Artificial intelligence-based PET denoising could allow a two-fold reduction in [18F]FDG PET acquisition time in digital PET/CT.

PURPOSE: We investigated whether artificial intelligence (AI)-based denoising halves PET acquisition time in digital PET/CT. METHODS: One hundred ninety-five patients referred for [18F]FDG PET/CT were prospectively included. Body PET acquisitions were performed in list mode. Original "PET90" (90 s/bed position) was compared to reconstructed ½-duration PET (45 s/bed position) with and without AI-denoising, "PET45AI and PET45". Denoising was performed by SubtlePET™ using deep convolutional neural networks. Visual global image quality (IQ) 3-point scores and lesion detectability were evaluated. Lesion maximal and peak standardized uptake values using lean body mass (SULmax and SULpeak), metabolic volumes (MV), and liver SULmean were measured, including both standard and EARL1 (European Association of Nuclear Medicine Research Ltd) compliant SUL. Lesion-to-liver SUL ratios (LLR) and liver coefficients of variation (CVliv) were calculated. RESULTS: PET45 showed mediocre IQ (scored poor in 8% and moderate in 68%) and lesion concordance rate with PET90 (88.7%). In PET45AI, IQ scores were similar to PET90 (P = 0.80), good in 92% and moderate in 8% for both. The lesion concordance rate between PET90 and PET45AI was 836/856 (97.7%), with 7 lesions (0.8%) only detected in PET90 and 13 (1.5%) exclusively in PET45AI. Lesion EARL1 SULpeak was not significantly different between both PET (P = 0.09). Lesion standard SULpeak, standard and EARL1 SULmax, LLR and CVliv were lower in PET45AI than in PET90 (P < 0.0001), while lesion MV and liver SULmean were higher (P < 0.0001). Good to excellent intraclass correlation coefficients (ICC) between PET90 and PET45AI were observed for lesion SUL and MV (ICC ≥ 0.97) and for liver SULmean (ICC ≥ 0.87). CONCLUSION: AI allows [18F]FDG PET duration in digital PET/CT to be halved, while restoring degraded ½-duration PET image quality. Future multicentric studies, including other PET radiopharmaceuticals, are warranted.

Upfront F18-choline PET/CT versus Tc99m-sestaMIBI SPECT/CT guided surgery in primary hyperparathyroidism: the randomized phase III diagnostic trial APACH2.

BACKGROUND: The common endocrine disorder primary hyperparathyroidism (PHPT) can be cured by surgery. Preoperative localization of parathyroid adenoma (PTA) by imaging is a prerequisite for outpatient minimally invasive parathyroidectomy (MIP). Compared to inpatient bilateral cervical exploration (BCE) which is performed if imaging is inconclusive, MIP is superior in terms of cure and complication rates and less costly. The imaging procedure F18-choline (FCH) PET/CT outperforms Tc99m-sestaMIBI (MIBI) SPECT/CT for PTA localization, but it is much costlier. The aim of this study is to identify the most efficient first-line imaging modality for optimal patient care in PHPT without added cost to society. METHODS: We will conduct a multicenter open diagnostic intervention randomized phase III trial comparing two diagnostic strategies in patients with PHPT: upfront FCH PET/CT versus MIBI SPECT/CT. The primary endpoint is the proportion of patients in whom the first-line imaging method results in successful MIP and cure. Follow-up including biological tests will be performed 1 and 6 months after surgery. The main secondary endpoint is the social cost of both strategies. Other secondary endpoints are as follows: FCH PET/CT and MIBI SPECT/CT diagnostic performance, performance of surgical procedure and complication rate, FCH PET/CT inter- and intra-observer variability and optimization of FCH PET/CT procedure. Fifty-eight patients will be enrolled and randomized 1:1. DISCUSSION: FCH PET/CT is a highly efficient but expensive imaging test for preoperative PTA localization and costs three to four times more than MIBI SPECT/CT. Whether FCH PET/CT improves patient outcomes compared to the reference standard MIBI SPECT/CT is unknown. To justify its added cost, FCH PET/CT-guided parathyroid surgery should lead to improved patient management, resulting in higher cure rates and fewer BCEs and surgical complications. In the previous phase II APACH1 study, we showed that second-line FCH PET/CT led to a cure in 88% of patients with negative or inconclusive MIBI SPECT/CT. BCE could be avoided in 75% of patients and surgical complication rates were low. We therefore hypothesize that upfront FCH PET/CT would improve patient care in PHPT and that the reduction in clinical costs would offset the increase in imaging costs. TRIAL REGISTRATION: NCT04040946 , registered August 1, 2019.  Protocol version Version 2.1 dated from 2020/04/23.

Nonsurgical giant cell tumour of the tendon sheath or of the diffuse type: are MRI or 18F-FDG PET/CT able to provide an accurate prediction of long-term outcome?

PURPOSE: To investigate whether MRI (RECIST 1.1, WHO criteria and the volumetric approach) or (18)F-FDG PET/CT (PERCIST 1.0) are able to predict long-term outcome in nonsurgical patients with giant cell tumour of the tendon sheath or of the diffuse type (GCT-TS/DT). METHODS: Fifteen "nonsurgical" patients with a histological diagnosis of GCT-TS/DT were divided into two groups: symptomatic patients receiving targeted therapy and asymptomatic untreated patients. All 15 patients were evaluated by MRI of whom 10 were treated, and a subgroup of 7 patients were evaluated by PET/CT of whom 4 were treated. Early evolution was assessed according to MRI and PET/CT scans at baseline and during follow-up. Cohen's kappa coefficient was used to evaluate the degree of agreement between PERCIST 1.0, RECIST 1.1, WHO criteria, volumetric approaches and the reference standard (long-term outcome, delay 505 ± 457 days). The response rate in symptomatic patients with GCT-TS/DT receiving targeted therapy was also assessed in a larger population that included additional patients obtained from a review of the literature. RESULTS: The kappa coefficients for agreement between RECIST/WHO/volumetric criteria and outcome (15 patients) were respectively: 0.35 (p = 0.06), 0.26 (p = 0.17) and 0.26 (p = 0.17). In the PET/CT subgroup (7 patients), PERCIST was in perfect agreement with the late symptomatic evolution (kappa = 1, p < 0.05). In the treated symptomatic group including the additional patients from the literature the response rates to targeted therapies according to late symptomatic assessment, and PERCIST and RECIST criteria were: 65 % (22/34), 77 % (10/13) and 26 % (10/39). CONCLUSION: (18)F-FDG PET/CT with PERCIST is a promising approach to the prediction of the long-term outcome in GCT-TS/DT and may avoid unnecessary treatments, toxicity and costs. On MRI, WHO and volumetric approaches are not more effective than RECIST using the current thresholds.

PET imaging and quantification of small animals using a clinical SiPM-based camera.

BACKGROUND: Small-animal PET imaging is an important tool in preclinical oncology. This study evaluated the ability of a clinical SiPM-PET camera to image several rats simultaneously and to perform quantification data analysis. METHODS: Intrinsic spatial resolution was measured using 18F line sources, and image quality was assessed using a NEMA NU 4-2018 phantom. Quantification was evaluated using a fillable micro-hollow sphere phantom containing 4 spheres of different sizes (ranging from 3.95 to 7.86 mm). Recovery coefficients were computed for the maximum (Amax) and the mean (A50) pixel values measured on a 50% isocontour drawn on each sphere. Measurements were performed first with the phantom placed in the centre of the field of view and then in the off-centre position with the presence of three scattering sources to simulate the acquisition of four animals simultaneously. Quantification accuracy was finally validated using four 3D-printed phantoms mimicking rats with four subcutaneous tumours each. All experiments were performed for both 18F and 68Ga radionuclides. RESULTS: Radial spatial resolutions measured using the PSF reconstruction algorithm were 1.80 mm and 1.78 mm for centred and off-centred acquisitions, respectively. Spill-overs in air and water and uniformity computed with the NEMA phantom centred in the FOV were 0.05, 0.1 and 5.55% for 18F and 0.08, 0.12 and 2.81% for 68Ga, respectively. Recovery coefficients calculated with the 18F-filled micro-hollow sphere phantom for each sphere varied from 0.51 to 1.43 for Amax and from 0.40 to 1.01 for A50. These values decreased from 0.28 to 0.92 for Amax and from 0.22 to 0.66 for A50 for 68 Ga acquisition. The results were not significantly different when imaging phantoms in the off-centre position with 3 scattering sources. Measurements performed with the four 3D-printed phantoms showed a good correlation between theoretical and measured activity in simulated tumours, with r2 values of 0.99 and 0.97 obtained for 18F and 68Ga, respectively. CONCLUSION: We found that the clinical SiPM-based PET system was close to that obtained with a dedicated small-animal PET device. This study showed the ability of such a system to image four rats simultaneously and to perform quantification analysis for radionuclides commonly used in oncology.

Artificial intelligence-based 68Ga-DOTATOC PET denoising for optimizing 68Ge/68Ga generator use throughout its lifetime.

Introduction: The yield per elution of a 68Ge/68Ga generator decreases during its lifespan. This affects the number of patients injected per elution or the injected dose per patient, thereby negatively affecting the cost of examinations and the quality of PET images due to increased image noise. We aimed to investigate whether AI-based PET denoising can offset this decrease in image quality parameters. Methods: All patients addressed to our PET unit for a 68Ga-DOTATOC PET/CT from April 2020 to February 2021 were enrolled. Forty-four patients underwent their PET scans according to Protocol_FixedDose (150 MBq) and 32 according to Protocol_WeightDose (1.5 MBq/kg). Protocol_WeightDose examinations were processed using the Subtle PET software (Protocol_WeightDoseAI). Liver and vascular SUV mean were recorded as well as SUVmax, SUVmean and metabolic tumour volume (MTV) of the most intense tumoural lesion and its background SUVmean. Liver and vascular coefficients of variation (CV), tumour-to-background and tumour-to-liver ratios were calculated. Results: The mean injected dose of 2.1 (0.4) MBq/kg per patient was significantly higher in the Protocol_FixedDose group as compared to 1.5 (0.1) MBq/kg for the Protocol_WeightDose group. Protocol_WeightDose led to noisier images than Protocol_FixedDose with higher CVs for liver (15.57% ± 4.32 vs. 13.04% ± 3.51, p = 0.018) and blood-pool (28.67% ± 8.65 vs. 22.25% ± 10.37, p = 0.0003). Protocol_WeightDoseAI led to less noisy images than Protocol_WeightDose with lower liver CVs (11.42% ± 3.05 vs. 15.57% ± 4.32, p < 0.0001) and vascular CVs (16.62% ± 6.40 vs. 28.67% ± 8.65, p < 0.0001). Tumour-to-background and tumour-to-liver ratios were lower for protocol_WeightDoseAI: 6.78 ± 3.49 vs. 7.57 ± 4.73 (p = 0.01) and 5.96 ± 5.43 vs. 6.77 ± 6.19 (p < 0.0001), respectively. MTVs were higher after denoising whereas tumour SUVmax were lower: the mean% differences in MTV and SUVmax were + 11.14% (95% CI = 4.84-17.43) and -3.92% (95% CI = -6.25 to -1.59). Conclusion: The degradation of PET image quality due to a reduction in injected dose at the end of the 68Ge/68Ga generator lifespan can be effectively counterbalanced by using AI-based PET denoising.

Application of a new spectral deconvolution method for in vitro dosimetry in assessment of targeted alpha therapy.

BACKGROUND: The improvement of in vitro assessment of targeted alpha therapy (reproducibility, comparability of experiments…) requires precise evaluation of the dose delivered to the cells. To answer this need, a previous study proposed an innovative dosimetry method based on α-spectroscopy and a specific deconvolution process to recover the spatial distribution of 212 Pb isotopes inside in vitro culture wells. Nevertheless, although promising, the deconvolution method was time consuming and only tested for a simple isotope decay chain. PURPOSE: The purpose of this work is to propose a new matrix deconvolution method of α spectra based on a constrained-non-negative-maximum-likelihood decomposition, both faster and offering a greater modelling flexibility, allowing to study independently the kinetics of each of the daughter nuclides of complex decay chains (illustrated here with 223 Ra) in in vitro culture wells. METHODS: Firstly, the performance of the new method was fully evaluated through Monte Carlo simulations of in vitro irradiations. Different spatial distributions of 212 Pb and 223 Ra, the corresponding α spectra measured by a silicon detector and the doses delivered to the cells were simulated with Geant4. The deconvolution results were then compared to the simulation results. Secondly, measurements were carried out in culture wells without cells containing 15 kBq of 212 Pb or 9.3 kBq of 223 Ra, placed above silicon detectors recording α spectra in real time. The matrix deconvolution was then applied to determine the spatial and temporal distribution of all α-emitting daughters of studied isotopes. RESULTS: The matrix deconvolution was proved to recover the simulated distribution gradients, ensuring simulated doses within 3 % for both tested radionuclides, with errors on dose normally distributed around the reference value (consequently not exhibiting any bias), even in the case of complex decay chains as 223 Ra. The experimental study of 212 Pb and 223 Ra showed highly inhomogeneous distributions and time evolution of the concentration gradients, consistent with the previous study. Furthermore, it highlighted the complex kinetics of 223 Ra with different distributions of its α-emitting daughters (219 Rn, 215 Po, 215 At, 211 Bi, 211 Po). CONCLUSIONS: This study validates a new deconvolution method, fast and flexible, that proved to be accurate and reliable. This method allowed to reveal the complexity of isotopes kinetics in in vitro experiments, especially with complex decay chains. Experimental dosimetry, necessary to improve reliability of in vitro studies in targeted alpha therapy, is demonstrated to be feasible with the proposed method.

Deep Learning Denoising Improves and Homogenizes Patient [18F]FDG PET Image Quality in Digital PET/CT.

Given the constant pressure to increase patient throughput while respecting radiation protection, global body PET image quality (IQ) is not satisfactory in all patients. We first studied the association between IQ and other variables, in particular body habitus, on a digital PET/CT. Second, to improve and homogenize IQ, we evaluated a deep learning PET denoising solution (Subtle PETTM) using convolutional neural networks. We analysed retrospectively in 113 patients visual IQ (by a 5-point Likert score in two readers) and semi-quantitative IQ (by the coefficient of variation in the liver, CVliv) as well as lesion detection and quantification in native and denoised PET. In native PET, visual and semi-quantitative IQ were lower in patients with larger body habitus (p < 0.0001 for both) and in men vs. women (p ≤ 0.03 for CVliv). After PET denoising, visual IQ scores increased and became more homogeneous between patients (4.8 ± 0.3 in denoised vs. 3.6 ± 0.6 in native PET; p < 0.0001). CVliv were lower in denoised PET than in native PET, 6.9 ± 0.9% vs. 12.2 ± 1.6%; p < 0.0001. The slope calculated by linear regression of CVliv according to weight was significantly lower in denoised than in native PET (p = 0.0002), demonstrating more uniform CVliv. Lesion concordance rate between both PET series was 369/371 (99.5%), with two lesions exclusively detected in native PET. SUVmax and SUVpeak of up to the five most intense native PET lesions per patient were lower in denoised PET (p < 0.001), with an average relative bias of -7.7% and -2.8%, respectively. DL-based PET denoising by Subtle PETTM allowed [18F]FDG PET global image quality to be improved and homogenized, while maintaining satisfactory lesion detection and quantification. DL-based denoising may render body habitus adaptive PET protocols unnecessary, and pave the way for the improvement and homogenization of PET modalities.

Deep Hybrid Learning Prediction of Patient-Specific Quality Assurance in Radiotherapy: Implementation in Clinical Routine.

BACKGROUND: Arc therapy allows for better dose deposition conformation, but the radiotherapy plans (RT plans) are more complex, requiring patient-specific pre-treatment quality assurance (QA). In turn, pre-treatment QA adds to the workload. The objective of this study was to develop a predictive model of Delta4-QA results based on RT-plan complexity indices to reduce QA workload. METHODS: Six complexity indices were extracted from 1632 RT VMAT plans. A machine learning (ML) model was developed for classification purpose (two classes: compliance with the QA plan or not). For more complex locations (breast, pelvis and head and neck), innovative deep hybrid learning (DHL) was trained to achieve better performance. RESULTS: For not complex RT plans (with brain and thorax tumor locations), the ML model achieved 100% specificity and 98.9% sensitivity. However, for more complex RT plans, specificity falls to 87%. For these complex RT plans, an innovative QA classification method using DHL was developed and achieved a sensitivity of 100% and a specificity of 97.72%. CONCLUSIONS: The ML and DHL models predicted QA results with a high degree of accuracy. Our predictive QA online platform is offering substantial time savings in terms of accelerator occupancy and working time.

Feasibility of Imaging Small Animals on a 360° Whole-Body Cadmium Zinc Telluride SPECT Camera: a Phantom Study.

PURPOSE: Single-photon emission computed tomography has found an important place in preclinical cancer research. Nevertheless, the cameras dedicated to small animals are not widely available. The present study aimed to assess the feasibility of imaging small animals by a newly released 360° cadmium zinc telluride camera (VERITON, Spectrum Dynamics, Israel) dedicated to human patients. PROCEDURES: A cylindrical phantom containing hot spheres was used to evaluate the intrinsic performance of the camera first without the presence of background activity and then with two contrasts between background and hot spheres (1/4 and 1/10). Acquisitions were repeated with different scan durations (10 and 20 min), two tested radioisotopes (Tc-99 m and I-123), and a set of reconstruction parameters (10 iterations [i] 8 subsets [s], 10i16s, 10i32s). A 3D-printed phantom mimicking a rat with four subcutaneous tumours was then used to test the camera under preclinical conditions. RESULTS: The results obtained from the micro-hollow sphere phantom showed that it was possible to visualize spheres with an inner diameter of 3.95 mm without background activity. Moreover, spheres with diameters of 4.95 mm can be seen in the condition of high contrast between background and spheres (1/10) and 7.86 mm with lower contrast (1/4). The rat-sized phantom acquisitions showed that 10- and 8-mm subcutaneous tumours were visible with a good contrast obtained for the two radioisotopes tested in this study. Both Tc-99 m and I-123 measurements demonstrated that a 10-min acquisition reconstructed with an ordered subset expectation maximization algorithm applying 10i32s was optimal to obtain sufficient image quality in terms of noise, resolution, and contrast. CONCLUSION: Phantom results showed the ability of the system to detect sub-centimetre lesions for various radioisotopes. It seemed feasible to image small animals using a 360° cadmium zinc telluride gamma camera for preclinical cancer research purposes.

The Impact of Artificial Intelligence CNN Based Denoising on FDG PET Radiomics.

BACKGROUND: With a constantly increasing number of diagnostic images performed each year, Artificial Intelligence (AI) denoising methods offer an opportunity to respond to the growing demand. However, it may affect information in the image in an unknown manner. This study quantifies the effect of AI-based denoising on FDG PET textural information in comparison to a convolution with a standard gaussian postfilter (EARL1). METHODS: The study was carried out on 113 patients who underwent a digital FDG PET/CT (VEREOS, Philips Healthcare). 101 FDG avid lesions were segmented semi-automatically by a nuclear medicine physician. VOIs in the liver and lung as reference organs were contoured. PET textural features were extracted with pyradiomics. Texture features from AI denoised and EARL1 versus original PET images were compared with a Concordance Correlation Coefficient (CCC). Features with CCC values ≥ 0.85 threshold were considered concordant. Scatter plots of variable pairs with R2 coefficients of the more relevant features were computed. A Wilcoxon signed rank test to compare the absolute values between AI denoised and original images was performed. RESULTS: The ratio of concordant features was 90/104 (86.5%) in AI denoised versus 46/104 (44.2%) with EARL1 denoising. In the reference organs, the concordant ratio for AI and EARL1 denoised images was low, respectively 12/104 (11.5%) and 7/104 (6.7%) in the liver, 26/104 (25%) and 24/104 (23.1%) in the lung. SUVpeak was stable after the application of both algorithms in comparison to SUVmax. Scatter plots of variable pairs showed that AI filtering affected more lower versus high intensity regions unlike EARL1 gaussian post filters, affecting both in a similar way. In lesions, the majority of texture features 79/100 (79%) were significantly (p<0.05) different between AI denoised and original PET images. CONCLUSIONS: Applying an AI-based denoising on FDG PET images maintains most of the lesion's texture information in contrast to EARL1-compatible Gaussian filter. Predictive features of a trained model could be thus the same, however with an adapted threshold. Artificial intelligence based denoising in PET is a very promising approach as it adapts the denoising in function of the tissue type, preserving information where it should.

The Impact of Resampling and Denoising Deep Learning Algorithms on Radiomics in Brain Metastases MRI.

BACKGROUND: Magnetic resonance imaging (MRI) is predominant in the therapeutic management of cancer patients, unfortunately, patients have to wait a long time to get an appointment for examination. Therefore, new MRI devices include deep-learning (DL) solutions to save acquisition time. However, the impact of these algorithms on intensity and texture parameters has been poorly studied. The aim of this study was to evaluate the impact of resampling and denoising DL models on radiomics. METHODS: Resampling and denoising DL model was developed on 14,243 T1 brain images from 1.5T-MRI. Radiomics were extracted from 40 brain metastases from 11 patients (2049 images). A total of 104 texture features of DL images were compared to original images with paired t-test, Pearson correlation and concordance-correlation-coefficient (CCC). RESULTS: When two times shorter image acquisition shows strong disparities with the originals concerning the radiomics, with significant differences and loss of correlation of 79.81% and 48.08%, respectively. Interestingly, DL models restore textures with 46.15% of unstable parameters and 25.96% of low CCC and without difference for the first-order intensity parameters. CONCLUSIONS: Resampling and denoising DL models reconstruct low resolution and noised MRI images acquired quickly into high quality images. While fast MRI acquisition loses most of the radiomic features, DL models restore these parameters.

Radioimmunotherapy for Brain Metastases: The Potential for Inflammation as a Target of Choice.

Brain metastases (BM) are frequently detected during the follow-up of patients with malignant tumors, particularly in those with advanced disease. Despite a major progress in systemic anti-cancer treatments, the average overall survival of these patients remains limited (6 months from diagnosis). Also, cognitive decline is regularly reported especially in patients treated with whole brain external beam radiotherapy (WBRT), due to the absorbed radiation dose in healthy brain tissue. New targeted therapies, for an earlier and/or more specific treatment of the tumor and its microenvironment, are needed. Radioimmunotherapy (RIT), a combination of a radionuclide to a specific antibody, appears to be a promising tool. Inflammation, which is involved in multiple steps, including the early phase, of BM development is attractive as a relevant target for RIT. This review will focus on the (1) early biomarkers of inflammation in BM pertinent for RIT, (2) state of the art studies on RIT for BM, and (3) the importance of dosimetry to RIT in BM. These two last points will be addressed in comparison to the conventional EBRT treatment, particularly with respect to the balance between tumor control and healthy tissue complications. Finally, because new diagnostic imaging techniques show a potential for the detection of BM at an early stage of the disease, we focus particularly on this therapeutic window.

Multiple quantum oscillations in the de Haas-van Alphen spectra of the underdoped high-temperature superconductor YBa2Cu3O6.5.

By improving the experimental conditions and extensive data accumulation, we have achieved very high precision in the measurements of the de Haas-van Alphen effect in the underdoped high-temperature superconductor YBa2Cu3O6.5. We find that the main oscillation, so far believed to be single frequency, is composed of three closely spaced frequencies. We attribute this to bilayer splitting and warping of a single quasi-2D Fermi surface, indicating that c axis coherence is restored at low temperature in underdoped cuprates. Our results do not support the existence of a larger frequency of the order of 1650 T reported recently in the same compound [S. E. Sebastian, Nature (London) 454, 200 (2008)].

Gated 18F-FDG PET/CT of the Lung Using a Respiratory Spirometric Gating Device: A Feasibility Study.

Spirometric gating devices (SGDs) can measure the respiratory signal with high temporal resolution and accuracy. The primary objective of this study was to assess the feasibility and tolerance of a gated lung PET/CT acquisition using an SGD. The secondary objective was to compare the technical quality, accuracy, and interoperability of the SGD with that of a standard respiratory gating device, Real-Time Position Management (RPM), based on measurement of vertical thoracoabdominal displacement. Methods: A prospective phase I monocentric clinical study was performed on patients undergoing 18F-FDG PET/CT for assessment of a solitary lung nodule, staging of lung malignancy, or planning of radiotherapy. After whole-body PET/CT, a centered gated acquisition of both PET and CT was simultaneously obtained with the SGD and RPM during normal breathing. Results: Of the 46 patients who were included, 6 were prematurely excluded (1 because of hyperglycemia and 5 because of distant metastases revealed by whole-body PET/CT, leading to an unjustified extra gated acquisition). No serious adverse events were observed. Of the 40 remaining patients, the gated acquisition was prematurely stopped in 1 patient because of mask discomfort (2.5%; confidence interval [CI], 0.1%-13.2%). This event was considered patient tolerance failure. The SGD generated accurately gated PET/CT images, with more than 95% of the breathing cycle detected and high temporal resolution, in 34 of the 39 patients (87.2%; 95% CI, 60.0%-100.0%) and failed to generate a biologic tumor volume in 1 of 21 patients with increased 18F-FDG uptake (4.8%; 95% CI, 0.1%-26.5%). The quality and accuracy of respiratory signal detection and synchronization were significantly better than those obtained with RPM (P < 0.05). Conclusion: This trial supports the use of an SGD for gated lung PET/CT because of its high patient tolerance and accuracy. Although this technique seems to technically outperform RPM for gated PET/CT, further assessment of its superiority and the clinical benefit is warranted. We believe that this technique could be used as a gold standard to develop innovative approaches to eliminate respiration-induced blurring artifacts.

The long- and short-term variability of breathing induced tumor motion in lung and liver over the course of a radiotherapy treatment.

PURPOSE: To evaluate the short and long-term variability of breathing induced tumor motion. MATERIALS AND METHODS: 3D tumor motion of 19 lung and 18 liver lesions captured over the course of an SBRT treatment were evaluated and compared to the motion on 4D-CT. An implanted fiducial could be used for unambiguous motion information. Fast orthogonal fluoroscopy (FF) sequences, included in the treatment workflow, were used to evaluate motion during treatment. Several motion parameters were compared between different FF sequences from the same fraction to evaluate the intrafraction variability. To assess interfraction variability, amplitude and hysteresis were compared between fractions and with the 3D tumor motion registered by 4D-CT. Population based margins, necessary on top of the ITV to capture all motion variability, were calculated based on the motion captured during treatment. RESULTS: Baseline drift in the cranio-caudal (CC) or anterior-poster (AP) direction is significant (ie. >5 mm) for a large group of patients, in contrary to intrafraction amplitude and hysteresis variability. However, a correlation between intrafraction amplitude variability and mean motion amplitude was found (Pearson's correlation coefficient, r = 0.72, p < 10-4). Interfraction variability in amplitude is significant for 46% of all lesions. As such, 4D-CT accurately captures the motion during treatment for some fractions but not for all. Accounting for motion variability during treatment increases the PTV margins in all directions, most significantly in CC from 5 mm to 13.7 mm for lung and 8.0 mm for liver. CONCLUSION: Both short-term and day-to-day tumor motion variability can be significant, especially for lesions moving with amplitudes above 7 mm. Abandoning passive motion management strategies in favor of more active ones is advised.

Population Pharmacokinetics of Tracers: A New Tool for Medical Imaging?

Positron emission tomography-computed tomography is a medical imaging method measuring the activity of a radiotracer chosen to accumulate in cancer cells. A recent trend of medical imaging analysis is to account for the radiotracer's pharmacokinetic properties at a voxel (three-dimensional-pixel) level to separate the different tissues. These analyses are closely linked to population pharmacokinetic-pharmacodynamic modelling. Kineticists possess the cultural background to improve medical imaging analysis. This article stresses the common points with population pharmacokinetics and highlights the methodological locks that need to be lifted.

Limits of radiomic-based entropy as a surrogate of tumor heterogeneity: ROI-area, acquisition protocol and tissue site exert substantial influence.

Entropy is a promising quantitative imaging biomarker for characterizing cancer imaging phenotype. Entropy has been associated with tumor gene expression, tumor metabolism, tumor stage, patient prognosis, and treatment response. Our hypothesis states that tumor-specific biomarkers such as entropy should be correlated between synchronous metastases. Therefore, a significant proportion of the variance of entropy should be attributed to the malignant process. We analyzed 112 patients with matched/paired synchronous metastases (SM#1 and SM#2) prospectively enrolled in the MOSCATO-01 clinical trial. Imaging features were extracted from Regions Of Interest (ROI) delineated on CT-scan using TexRAD software. We showed that synchronous metastasis entropy was correlated across 5 Spatial Scale Filters: Spearman's Rho ranged between 0.41 and 0.59 (P = 0.0001, Bonferroni correction). Multivariate linear analysis revealed that entropy in SM#1 is significantly associated with (i) primary tumor type; (ii) entropy in SM#2 (same malignant process); (iii) ROI area size; (iv) metastasis site; and (v) entropy in the psoas muscle (reference tissue). Entropy was a logarithmic function of ROI area in normal control tissues (aorta, psoas) and in mathematical models (P < 0.01). We concluded that entropy is a tumor-specific metric only if confounding factors are corrected.

Population Pharmacokinetic Approach Applied to Positron Emission Tomography: Computed Tomography for Tumor Tissue Identification in Patients with Glioma.

BACKGROUND AND AIMS: 18F-fluoro-ethyl-tyrosine (FET) is a radiopharmaceutical used in positron emission tomography (PET)-computed tomography in patients with glioma. We propose an original approach combining a radiotracer-pharmacokinetic exploration performed at the voxel level (three-dimensional pixel) and voxel classification to identify tumor tissue. Our methodology was validated using the standard FET-PET approach and magnetic resonance imaging (MRI) data acquired according to the current clinical practices. METHODS: FET-PET and MRI data were retrospectively analyzed in ten patients presenting with progressive high-grade glioma. For FET-PET exploration, radioactivity acquisition started 15 min after radiotracer injection, and was measured each 5 min during 40 min. The tissue segmentation relies on population pharmacokinetic modeling with dependent individuals (voxels). This model can be approximated by a linear mixed-effects model. The tumor volumes estimated by our approach were compared with those determined with the current clinical techniques, FET-PET standard approach (i.e., a cumulated value of FET signal is computed during a time interval) and MRI sequences (T1 and T2/fluid-attenuated inversion recovery [FLAIR]), used as references. The T1 sequence is useful to identify highly vascular tumor and necrotic tissues, while the T2/FLAIR sequence is useful to isolate infiltration and edema tissue located around the tumor. RESULTS: With our kinetic approach, the volumes of tumor tissue were larger than the tissues identified by the standard FET-PET and MRI T1, while they were smaller than those determined with MRI T2/FLAIR. CONCLUSION: Our results revealed the presence of suspected tumor voxels not identified by the standard PET approach.

Treating patients with Dynamic Wave Arc: First clinical experience.

BACKGROUND AND PURPOSE: Dynamic Wave Arc (DWA) is a system-specific noncoplanar arc technique that combines synchronized gantry-ring rotation with D-MLC optimization. This paper presents the clinical workflow, quality assurance program, and reports the geometric and dosimetric results of the first patient cohort treated with DWA. METHODS AND MATERIALS: The RayStation TPS was clinically integrated on the Vero SBRT platform for DWA treatments. The first 15 patients treated with DWA represent a broad range of treatment sites: breast boost, prostate, lung SBRT and bone metastases, which allowed us to explore the potentials and assess the limitations of the current DWA site-specific template solution. For the DWA verification a variety of QA equipment was used, from 3D diode array to an anthropomorphic end-to-end phantom. The geometric accuracy of each arc was verified with an independent orthogonal fluoroscopy method. RESULTS: The average beam-on delivery time was 3min, ranging from 1.22min to 8.82min. All patient QAs passed our institutional clinical criteria of gamma index. For both EBT3 film and Delta4 measurements, DWA planned versus delivered dose distributions presented an average agreement above 97%. An overall mean gantry-ring geometric deviation of -0.03°±0.46° and 0.18°±0.26° was obtained, respectively. CONCLUSION: For the first time, DWA has been translated into the clinic and used to treat various treatment sides. DWA has been successfully added to the noncoplanar rotational IMRT techniques arsenal, allowing additional flexibility in dose shaping while preserving dosimetrically robust delivery.

Dynamic Scintigraphy With SPECT-CT of Postoperative Salivary Leak.

This 65 year-old woman, 1 month postoperative after maxillary sinus carcinoma (pT4N0cM0) excision and reconstruction, presented with significant left facial clear fluid wound leakage. A salivary or cerebrospinal leakage was suspected. Fluid analysis, CT, and MRI were noncontributory. Dynamic salivary scintigraphy with SPECT-CT allowed for the detection and localization of the leakage from the left parotid gland. Radioactive dose rate of the wound bandage was 50 µSv/h compared with 0.05 µSv/h for background and confirmed the diagnosis. Left total parotidectomy resulted in resolution.