Pelvic PET/MR attenuation correction in the image space using deep learning

IntroductionThe five-class Dixon-based PET/MR attenuation correction (AC) model, which adds bone information to the four-class model by registering major bones from a bone atlas, has been shown to be error-prone. In this study, we introduce a novel method of accounting for bone in pelvic PET/MR AC by directly predicting the errors in the PET image space caused by the lack of bone in four-class Dixon-based attenuation correction.MethodsA convolutional neural network was trained to predict the four-class AC error map relative to CT-based attenuation correction. Dixon MR images and the four-class attenuation correction µ-map were used as input to the models. CT and PET/MR examinations for 22 patients ([18F]FDG) were used for training and validation, and 17 patients were used for testing (6 [18F]PSMA-1007 and 11 [68Ga]Ga-PSMA-11). A quantitative analysis of PSMA uptake using voxel- and lesion-based error metrics was used to assess performance.ResultsIn the voxel-based analysis, the proposed model reduced the median root mean squared percentage error from 12.1% and 8.6% for the four- and five-class Dixon-based AC methods, respectively, to 6.2%. The median absolute percentage error in the maximum standardized uptake value (SUVmax) in bone lesions improved from 20.0% and 7.0% for four- and five-class Dixon-based AC methods to 3.8%.ConclusionThe proposed method reduces the voxel-based error and SUVmax errors in bone lesions when compared to the four- and five-class Dixon-based AC models

Performance of magnetic resonance imaging-based prostate cancer risk calculators and decision strategies in two large European medical centres

Objectives: To compare the performance of currently available biopsy decision support tools incorporating magnetic resonance imaging (MRI) findings in predicting clinically significant prostate cancer (csPCa). Patients and Methods: We retrospectively included men who underwent prostate MRI and subsequent targeted and/or systematic prostate biopsies in two large European centres. Available decision support tools were identified by a PubMed search. Performance was assessed by calibration, discrimination, decision curve analysis (DCA) and numbers of biopsies avoided vs csPCa cases missed, before and after recalibration, at risk thresholds of 5%–20%. Results: A total of 940 men were included, 507 (54%) had csPCa. The median (interquartile range) age, prostate-specific antigen (PSA) level, and PSA density (PSAD) were 68 (63–72) years, 9 (7–15) ng/mL, and 0.20 (0.13–0.32) ng/mL2, respectively. In all, 18 multivariable risk calculators (MRI-RCs) and dichotomous biopsy decision strategies based on MRI findings and PSAD thresholds were assessed. The Van Leeuwen model and the Rotterdam Prostate Cancer Risk Calculator (RPCRC) had the best discriminative ability (area under the receiver operating characteristic curve 0.86) of the MRI-RCs that could be assessed in the whole cohort. DCA showed the highest clinical utility for the Van Leeuwen model, followed by the RPCRC. At the 10% threshold the Van Leeuwen model would avoid 22% of biopsies, missing 1.8% of csPCa, whilst the RPCRC would avoid 20% of biopsies, missing 2.6% of csPCas. These multivariable models outperformed all dichotomous decision strategies based only on MRI-findings and PSAD. Conclusions: Even in this high-risk cohort, biopsy decision support tools would avoid many prostate biopsies, whilst missing very few csPCa cases. The Van Leeuwen model had the highest clinical utility, followed by the RPCRC. These multivariable MRI-RCs outperformed and should be favoured over decision strategies based only on MRI and PSAD.</p

Decidual and placental NOD1 is associated with inflammation in normal and preeclamptic pregnancies

Introduction: Inflammation is a normal physiological process that increases to harmful levels in preeclampsia. It affects the interaction between maternal immune cells and fetal trophoblasts at both sites of the maternal-fetal interface; decidua and placenta. The pattern recognition receptor nucleotide-binding oligomerization domain-containing protein (NOD)1 is expressed at both sites. This study aimed to characterize the cellular expression and functionality of NOD1 at the maternal-fetal interface of normal and preeclamptic pregnancies. Methods: Women with normal or preeclamptic pregnancies delivered by caesarean section were included. Decidual (n = 90) and placental (n = 91) samples were analyzed for NOD1 expression by immunohistochemistry and an automated image-based quantification method. Decidual and placental explants were incubated with or without the NOD1-agonist iE-DAP and cytokine responses measured by ELISA. Results: NOD1 was markedly expressed by maternal cells in the decidua and by fetal trophoblasts in both decidua and placenta, with trophoblasts showing the highest NOD1 expression. Preeclampsia with normal fetal growth was associated with a trophoblast-dependent increase in decidual NOD1 expression density. Compared to normal pregnancies, preeclampsia demonstrated stronger correlation between decidual and placental NOD1 expression levels. Increased production of interleukin (IL)-6 or IL-8 after in vitro explant stimulation confirmed NOD1 functionality. Discussion: These findings suggest that NOD1 contributes to inflammation at the maternal-fetal interface in normal pregnancies and preeclampsia and indicate a role in direct maternal-fetal communication. The strong expression of NOD1 by all trophoblast types highlights the importance of combined assessment of decidua and placenta for overall understanding of pathophysiological processes at the maternal-fetal interface.publishedVersio

Divergent Regulation of Decidual Oxidative-Stress Response by NRF2 and KEAP1 in Preeclampsia with and without Fetal Growth Restriction

Utero-placental development in pregnancy depends on direct maternal–fetal interaction in the uterine wall decidua. Abnormal uterine vascular remodeling preceding placental oxidative stress and placental dysfunction are associated with preeclampsia and fetal growth restriction (FGR). Oxidative stress is counteracted by antioxidants and oxidative repair mechanisms regulated by the transcription factor nuclear factor erythroid 2-related factor 2 (NRF2). We aimed to determine the decidual regulation of the oxidative-stress response by NRF2 and its negative regulator Kelch-like ECH-associated protein 1 (KEAP1) in normal pregnancies and preeclamptic pregnancies with and without FGR. Decidual tissue from 145 pregnancies at delivery was assessed for oxidative stress, non-enzymatic antioxidant capacity, cellular NRF2- and KEAP1-protein expression, and NRF2-regulated transcriptional activation. Preeclampsia combined with FGR was associated with an increased oxidative-stress level and NRF2-regulated gene expression in the decidua, while decidual NRF2- and KEAP1-protein expression was unaffected. Although preeclampsia with normal fetal growth also showed increased decidual oxidative stress, NRF2-regulated gene expression was reduced, and KEAP1-protein expression was increased in areas of high trophoblast density. The trophoblast-dependent KEAP1-protein expression in preeclampsia with normal fetal growth indicates control of decidual oxidative stress by maternal–fetal interaction and underscores the importance of discriminating between preeclampsia with and without FGR.publishedVersio

Holmium-166 radioembolization for the treatment of patients with liver metastases: design of the phase I HEPAR trial

<p>Abstract</p> <p>Background</p> <p>Intra-arterial radioembolization with yttrium-90 microspheres ( ⁹⁰Y-RE) is an increasingly used therapy for patients with unresectable liver malignancies. Over the last decade, radioactive holmium-166 poly(L-lactic acid) microspheres ( ¹⁶⁶Ho-PLLA-MS) have been developed as a possible alternative to ⁹⁰Y-RE. Next to high-energy beta-radiation, ¹⁶⁶Ho also emits gamma-radiation, which allows for imaging by gamma scintigraphy. In addition, Ho is a highly paramagnetic element and can therefore be visualized by MRI. These imaging modalities are useful for assessment of the biodistribution, and allow dosimetry through quantitative analysis of the scintigraphic and MR images. Previous studies have demonstrated the safety of ¹⁶⁶Ho-PLLA-MS radioembolization ( ¹⁶⁶Ho-RE) in animals. The aim of this phase I trial is to assess the safety and toxicity profile of ¹⁶⁶Ho-RE in patients with liver metastases.</p> <p>Methods</p> <p>The HEPAR study (Holmium Embolization Particles for Arterial Radiotherapy) is a non-randomized, open label, safety study. We aim to include 15 to 24 patients with liver metastases of any origin, who have chemotherapy-refractory disease and who are not amenable to surgical resection. Prior to treatment, in addition to the standard technetium-99m labelled macroaggregated albumin ( ^99mTc-MAA) dose, a low radioactive safety dose of 60-mg ¹⁶⁶Ho-PLLA-MS will be administered. Patients are treated in 4 cohorts of 3-6 patients, according to a standard dose escalation protocol (20 Gy, 40 Gy, 60 Gy, and 80 Gy, respectively). The primary objective will be to establish the maximum tolerated radiation dose of ¹⁶⁶Ho-PLLA-MS. Secondary objectives are to assess tumour response, biodistribution, performance status, quality of life, and to compare the ¹⁶⁶Ho-PLLA-MS safety dose and the ^99mTc-MAA dose distributions with respect to the ability to accurately predict microsphere distribution.</p> <p>Discussion</p> <p>This will be the first clinical study on ¹⁶⁶Ho-RE. Based on preclinical studies, it is expected that ¹⁶⁶Ho-RE has a safety and toxicity profile comparable to that of ⁹⁰Y-RE. The biochemical and radionuclide characteristics of ¹⁶⁶Ho-PLLA-MS that enable accurate dosimetry calculations and biodistribution assessment may however improve the overall safety of the procedure.</p> <p>Trial registration</p> <p>ClinicalTrials.gov NCT01031784</p

Quantitative Evaluation of Scintillation Camera Imaging Characteristics of Isotopes Used in Liver Radioembolization

Scintillation camera imaging is used for treatment planning and post-treatment dosimetry in liver radioembolization (RE). In yttrium-90 (90Y) RE, scintigraphic images of technetium-99m (99mTc) are used for treatment planning, while 90Y Bremsstrahlung images are used for post-treatment dosimetry. In holmium-166 (166Ho) RE, scintigraphic images of 166Ho can be used for both treatment planning and post-treatment dosimetry. The aim of this study is to quantitatively evaluate and compare the imaging characteristics of these three isotopes, in order that imaging protocols can be optimized and RE studies with varying isotopes can be compared.Phantom experiments were performed in line with NEMA guidelines to assess the spatial resolution, sensitivity, count rate linearity, and contrast recovery of 99mTc, 90Y and 166Ho. In addition, Monte Carlo simulations were performed to obtain detailed information about the history of detected photons. The results showed that the use of a broad energy window and the high-energy collimator gave optimal combination of sensitivity, spatial resolution, and primary photon fraction for 90Y Bremsstrahlung imaging, although differences with the medium-energy collimator were small. For 166Ho, the high-energy collimator also slightly outperformed the medium-energy collimator. In comparison with 99mTc, the image quality of both 90Y and 166Ho is degraded by a lower spatial resolution, a lower sensitivity, and larger scatter and collimator penetration fractions.The quantitative evaluation of the scintillation camera characteristics presented in this study helps to optimize acquisition parameters and supports future analysis of clinical comparisons between RE studies

Label-set impact on deep learning-based prostate segmentation on MRI

Abstract Background Prostate segmentation is an essential step in computer-aided detection and diagnosis systems for prostate cancer. Deep learning (DL)-based methods provide good performance for prostate gland and zones segmentation, but little is known about the impact of manual segmentation (that is, label) selection on their performance. In this work, we investigated these effects by obtaining two different expert label-sets for the PROSTATEx I challenge training dataset (n = 198) and using them, in addition to an in-house dataset (n = 233), to assess the effect on segmentation performance. The automatic segmentation method we used was nnU-Net. Results The selection of training/testing label-set had a significant (p < 0.001) impact on model performance. Furthermore, it was found that model performance was significantly (p < 0.001) higher when the model was trained and tested with the same label-set. Moreover, the results showed that agreement between automatic segmentations was significantly (p < 0.0001) higher than agreement between manual segmentations and that the models were able to outperform the human label-sets used to train them. Conclusions We investigated the impact of label-set selection on the performance of a DL-based prostate segmentation model. We found that the use of different sets of manual prostate gland and zone segmentations has a measurable impact on model performance. Nevertheless, DL-based segmentation appeared to have a greater inter-reader agreement than manual segmentation. More thought should be given to the label-set, with a focus on multicenter manual segmentation and agreement on common procedures. Critical relevance statement Label-set selection significantly impacts the performance of a deep learning-based prostate segmentation model. Models using different label-set showed higher agreement than manual segmentations. Key points • Label-set selection has a significant impact on the performance of automatic segmentation models. • Deep learning-based models demonstrated true learning rather than simply mimicking the label-set. • Automatic segmentation appears to have a greater inter-reader agreement than manual segmentation. Graphical Abstrac

Artificial intelligence for prostate MRI: open datasets, available applications, and grand challenges

Artificial intelligence (AI) for prostate magnetic resonance imaging (MRI) is starting to play a clinical role for prostate cancer (PCa) patients. AI-assisted reading is feasible, allowing workflow reduction. A total of 3,369 multi-vendor prostate MRI cases are available in open datasets, acquired from 2003 to 2021 in Europe or USA at 3 T (n = 3,018; 89.6%) or 1.5 T (n = 296; 8.8%), 346 cases scanned with endorectal coil (10.3%), 3,023 (89.7%) with phased-array surface coils; 412 collected for anatomical segmentation tasks, 3,096 for PCa detection/classification; for 2,240 cases lesions delineation is available and 56 cases have matching histopathologic images; for 2,620 cases the PSA level is provided; the total size of all open datasets amounts to approximately 253 GB. Of note, quality of annotations provided per dataset highly differ and attention must be paid when using these datasets (e.g., data overlap). Seven grand challenges and commercial applications from eleven vendors are here considered. Few small studies provided prospective validation. More work is needed, in particular validation on large-scale multi-institutional, well-curated public datasets to test general applicability. Moreover, AI needs to be explored for clinical stages other than detection/characterization (e.g., follow-up, prognosis, interventions, and focal treatment)

Multimodality calibration for simultaneous fluoroscopic and nuclear imaging

BACKGROUND: Simultaneous real-time fluoroscopic and nuclear imaging could benefit image-guided (oncological) procedures. To this end, a hybrid modality is currently being developed by our group, by combining a c-arm with a gamma camera and a four-pinhole collimator. Accurate determination of the system parameters that describe the position of the x-ray tube, x-ray detector, gamma camera, and collimators is crucial to optimize image quality. The purpose of this study was to develop a calibration method that estimates the system parameters used for reconstruction. A multimodality phantom consisting of five point sources was created. First, nuclear and fluoroscopic images of the phantom were acquired at several distances from the image intensifier. The system parameters were acquired using physical measurement, and multimodality images of the phantom were reconstructed. The resolution and co-registration error of the point sources were determined as a measure of image quality. Next, the system parameters were estimated using a calibration method, which adjusted the parameters in the reconstruction algorithm, until the resolution and co-registration were optimized. For evaluation, multimodality images of a second set of phantom acquisitions were reconstructed using calibrated parameter sets. Subsequently, the resolution and co-registration error of the point sources were determined as a measure of image quality. This procedure was performed five times for different noise simulations. In addition, simultaneously acquired fluoroscopic and nuclear images of two moving syringes were obtained with parameter sets from before and after calibration. RESULTS: The mean FWHM was significantly lower after calibration than before calibration for 21 out of 25 point sources. The mean co-registration error was significantly lower after calibration than before calibration for all point sources. The simultaneously acquired fluoroscopic and nuclear images showed improved co-registration after calibration as compared with before calibration. CONCLUSIONS: A calibration method was presented that improves the resolution and co-registration of simultaneously acquired hybrid fluoroscopic and nuclear images by estimating the geometric parameter set as compared with a parameter set acquired by direct physical measurement

Toward Simultaneous Real-Time Fluoroscopic and Nuclear Imaging in the Intervention Room

Purpose To investigate the technical feasibility of hybrid simultaneous fluoroscopic and nuclear imaging. Materials and Methods An x-ray tube, an x-ray detector, and a gamma camera were positioned in one line, enabling imaging of the same field of view. Since a straightforward combination of these elements would block the lines of view, a gamma camera setup was developed to be able to view around the x-ray tube. A prototype was built by using a mobile C-arm and a gamma camera with a four-pinhole collimator. By using the prototype, test images were acquired and sensitivity, resolution, and coregistration error were analyzed. Results Nuclear images (two frames per second) were acquired simultaneously with fluoroscopic images. Depending on the distance from point source to detector, the system resolution was 1.5-1.9-cm full width at half maximum, the sensitivity was (0.6-1.5) × 10(-5) counts per decay, and the coregistration error was -0.13 to 0.15 cm. With good spatial and temporal alignment of both modalities throughout the field of view, fluoroscopic images can be shown in grayscale and corresponding nuclear images in color overlay. Conclusion Measurements obtained with the hybrid imaging prototype device that combines simultaneous fluoroscopic and nuclear imaging of the same field of view have demonstrated the feasibility of real-time simultaneous hybrid imaging in the intervention room. (©) RSNA, 2015 Online supplemental material is available for this article