evaluation of a dedicated software for semi-automated VMAT planning of spine Stereotactic Body Radiotherapy (SBRT).

PURPOSE: To determine whether SBRT of spinal metastasis using a dedicated treatment planning system (TPS) and delivered with a gantry-based LINAC could provide plans of similar quality to the Cyberknife technology. Additional comparison was also done with other commercial TPS used for volumetric modulated arc therapy (VMAT) planning. MATERIALS AND METHODS: Thirty Spine SBRT patients, previously treated in our institution with CyberKnife (Accuray, Sunnyvale) using Multiplan TPS, were replanned in VMAT with an dedicated TPS (Elements Spine SRS, Brainlab, Munich) and our clinical TPS (Monaco, Elekta LTD, Stockholm), using exactly the same arc geometry. The comparison was done by assessing differences in dose delivered to PTV, CTV and spinal cord, calculating modulation complexity scores (MCS) and performing quality control (QA) of the plans. RESULTS: Regardless of the vertebra level, in general, no statistical difference was found in PTV coverage between all TPS. Conversely, PTV and CTV D50% were found significantly higher for the dedicated TPS compared to others. In addition, the dedicated TPS also resulted in better gradient index (GI) than clinical VMAT TPS, whatever the vertebral level, and better GI than Cyberknife TPS for the thoracic level only. The D2% to the spinal cord was generally significantly lower with the dedicated TPS compared with others. No significant difference was found in the MCS between both VMAT TPS. All QA were clinically acceptable. CONCLUSION: The Elements Spine SRS TPS offers very effective and user-friendly semi-automated planning tools and is secure and promising for gantry-based LINAC spinal SBRT.

From netrin-1-targeted SPECT/CT to internal radiotherapy for management of advanced solid tumors.

Targeted radionuclide therapy is a revolutionary tool for the treatment of highly spread metastatic cancers. Most current approaches rely on the use of vectors to deliver radionuclides to tumor cells, targeting membrane-bound cancer-specific moieties. Here, we report the embryonic navigation cue netrin-1 as an unanticipated target for vectorized radiotherapy. While netrin-1, known to be re-expressed in tumoral cells to promote cancer progression, is usually characterized as a diffusible ligand, we demonstrate here that netrin-1 is actually poorly diffusible and bound to the extracellular matrix. A therapeutic anti-netrin-1 monoclonal antibody (NP137) has been preclinically developed and was tested in various clinical trials showing an excellent safety profile. In order to provide a companion test detecting netrin-1 in solid tumors and allowing the selection of therapy-eligible patients, we used the clinical-grade NP137 agent and developed an indium-111-NODAGA-NP137 single photon emission computed tomography (SPECT) contrast agent. NP137-111 In provided specific detection of netrin-1-positive tumors with an excellent signal-to-noise ratio using SPECT/CT imaging in different mouse models. The high specificity and strong affinity of NP137 paved the way for the generation of lutetium-177-DOTA-NP137, a novel vectorized radiotherapy, which specifically accumulated in netrin-1-positive tumors. We demonstrate here, using tumor cell-engrafted mouse models and a genetically engineered mouse model, that a single systemic injection of NP137-177 Lu provides important antitumor effects and prolonged mouse survival. Together, these data support the view that NP137-111 In and NP137-177 Lu may represent original and unexplored imaging and therapeutic tools against advanced solid cancers.

Dosimetric impact of 3D motion-compensated SPECT reconstruction for SIRT planning.

BACKGROUND: In selective internal radiation therapy, 99mTc SPECT images are used to optimize patient treatment planning, but they are affected by respiratory motion. In this study, we evaluated on patient data the dosimetric impact of motion-compensated SPECT reconstruction on several volumes of interest (VOI), on the tumor-to-normal liver (TN) ratio and on the activity to be injected. METHODS: Twenty-nine patients with liver cancer or hepatic metastases treated by radioembolization were included in this study. The biodistribution of 90Y is assumed to be the same as that of 99mTc when predictive dosimetry is implemented. A total of 31 99mTc SPECT images were acquired and reconstructed with two methods: conventional OSEM (3D) and motion-compensated OSEM (3Dcomp). Seven VOI (liver, lungs, tumors, perfused liver, hepatic reserve, healthy perfused liver and healthy liver) were delineated on the CT or obtained by thresholding SPECT images followed by Boolean operations. Absorbed doses were calculated for each reconstruction using Monte Carlo simulations. Percentages of dose difference (PDD) between 3Dcomp and 3D reconstructions were estimated as well as the relative differences for TN ratio and activities to be injected. The amplitude of movement was determined with local rigid registration of the liver between the 3Dcomp reconstructions of the extreme phases of breathing. RESULTS: The mean amplitude of the liver was 9.5 ± 2.7 mm. Medians of PDD were closed to zero for all VOI except for lungs (6.4%) which means that the motion compensation overestimates the absorbed dose to the lungs compared to the 3D reconstruction. The smallest lesions had higher PDD than the largest ones. Between 3D and 3Dcomp reconstructions, means of differences in lung dose and TN ratio were not statistically significant, but in some cases these differences exceed 1 Gy (4/31) and 8% (2/31). The absolute differences in activity were on average 3.1% ± 5.1% and can reach 22.8%. CONCLUSION: The correction of respiratory motion mainly impacts the lung and tumor doses but only for some patients. The largest dose differences are observed for the smallest lesions.

Comparison of atlas-based and deep learning methods for organs at risk delineation on head-and-neck CT images using an automated treatment planning system.

BACKGROUND AND PURPOSE: To investigate the performance of head-and-neck (HN) organs-at-risk (OAR) automatic segmentation (AS) using four atlas-based (ABAS) and two deep learning (DL) solutions. MATERIAL AND METHODS: All patients underwent iodine contrast-enhanced planning CT. Fourteen OAR were manually delineated. DL.1 and DL.2 solutions were trained with 63 mono-centric patients and > 1000 multi-centric patients, respectively. Ten and 15 patients with varied anatomies were selected for the atlas library and for testing, respectively. The evaluation was based on geometric indices (DICE coefficient and 95th percentile-Hausdorff Distance (HD95%)), time needed for manual corrections and clinical dosimetric endpoints obtained using automated treatment planning. RESULTS: Both DICE and HD95% results indicated that DL algorithms generally performed better compared with ABAS algorithms for automatic segmentation of HN OAR. However, the hybrid-ABAS (ABAS.3) algorithm sometimes provided the highest agreement to the reference contours compared with the 2 DL. Compared with DL.2 and ABAS.3, DL.1 contours were the fastest to correct. For the 3 solutions, the differences in dose distributions obtained using AS contours and AS + manually corrected contours were not statistically significant. High dose differences could be observed when OAR contours were at short distances to the targets. However, this was not always interrelated. CONCLUSION: DL methods generally showed higher delineation accuracy compared with ABAS methods for AS segmentation of HN OAR. Most ABAS contours had high conformity to the reference but were more time consuming than DL algorithms, especially when considering the computing time and the time spent on manual corrections.

Deep learning-based segmentation in prostate radiation therapy using Monte Carlo simulated cone-beam computed tomography.

PURPOSE: Segmenting organs in cone-beam CT (CBCT) images would allow to adapt the radiotherapy based on the organ deformations that may occur between treatment fractions. However, this is a difficult task because of the relative lack of contrast in CBCT images, leading to high inter-observer variability. Deformable image registration (DIR) and deep-learning based automatic segmentation approaches have shown interesting results for this task in the past years. However, they are either sensitive to large organ deformations, or require to train a convolutional neural network (CNN) from a database of delineated CBCT images, which is difficult to do without improvement of image quality. In this work, we propose an alternative approach: to train a CNN (using a deep learning-based segmentation tool called nnU-Net) from a database of artificial CBCT images simulated from planning CT, for which it is easier to obtain the organ contours. METHODS: Pseudo-CBCT (pCBCT) images were simulated from readily available segmented planning CT images, using the GATE Monte Carlo simulation. CT reference delineations were copied onto the pCBCT, resulting in a database of segmented images used to train the neural network. The studied segmentation contours were: bladder, rectum, and prostate contours. We trained multiple nnU-Net models using different training: (1) segmented real CBCT, (2) pCBCT, (3) segmented real CT and tested on pseudo-CT (pCT) generated from CBCT with cycleGAN, and (4) a combination of (2) and (3). The evaluation was performed on different datasets of segmented CBCT or pCT by comparing predicted segmentations with reference ones thanks to Dice similarity score and Hausdorff distance. A qualitative evaluation was also performed to compare DIR-based and nnU-Net-based segmentations. RESULTS: Training with pCBCT was found to lead to comparable results to using real CBCT images. When evaluated on CBCT obtained from the same hospital as the CT images used in the simulation of the pCBCT, the model trained with pCBCT scored mean DSCs of 0.92 ± 0.05, 0.87 ± 0.02, and 0.85 ± 0.04 and mean Hausdorff distance 4.67 ± 3.01, 3.91 ± 0.98, and 5.00 ± 1.32 for the bladder, rectum, and prostate contours respectively, while the model trained with real CBCT scored mean DSCs of 0.91 ± 0.06, 0.83 ± 0.07, and 0.81 ± 0.05 and mean Hausdorff distance 5.62 ± 3.24, 6.43 ± 5.11, and 6.19 ± 1.14 for the bladder, rectum, and prostate contours, respectively. It was also found to outperform models using pCT or a combination of both, except for the prostate contour when tested on a dataset from a different hospital. Moreover, the resulting segmentations demonstrated a clinical acceptability, where 78% of bladder segmentations, 98% of rectum segmentations, and 93% of prostate segmentations required minor or no corrections, and for 76% of the patients, all structures of the patient required minor or no corrections. CONCLUSION: We proposed to use simulated CBCT images to train a nnU-Net segmentation model, avoiding the need to gather complex and time-consuming reference delineations on CBCT images.

The OpenGATE ecosystem for Monte Carlo simulation in medical physics.

This paper reviews the ecosystem of GATE, an open-source Monte Carlo toolkit for medical physics. Based on the shoulders of Geant4, the principal modules (geometry, physics, scorers) are described with brief descriptions of some key concepts (Volume, Actors, Digitizer). The main source code repositories are detailed together with the automated compilation and tests processes (Continuous Integration). We then described how the OpenGATE collaboration managed the collaborative development of about one hundred developers during almost 20 years. The impact of GATE on medical physics and cancer research is then summarized, and examples of a few key applications are given. Finally, future development perspectives are indicated.

Patient-specific dosimetry adapted to variable number of SPECT/CT time-points per cycle for [Formula: see text]Lu-DOTATATE therapy.

BACKGROUND: The number of SPECT/CT time-points is important for accurate patient dose estimation in peptide receptor radionuclide therapy. However, it may be limited by the patient's health and logistical reasons. Here,  an image-based dosimetric workflow adapted to the number of SPECT/CT acquisitions available throughout the treatment cycles was proposed, taking into account patient-specific pharmacokinetics and usable in clinic for all organs at risk. METHODS: Thirteen patients with neuroendocrine tumors were treated with four injections of 7.4 GBq of [Formula: see text]Lu-DOTATATE. Three SPECT/CT images were acquired during the first cycle (1H, 24H and 96H or 144H post-injection) and a single acquisition (24H) for following cycles. Absorbed doses were estimated for kidneys (LK and RK), liver (L), spleen (S), and three surrogates of bone marrow (L2 to L4, L1 to L5 and T9 to L5) that were compared. 3D dose rate distributions were computed with Monte Carlo simulations. Voxel dose rates were averaged at the organ level. The obtained Time Dose-Rate Curves (TDRC) were fitted with a tri-exponential model and time-integrated. This method modeled patient-specific uptake and clearance phases observed at cycle 1. Obtained fitting parameters were reused for the following cycles, scaled to the measure organ dose rate at 24H. An alternative methodology was proposed when some acquisitions were missing based on population average TDRC (named STP-Inter). Seven other patients with three SPECT/CT acquisitions at cycles 1 and 4 were included to estimate the uncertainty of the proposed methods. RESULTS: Absorbed doses (in Gy) per cycle available were: 3.1 ± 1.1 (LK), 3.4 ± 1.5 (RK), 4.5 ± 2.8 (L), 4.6 ± 1.8 (S), 0.3 ± 0.2 (bone marrow). There was a significant difference between bone marrow surrogates (L2 to L4 and L1 to L5, Wilcoxon's test: p value < 0.05), and while depicting very doses, all three surrogates were significantly different than dose in background (p value < 0.01). At cycle 1, if the acquisition at 24H is missing and approximated, medians of percentages of dose difference (PDD) compared to the initial tri-exponential function were inferior to 3.3% for all organs. For cycles with one acquisition, the median errors were smaller with a late time-point. For STP-Inter, medians of PDD were inferior to 7.7% for all volumes, but it was shown to depend on the homogeneity of TDRC. CONCLUSION: The proposed workflow allows the estimation of organ doses, including bone marrow, from a variable number of time-points acquisitions for patients treated with [Formula: see text]Lu-DOTATATE.

Minimum non-isotropic and asymmetric margins for taking into account intrafraction prostate motion during moderately hypofractionated radiotherapy.

PURPOSE: To investigate the impact on dose distribution of intrafraction motion during moderate hypofractionated prostate cancer treatments and to estimate minimum non-isotropic and asymmetric (NI-AS) treatment margins taking motion into account. METHODS: Prostate intrafraction 3D displacements were recorded with a transperineal ultrasound probe and were evaluated in 46 prostate cancer patients (876 fractions) treated by moderate hypofractionated radiation therapy (60 Gy in 20 fractions). For 18 patients (346 fractions), treatment plans were recomputed increasing CTV-to-PTV margins from 0 to 6 mm with an auto-planning optimization algorithm. Dose distribution was estimated using the voxel shifting method by displacing CTV structure according to the retrieved movements. Time-dependent margins were finally calculated using both van Herk's formula and the voxel shifting method. RESULTS: Mean intrafraction prostate displacements observed were -0.02 ± 0.52 mm, 0.27 ± 0.78 mm and -0.43 ± 1.06 mm in left-right, supero-inferior and antero-posterior directions, respectively. The CTV dosimetric coverage increased with increased CTV-to-PTV margins but it decreased with time. Hence using van Herk's formula, after 7 min of treatment, a margin of 0.4 and 0.5 mm was needed in left and right, 1.5 and 0.7 mm in inferior and superior and 1.1 and 3.2 mm in anterior and posterior directions, respectively. Conversely, using the voxel shifting method, a margin of 0 mm was needed in left-right, 2 mm in superior, 3 mm in inferior and anterior and 5 mm in posterior directions, respectively. With this latter NI-AS margin strategy, the dosimetric target coverage was equivalent to the one obtained with a 5 mm homogeneous margin. CONCLUSIONS: NI-AS margins would be required to optimally take into account intrafraction motion.

Yttrium-90 quantitative phantom study using digital photon counting PET.

BACKGROUND: PET imaging of 90Y-microsphere distribution following radioembolisation is challenging due to the count-starved statistics from the low branching ratio of e+/e- pair production during 90Y decay. PET systems using silicon photo-multipliers have shown better 90Y image quality compared to conventional photo-multiplier tubes. The main goal of the present study was to evaluate reconstruction parameters for different phantom configurations and varying listmode acquisition lengths to improve quantitative accuracy in 90Y dosimetry, using digital photon counting PET/CT. METHODS: Quantitative PET and dosimetry accuracy were evaluated using two uniform cylindrical phantoms specific for PET calibration validation. A third body phantom with a 9:1 hot sphere-to-background ratio was scanned at different activity concentrations of 90Y. Reconstructions were performed using OSEM algorithm with varying parameters. Time-of-flight and point-spread function modellings were included in all reconstructions. Absorbed dose calculations were carried out using voxel S-values convolution and were compared to reference Monte Carlo simulations. Dose-volume histograms and root-mean-square deviations were used to evaluate reconstruction parameter sets. Using listmode data, phantom and patient datasets were rebinned into various lengths of time to assess the influence of count statistics on the calculation of absorbed dose. Comparisons between the local energy deposition method and the absorbed dose calculations were performed. RESULTS: Using a 2-mm full width at half maximum post-reconstruction Gaussian filter, the dosimetric accuracy was found to be similar to that found with no filter applied but also reduced noise. Larger filter sizes should not be used. An acquisition length of more than 10 min/bed reduces image noise but has no significant impact in the quantification of phantom or patient data for the digital photon counting PET. 3 iterations with 10 subsets were found suitable for large spheres whereas 1 iteration with 30 subsets could improve dosimetry for smaller spheres. CONCLUSION: The best choice of the combination of iterations and subsets depends on the size of the spheres. However, one should be careful on this choice, depending on the imaging conditions and setup. This study can be useful in this choice for future studies for more accurate 90Y post-dosimetry using a digital photon counting PET/CT.

In vivo gadolinium nanoparticle quantification with SPECT/CT.

BACKGROUND: Gadolinium nanoparticles (Gd-NP) combined with radiotherapy are investigated for radiation dose enhancement in radiotherapy treatment. Indeed, NPs concentrated in a tumor could enhance its radiosensitization. The noninvasive quantification of the NP concentration is a crucial task for radiotherapy treatment planning and post-treatment monitoring as it will determine the absorbed dose. In this work, we evaluate the achievable accuracy of in vivo SPECT-based Gd-NP organ concentration on rats. METHODS: Gd-NPs were labeled with 111In radionuclide. SPECT images have been acquired on phantom and rats, with various Gd-NP injections. Images have been calibrated and corrected for attenuation, scatter, and partial volume effect. Image-based estimations were compared to both inductively coupled plasma mass spectrometer (ICP-MS) for Gd concentration and ex vivo organ activity measured by gamma counter. RESULTS: The accuracy for the Gd mass measurements in organ was within 10% for activity above 2 MBq or concentrations above ∼ 3-4 MBq/mL. The Gd mass calculation is based on In-Gd coefficient which defines the Gd detection limit. It was found to be in a range from 2 mg/MBq to 2 µg/MBq depending on the proportions of initial injection preparations. Measurement was also impaired by free Gd and 111In formed during metabolic processes. CONCLUSIONS: Even if SPECT image quantification remains challenging mostly due to partial volume effect, this study shows that it has potential for the Gd mass measurements in organ. The main limitation of the method is its indirectness, and a special care should be taken if the organ of interest could be influenced by different clearance rate of free Gd and 111In formed by metabolic processes. We also discuss the practical aspects, potential, and limitations of Gd-NP in vivo image quantification with a SPECT.

Deformable image registration applied to lung SBRT: Usefulness and limitations.

Radiation therapy (RT) of the lung requires deformation analysis. Deformable image registration (DIR) is the fundamental method to quantify deformations for various applications: motion compensation, contour propagation, dose accumulation, etc. DIR is therefore unavoidable in lung RT. DIR algorithms have been studied for decades and are now available both within commercial and academic packages. However, they are complex and have limitations that every user must be aware of before clinical implementation. In this paper, the main applications of DIR for lung RT with their associated uncertainties and their limitations are reviewed.

First Clinical Investigation of Cone Beam Computed Tomography and Deformable Registration for Adaptive Proton Therapy for Lung Cancer.

PURPOSE: An adaptive proton therapy workflow using cone beam computed tomography (CBCT) is proposed. It consists of an online evaluation of a fast range-corrected dose distribution based on a virtual CT (vCT) scan. This can be followed by more accurate offline dose recalculation on the vCT scan, which can trigger a rescan CT (rCT) for replanning. METHODS AND MATERIALS: The workflow was tested retrospectively for 20 consecutive lung cancer patients. A diffeomorphic Morphon algorithm was used to generate the lung vCT by deforming the average planning CT onto the CBCT scan. An additional correction step was applied to account for anatomic modifications that cannot be modeled by deformation alone. A set of clinical indicators for replanning were generated according to the water equivalent thickness (WET) and dose statistics and compared with those obtained on the rCT scan. The fast dose approximation consisted of warping the initial planned dose onto the vCT scan according to the changes in WET. The potential under- and over-ranges were assessed as a variation in WET at the target's distal surface. RESULTS: The range-corrected dose from the vCT scan reproduced clinical indicators similar to those of the rCT scan. The workflow performed well under different clinical scenarios, including atelectasis, lung reinflation, and different types of tumor response. Between the vCT and rCT scans, we found a difference in the measured 95% percentile of the over-range distribution of 3.4 ± 2.7 mm. The limitations of the technique consisted of inherent uncertainties in deformable registration and the drawbacks of CBCT imaging. The correction step was adequate when gross errors occurred but could not recover subtle anatomic or density changes in tumors with complex topology. CONCLUSIONS: A proton therapy workflow based on CBCT provided clinical indicators similar to those using rCT for patients with lung cancer with considerable anatomic changes.