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OBJECTIVE Some neonates born prematurely with intraventricular hemorrhage develop posthemorrhagic hydrocephalus and require lifelong treatment to divert the flow of CSF. Early prediction of the eventual need for a ventriculoperitoneal shunt (VPS) is difficult, and early discussions with families are based on statistics and the grade of hemorrhage. The authors hypothesize that change in ventricular volume during ventricular taps that is measured with repeated 3D ultrasound (3D US) imaging of the lateral ventricles could be used to assess the risk of the future requirement of a VPS. METHODS A total of 92 neonates with intraventricular hemorrhage who were treated in the NICU were recruited between April 2012 and November 2019. Only patients who required ventricular taps (VTs) were included in this study, resulting in the analysis of 19 patients with a total of 61 VTs. Among them, 14 patients were treated with a VPS, and in 5 patients the hydrocephalus resolved spontaneously. Parameters studied were total ventricular volume measured with 3D US, ventricular volume change after VT, the ratio between volume reduction and tap amount, the difference between tap amount and volume reduction after tap, the average tap amount, the average number of days between taps, pre-tap head circumference, and reduction in head circumference after tap. RESULTS Statistically significant differences were found in ventricular volume reduction after tap (p = 0.007), the ratio between volume reduction and tap amount (p = 0.03), the difference between tap amount and volume reduction after tap (p = 0.05), and the interval of days between taps (p = 0.0115). CONCLUSIONS Measuring with 3D US before and after VT can be a useful tool for quantifying ventricular volume. The findings in this study showed that neonates who experience a large reduction of ventricular volume after VT are more likely to be treated with a shunt than are neonates who experience a small reduction.

Multi-parametric MRI (mpMRI) is an effective tool for detecting and staging prostate cancer (PCa), guiding interventional therapy, and monitoring PCa treatment outcomes. MRI-guided focal laser ablation (FLA) therapy is an alternative, minimally invasive treatment method to conventional therapies, which has been demonstrated to control low-grade, localized PCa while preserving patient quality of life. The therapeutic success of FLA depends on the accurate placement of needles for adequate delivery of ablative energy to the target lesion. We previously developed an MR-compatible mechatronic system for prostate FLA needle guidance and validated its performance in open-air and clinical 3T in-bore experiments using virtual targets.To develop a robust MRI-to-mechatronic system registration method and evaluate its in-bore MR-guided needle delivery accuracy in tissue-mimicking prostate phantoms.The improved registration multi-fiducial assembly houses thirty-six aqueous gadolinium-filled spheres distributed over a 7.3 x 7.3 x 5.2 cm volume. MRI-guided needle guidance accuracy was quantified in agar-based tissue-mimicking prostate phantoms on trajectories (N = 44) to virtual targets covering the mechatronic system's range of motion. 3T gradient-echo recalled (GRE) MRI images were acquired after needle insertions to each target, and the air-filled needle tracks were segmented. Needle guidance error was measured as the shortest Euclidean distance between the target point and the segmented needle trajectory, and angular error was measured as the angle between the targeted trajectory and the segmented needle trajectory. These measurements were made using both the previously-designed four-sphere registration fiducial assembly on trajectories (N = 7) and compared with the improved multi-fiducial assembly using a Mann Whitney U test.The median needle guidance error of the system using the improved registration fiducial assembly at a depth of 10 cm was 1.02 mm with an interquartile range (IQR) of 0.42 - 2.94 mm. The upper limit of the one-sided 95% prediction interval of needle guidance error was 4.13 mm. The median (IQR) angular error was 0.0097 rad (0.0057 - 0.015 rad) with a one-sided 95% prediction interval upper limit of 0.022 rad. The median (IQR) positioning error using the previous four-sphere registration fiducial assembly was 1.87 mm (1.77 - 2.14 mm). This was found to be significantly different (p=0.0012) from the median (IQR) positioning error of 0.28 mm (0.14 - 0.95 mm) using the new registration fiducial assembly on the same trajectories. No significant difference was detected between the medians of the angular errors (p=0.26).This is the first study presenting an improved registration method and validation in tissue-mimicking phantoms of our remotely actuated MR-compatible mechatronic system for delivery of prostate FLA needles. Accounting for the effects of needle deflection, the system was demonstrated to be capable of needle delivery with an error of 4.13 mm or less in 95% of cases under ideal conditions, which is a statistically significant improvement over the previous method. The system will next be validated in a clinical setting. This article is protected by copyright. All rights reserved.

Carotid total plaque area (TPA) is an important contributing measurement to the evaluation of stroke risk. Deep learning provides an efficient method for ultrasound carotid plaque segmentation and TPA quantification. However, high performance of deep learning requires datasets with many labeled images for training, which is very labor-intensive. Thus, we propose an image reconstruction-based self-supervised learning algorithm (IR-SSL) for carotid plaque segmentation when few labeled images are available. IR-SSL consists of pre-trained and downstream segmentation tasks. The pre-trained task learns region-wise representations with local consistency by reconstructing plaque images from randomly partitioned and disordered images. The pre-trained model is then transferred to the segmentation network as the initial parameters in the downstream task. IR-SSL was implemented with two networks, UNet++ and U-Net, and evaluated on two independent datasets of 510 carotid ultrasound images from 144 subjects at SPARC (London, Canada) and 638 images from 479 subjects at Zhongnan hospital (Wuhan, China). Compared to the baseline networks, IR-SSL improved the segmentation performance when trained on few labeled images (n = 10, 30, 50 and 100 subjects). For 44 SPARC subjects, IR-SSL yielded Dice-similarity-coefficients (DSC) of 80.14–88.84%, and algorithm TPAs were strongly correlated ($ r = 0.962 - 0.993 $, $ p $ < 0.001) with manual results. The models trained on the SPARC images but applied to the Zhongnan dataset without retraining achieved DSCs of 80.61–88.18% and strong correlation with manual segmentation ($ r = 0.852 - 0.978 $, $ p $ < 0.001). These results suggest that IR-SSL could improve deep learning when trained on small labeled datasets, making it useful for monitoring carotid plaque progression/regression in clinical use and trials.

Joint arthropathies often require continuous monitoring of the joint condition, typically performed using magnetic resonance (MR) or ultrasound (US) imaging. US imaging is often the preferred screening or diagnostic tool as it is fast and inexpensive. However, conventional 2-D US has limited capability to compare imaging results between examinations because of its operator dependence and challenges related to repeat imaging in the same location and orientation. Comparison between several imaging sessions is crucial to assess the interval progression of joint conditions. We propose a novel 3-D US scanner for ankle joint assessment that can partially overcome these issues by enabling 3-D imaging. Here, we (i) present the design of the 3-D US ankle scanner system, (ii) validate the geometric reconstruction accuracy of the system, (iii) provide preliminary images of healthy volunteer ankles and (iv) compare 3-D US imaging results with MR imaging. The 3-D ankle scanner consists of a tub filled with water, a linear US probe attached to the wall of the tub and a motorized unit that rotates the US probe 360° around the center of the tub. As the probe rotates, a 3-D US image is formed of the ankle of the patient positioned in the middle of the tub. US probe height, angle and distance from the tub center can be adjusted. The reconstruction accuracy of the system was validated in each of the coordinate directions at different probe angles using two test phantoms. A phantom consisting of numerous Ø200-µm nylon threads with known spacing and a metal rod with machined grooves was used for validation in the horizontal and vertical directions, respectively. The volumetric reconstruction accuracy validation was performed by imaging an agar phantom with two embedded spheres of known volumes and comparing the segmented sphere volume and surface area with the expected. Three-dimensional US and MR images of both ankles of five healthy volunteers were acquired. Distal tibia and proximal talus were segmented in both imaging modalities and the surfaces of these segmentations were compared using the 95% Hausdorff and mean surface distances. The observed mean linear measurement error in all the coordinate directions and over several probe angles was 2.98%. The mean measured volumetric measurement error was 3.45%. The volunteer study revealed useful features for joint assessment present in the 3-D ankle scanner images, such as joint spacing, distal tibia and proximal talus. The mean 95% Hausdorff and mean surface distances between segmentations in 3-D US and MR images were 5.68 ± 0.83 and 2.01 ± 0.30 mm, respectively. In this proof-of-concept study, the 3-D US ankle scanner enabled visualization of the ankle joint features that are useful for joint assessment.

Mammographic screening has reduced mortality in women through the early detection of breast cancer. However, the sensitivity for breast cancer detection is significantly reduced in women with dense breasts, in addition to being an independent risk factor. Ultrasound (US) has been proven effective in detecting small, early-stage, and invasive cancers in women with dense breasts.To develop an alternative, versatile, and cost-effective spatially tracked three-dimensional (3D) US system for whole-breast imaging. This paper describes the design, development, and validation of the spatially tracked 3DUS system, including its components for spatial tracking, multi-image registration and fusion, feasibility for whole-breast 3DUS imaging and multi-planar visualization in tissue-mimicking phantoms, and a proof-of-concept healthy volunteer study.The spatially tracked 3DUS system contains (a) a six-axis manipulator and counterbalanced stabilizer, (b) an in-house quick-release 3DUS scanner, adaptable to any commercially available US system, and removable, allowing for handheld 3DUS acquisition and two-dimensional US imaging, and (c) custom software for 3D tracking, 3DUS reconstruction, visualization, and spatial-based multi-image registration and fusion of 3DUS images for whole-breast imaging. Spatial tracking of the 3D position and orientation of the system and its joints (JMean tracking errors were 0.87 ± 0.52, 0.70 ± 0.46, 0.53 ± 0.48, 0.34 ± 0.32, 0.43 ± 0.28, and 0.78 ± 0.54 mm for joints JOur spatially tracked 3DUS system shows potential utility as an alternative, accurate, and feasible whole-breast approach with the capability for bedside POC imaging. Future work is focused on reducing misregistration errors due to motion and tissue deformations, to develop a robust spatially tracked whole-breast 3DUS acquisition protocol, then exploring its clinical utility for screening high-risk women with dense breasts.

Supplementary Figure 6 from Functional Neoangiogenesis Imaging of Genetically Engineered Mouse Prostate Cancer Using Three-Dimensional Power Doppler Ultrasound

We report the first application of high-frequency three-dimensional power Doppler ultrasound imaging in a genetically engineered mouse (GEM) prostate cancer model. We show that the technology sensitively and specifically depicts functional neoangiogenic blood flow because little or no flow is measurable in normal prostate tissue or tumors smaller than 2–3 mm diameter, the neoangiogenesis “switch-on” size. Vascular structures depicted by power Doppler were verified using Microfil-enhanced micro-computed tomography (micro-CT) and by correlation with microvessel distributions measured by immunohistochemistry and enhanced vascularity visualized by confocal microscopy in two GEM models [transgenic adenocarcinoma of the mouse prostate (TRAMP) and PSP94 gene-directed transgenic mouse adenocarcinoma of the prostate (PSP-TGMAP)]. Four distinct phases of neoangiogenesis in cancer development were observed, specifically, (a) an early latent phase; (b) establishment of a peripheral capsular vascular structure as a neoangiogenesis initiation site; (c) a peak in tumor vascularity that occurs before aggressive tumor growth; and (d) rapid tumor growth accompanied by decreasing vascularity. Microsurgical interventions mimicking local delivery of antiangiogenesis drugs were done by ligating arteries upstream from feeder vessels branching to the prostate. Microsurgery produced an immediate reduction of tumor blood flow, and flow remained low from 1 h to 2 weeks or longer after treatment. Power Doppler, in conjunction with micro-CT, showed that the tumors recruit secondary blood supplies from nearby vessels, which likely accounts for the continued growth of the tumors after surgery. The microsurgical model represents an advanced angiogenic prostate cancer stage in GEM mice corresponding to clinically defined hormone-refractory prostate cancer. Three-dimensional power Doppler imaging is completely noninvasive and will facilitate basic and preclinical research on neoangiogenesis in live animal models. [Cancer Res 2007;67(6):2830–9]

Supplementary Procedures from Functional Neoangiogenesis Imaging of Genetically Engineered Mouse Prostate Cancer Using Three-Dimensional Power Doppler Ultrasound

Supplementary Movie 1 from Functional Neoangiogenesis Imaging of Genetically Engineered Mouse Prostate Cancer Using Three-Dimensional Power Doppler Ultrasound

Supplementary Figure 2 from A New Three-Dimensional Ultrasound Microimaging Technology for Preclinical Studies Using a Transgenic Prostate Cancer Mouse Model

Supplementary Figure 3 from Functional Neoangiogenesis Imaging of Genetically Engineered Mouse Prostate Cancer Using Three-Dimensional Power Doppler Ultrasound

Supplementary Figure 4 from Functional Neoangiogenesis Imaging of Genetically Engineered Mouse Prostate Cancer Using Three-Dimensional Power Doppler Ultrasound

Supplementary Figure 1 from A New Three-Dimensional Ultrasound Microimaging Technology for Preclinical Studies Using a Transgenic Prostate Cancer Mouse Model

Supplementary Figure 5 from Functional Neoangiogenesis Imaging of Genetically Engineered Mouse Prostate Cancer Using Three-Dimensional Power Doppler Ultrasound

Prostate cancer is the most common cancer in adult men in North America. Preclinical studies of prostate cancer employ genetically engineered mouse models, because prostate cancer does not occur naturally in rodents. Widespread application of these models has been limited because autopsy was the only reliable method to evaluate treatment efficacy in longitudinal studies. This article reports the first use of three-dimensional ultrasound microimaging for measuring tumor progression in a genetically engineered mouse model, the 94–amino acid prostate secretory protein gene-directed transgenic prostate cancer model. Qualitative comparisons of three-dimensional ultrasound images with serial histology sections of prostate tumors show the ability of ultrasound to accurately depict the size and shape of malignant masses in live mice. Ultrasound imaging identified tumors ranging from 2.4 to 14 mm maximum diameter. The correlation coefficient of tumor diameter measurements done in vivo with three-dimensional ultrasound and at autopsy was 0.998. Prospective tumor detection sensitivity and specificity were both >90% when diagnoses were based on repeated ultrasound examinations done on separate days. Representative exponential growth curves constructed via longitudinal ultrasound imaging indicated volume doubling times of 5 and 13 days for two prostate tumors. Compared with other microimaging and molecular imaging modalities, the application of three-dimensional ultrasound imaging to prostate cancer in mice showed advantages, such as high spatial resolution and contrast in soft tissue, fast and uncomplicated protocols, and portable and economical equipment that will likely enable ultrasound to become a new microimaging modality for mouse preclinical trial studies.

Supplementary Figure 3 from A New Three-Dimensional Ultrasound Microimaging Technology for Preclinical Studies Using a Transgenic Prostate Cancer Mouse Model

Supplementary Figure Legends 1-6 from Functional Neoangiogenesis Imaging of Genetically Engineered Mouse Prostate Cancer Using Three-Dimensional Power Doppler Ultrasound

PURPOSE In this study, we propose combining three-dimensional (3D) transrectal ultrasound (TRUS) and 3D transabdominal ultrasound (TAUS) images of gynecologic brachytherapy applicators to leverage the advantages of each imaging perspective, providing a broader field-of-view and allowing previously obscured features to be recovered. The aim of this study was to evaluate the feasibility of fusing these 3D ultrasound (US) perspectives based on the applicator geometry in a phantom prior to clinical implementation. METHODS In proof-of-concept experiments, 3D US images of application-specific multimodality pelvic phantoms were acquired with tandem-and-ring and tandem-and-ovoids applicators using previously validated imaging systems. Two TRUS images were acquired at different insertion depths and manually fused based on the position of the ring/ovoids to broaden the TRUS field-of-view. The phantom design allowed "abdominal thickness" to be modified to represent different body habitus and TAUS images were acquired at three thicknesses for each applicator. The merged TRUS images were then combined with TAUS images by rigidly aligning applicator components and manually refining the registration using the positions of source channels and known tandem length, as well as the ring diameter for the tandem-and-ring applicator. Combined 3D US images were manually, rigidly registered to images from a second modality (magnetic resonance (MR) imaging for the tandem-and-ring applicator and X-ray computed tomography (CT) for the tandem-and-ovoids applicator (based on applicator compatibility)) to assess alignment. Four spherical fiducials were used to calculate target registration errors (TREs), providing a metric for validating registrations, where TREs were computed using root-mean-square distances to describe the alignment of manually identified corresponding fiducials. An analysis of variance (ANOVA) was used to identify statistically significant differences (p

Carotid ultrasound measurement of total plaque area (TPA) provides a method for quantifying carotid plaque burden and monitoring changes in carotid atherosclerosis in response to medical treatment. Plaque boundary segmentation is required to generate the TPA measurement; however, training of observers and manual delineation are time consuming. Thus, our objective was to develop an automated plaque segmentation method to generate TPA from longitudinal carotid ultrasound images. In this study, a deep learning-based method, modified U-Net, was used to train the segmentation model and generate TPA measurement. A total of 510 plaques from 144 patients were used in our study, where the Monte Carlo cross-validation was used by randomly splitting the data set into 2/3 and 1/3 for training and testing. Two observers were trained to manually delineate the 510 plaques separately, which were used as the ground-truth references. Two U-Net models (M1 and M2) were trained using the two different ground-truth data sets from the two observers to evaluate the accuracy, variability and sensitivity on the ground-truth data sets used for training our method. The results of the algorithm segmentations of the two models yielded strong agreement with the two manual segmentations with the Pearson correlation coefficient r = 0.989 (p0.0001) and r = 0.987 (p0.0001). Comparison of the U-Net and manual segmentations resulted in mean TPA differences of 0.05 ± 7.13 mm

With the increase of the ageing in the world’s population, the ageing and degeneration studies of physiological characteristics in human skin, bones, and muscles become important topics. Research on the ageing of bones, especially the skull, are paid much attention in recent years. In this study, a novel deep learning method representing the ageing-related dynamic attention (ARDA) is proposed. The proposed method can quantitatively display the ageing salience of the bones and their change patterns with age on lateral cephalometric radiographs images (LCR) images containing the craniofacial and cervical spine. An age estimation-based deep learning model based on 14142 LCR images from 4 to 40 years old individuals is trained to extract ageing-related features, and based on these features the ageing salience maps are generated by the Grad-CAM method. All ageing salience maps with the same age are merged as an ARDA map corresponding to that age. Ageing salience maps show that ARDA is mainly concentrated in three regions in LCR images: the teeth, craniofacial, and cervical spine regions. Furthermore, the dynamic distribution of ARDA at different ages and instances in LCR images is quantitatively analyzed. The experimental results on 3014 cases show that ARDA can accurately reflect the development and degeneration patterns in LCR images.

Measurement of total-plaque-area (TPA) is important for determining long term risk for stroke and monitoring carotid plaque progression. Since delineation of carotid plaques is required, a deep learning method can provide automatic plaque segmentations and TPA measurements; however, it requires large datasets and manual annotations for training with unknown performance on new datasets. A UNet++ ensemble algorithm was proposed to segment plaques from 2D carotid ultrasound images, trained on three small datasets (n = 33, 33, 34 subjects) and tested on 44 subjects from the SPARC dataset (n = 144, London, Canada). The ensemble was also trained on the entire SPARC dataset and tested with a different dataset (n = 497, Zhongnan Hospital, China). Algorithm and manual segmentations were compared using Dice-similarity-coefficient (DSC), and TPAs were compared using the difference ( $\Delta$ TPA), Pearson correlation coefficient ( r ) and Bland-Altman analyses. Segmentation variability was determined using the intra-class correlation coefficient (ICC) and coefficient-of-variation (CoV). For 44 SPARC subjects, algorithm DSC was 83.3–85.7%, and algorithm TPAs were strongly correlated ( r = 0.985–0.988; p $^2$ using the three training datasets. Algorithm ICC for TPAs (ICC = 0.996) was similar to intra- and inter-observer manual results (ICC = 0.977, 0.995). Algorithm CoV = 6.98% for plaque areas was smaller than the inter-observer manual CoV (7.54%). For the Zhongnan dataset, DSC was 88.6% algorithm and manual TPAs were strongly correlated ( r = 0.972, p $\Delta$ TPA = −0.44 $\pm$ 4.05 mm $^2$ and ICC = 0.985. The proposed algorithm trained on small datasets and segmented a different dataset without retraining with accuracy and precision that may be useful clinically and for research.

Purpose Prostate cancer is the most common non-cutaneous cancer among men in the United States and is the second leading cause of cancer death in American men. (Siegel et al. [2019] CA: A Cancer J Clin.69(1):7-34.) Focal laser ablation (FLA) has the potential to control small tumors while preserving urinary and erectile function by leaving the neurovascular bundles and urethral sphincters intact. Accurate needle guidance is critical to the success of FLA. Multiparametric magnetic resonance images (mpMRI) can be used to identify targets, guide needles, and assess treatment outcomes. The purpose of this work was to design and evaluate the accuracy of an MR-compatible mechatronic system for in-bore transperineal guidance of FLA ablation needles to localized lesions in the prostate. Methods The mechatronic system was constructed entirely of non-ferromagnetic materials, with actuation controlled by piezoelectric motors and optical encoders. The needle guide hangs between independent front and rear two-link arms, which allows for horizontal and vertical translation as well as pitch and yaw rotation of the guide with a 6.0 cm range of motion in each direction. Needles are inserted manually through a chosen hole in the guide, which has been aligned with the target in the prostate. Open-air positioning error was evaluated using an optical tracking system (0.25 mm RMS accuracy) to measure 125 trajectories in free space. Correction of systematic bias in the system was performed using 85 of the trajectories, and the remaining 40 were used to estimate the residual error. The error was calculated as the horizontal and vertical displacement between the axis of the desired and measured trajectories at a typical needle insertion depth of 10 cm. MR-compatibility was evaluated using a grid phantom to assess image degradation due to the presence of the system, and induced force, heating, and electrical interference in the system were assessed qualitatively. In-bore positioning error was evaluated on 25 trajectories. Results Open-air mean positioning error at the needle tip was 0.80 ± 0.36 mm with a one-sided 95% confidence interval of 1.40 mm. The mean deviation of needle trajectories from the planned direction was 0.14 ± 0.06∘ . In the MR bore, the mean positioning error at the needle tip was 2.11 ± 1.05 mm with a one-sided 95% prediction interval of 3.84 mm. The mean angular error was 0.49 ± 0.26∘ . The system was found to be compatible with the MR environment under the specified gradient-echo sequence parameters used in this study. Conclusion A complete system for delivering needles to localized prostate tumors was developed and described in this work, and its compatibility with the MR environment was demonstrated. In-bore MRI positioning error was sufficiently small for targeting small localized prostate tumors.

OBJECTIVE: Effusion-synovitis is related to pain and progression in knee osteoarthritis (OA), but current gold standard ultrasound (US) measures are limited to semi-quantitative grading of joint distension or 1-dimensional thickness measures. A novel quantitative 2-dimensional image analysis methodology is applied to US images of effusion-synovitis; reliability and concurrent validity was assessed in patients with knee OA. METHODS: Cross sectional analysis of US images collected from 51 patients with symptomatic knee OA were processed in ImageJ and segmented in 3DSlicer to produce a binary mask of the supra-patellar synovitis region of interest (ROI). Area measures (mm(2)) of total synovitis, effusion and hypertrophy components were exported. Intra-rater reliability and test-retest reliability (1–14 days washout) were estimated with intra-class correlation coefficients (ICCs). Concurrent validity was measured by Spearman correlations between quantitative measures and gold standard OMERACT and caliper measurements of synovitis. RESULTS: Intra-rater reliability for hypertrophy area was estimated at 0.98, 0.99 for effusion area, and 0.99 for total synovitis area. The test-retest reliability for total synovitis area was 0.63 (SEM 87.8 ​mm(2)), 0.59 for hypertrophy area (SEM 21.0 ​mm(2)), and 0.64 for effusion area (SEM 73.8 ​mm(2)). Correlation between total synovitis area and OMERACT grade was 0.84, 0.81 between total synovitis area and effusion-synovitis calipers, and 0.81 between total effusion area and effusion calipers. CONCLUSION: This new research tool for image analysis demonstrated excellent intra-rater reliability, good concurrent validity, and moderate test-retest reliability. Quantitative 2D US measures of effusion-synovitis and its individual components may enhance the study and management of knee OA.

PURPOSE Image-guided needle biopsy of small, detectable lesions is crucial for early-stage diagnosis, treatment planning, and management of breast cancer. High-resolution positron emission mammography (PEM) is a dedicated functional imaging modality that can detect breast cancer independent of breast tissue density, but anatomical context and real-time needle visualization are not yet available to guide biopsy. We propose a mechatronic guidance system integrating an ultrasound (US)-guided core-needle biopsy (CNB) with high-resolution PEM localization to improve the spatial sampling of breast lesions. This paper presents the benchtop testing and phantom studies to evaluate the accuracy of the system and its constituent components for targeted PEM-US-guided biopsy under simulated high-resolution PEM localization. METHODS A mechatronic guidance system was developed to operate with the Radialis PEM system and a conventional US system. The system includes a user-operated guidance arm and end-effector biopsy device, integrating a US transducer and CNB gun, with its needle focused on a remote center of motion (RCM). Custom software modules were developed to track, display, and guide the end-effector biopsy device. Registration of the mechatronic guidance system to a simulated PEM detector plate was performed using a landmark-based method. Testing was performed with fiducials positioned in the peripheral and central regions of the simulated detector plate and registration error was quantified. Breast phantom experiments were performed under ideal detection and localization to evaluate for bias in the end-effector biopsy device. The accuracy of the complete mechatronic guidance system to perform targeted breast biopsy was assessed using breast phantoms with simulated lesions. Three-dimensional positioning error was quantified, and principal component analysis assessed for directional trends in 3D space within 95% prediction intervals. Targeted breast biopsies with test phantoms were performed and an overall in-plane needle targeting error was quantified. RESULTS The mean registration errors were 0.63 mm (N = 44) and 0.73 mm (N = 72) in the peripheral and central regions of the simulated PEM detector plate, respectively. A 3D 95% prediction ellipsoid shows an error volume

Complete tumor coverage by the thermal ablation zone and with a safety margin (5 or 10 mm) is required to achieve the entire tumor eradication in liver tumor ablation procedures. However, 2D ultrasound (US) imaging has limitations in evaluating the tumor coverage by imaging only one or multiple planes, particularly for cases with multiple inserted applicators or irregular tumor shapes. In this paper, we evaluate the intra-procedural tumor coverage using 3D US imaging and investigate whether it can provide clinically needed information. Using data from 14 cases, we employed surface- and volume-based evaluation metrics to provide information on any uncovered tumor region. For cases with incomplete tumor coverage or uneven ablation margin distribution, we also proposed a novel margin uniformity -based approach to provide quantitative applicator adjustment information for optimization of tumor coverage. Both the surface- and volume-based metrics showed that 5 of 14 cases had incomplete tumor coverage according to the estimated ablation zone. After applying our proposed applicator adjustment approach, the simulated results showed that 92.9% (13 of 14) cases achieved 100% tumor coverage and the remaining case can benefit by increasing the ablation time or power. Our proposed method can evaluate the intra-procedural tumor coverage and intuitively provide applicator adjustment information for the physician. Our 3D US-based method is compatible with the constraints of conventional US-guided ablation procedures and can be easily integrated into the clinical workflow.

Thanka murals are important cultural heritages of Tibet, but many precious murals were damaged during history. Thanka mural restoration is very important for the protection of Tibetan cultural heritage. Partial convolution has great potential for Thanka mural restoration due to its outstanding performance for inpainting irregular holes. However, three challenges prevent the existing partial convolution-based methods from solving Thanka restoration problems: 1) the features of multi-scale objects in Thanka murals cannot be extracted correctly because of single-scale partial convolution; 2) the stroke-like Thanka inpainting mode cannot be effectively simulated and learned by existing rectangular or arbitrary masks; and 3) the original content of damaged Thanka murals cannot be restored. To resolve these problems, we propose a Thanka mural inpainting method based on multi-scale adaptive partial convolution and stroke-like masks. The proposed method consists of three parts: 1) a kernel-level multi-scale adaptive partial convolution (MAPConv) to accurately discriminate valid pixels from invalid pixels, and to extract the features of multi-scale objects; 2) a parameter-configurable stroke-like mask generation method to simulate and learn the stroke-like Thanka inpainting mode; and 3) a 2-phase learning framework based on MAPConv Unet and different loss functions to restore the original content of Thanka murals. Experiments on both simulated and real damages of Thanka murals demonstrated that our approach works well on a small dataset (N=2780), generates realistic mural content, and restores the damaged Thanka murals with high speed (600 ms for multiple holes in $512\times 512$ images). The proposed end-to-end method can be applied to other small datasets-based inpainting tasks.

Purpose Permanent breast seed implant (PBSI) brachytherapy is a novel technique for early-stage breast cancer. Computed tomography (CT) images are used for treatment planning and freehand 2D ultrasound for implant guidance. The multimodality imaging approach leads to discrepancies in target identification. To address this, a prototype 3D ultrasound (3DUS) system was recently developed for PBSI. In this study, we characterize the 3DUS system performance, establish QA baselines, and develop and test a method to register 3DUS images to CT images for PBSI planning. Methods and Materials 3DUS system performance was characterized by testing distance and volume measurement accuracy, and needle template alignment accuracy. 3DUS-CT registration was achieved through point-based registration using a 3D-printed model designed and constructed to provide visible landmarks on both images and tested on an in-house made gel breast phantom. Results The 3DUS system mean distance measurement accuracy was within 1% in axial, lateral, and elevational directions. A volumetric error of 3% was observed. The mean needle template alignment error was 1.0° ± 0.3 ° and 1.3 ± 0.5 mm. The mean 3DUS-CT registration error was within 3 mm when imaging at the breast centre or across all breast quadrants. Conclusions This study provided baseline data to characterize the performance of a prototype 3DUS system for PBSI planning and developed and tested a method to obtain accurate 3DUS-CT image registration for PBSI planning. Future work will focus on system validation and characterization in a clinical context as well as the assessment of impact on treatment plans.

Objective This study aimed to determine whether there are differences in the lateral ventricular volumes, measured by three-dimensional ultrasound (3D US) depending on the posture of the neonate (right and left lateral decubitus). Study Design This was a prospective analysis of the lateral ventricular volumes of preterm neonates recruited from Victoria Hospital, London, Ontario (June 2018–November 2019). A total of 24 premature neonates were recruited. The first cohort of 18 unstable premature neonates were imaged with 3D US in their current sides providing 15 right-sided and 16 left-sided 3D US images. The neonates in the second cohort of six relatively stable infants were imaged after positioning in each lateral decubitus position for 30 minutes, resulting in 40 3D US images obtained from 20 posture change sessions. The images were segmented and the ventricle volumes in each lateral posture were compared with determine whether the posture of the head influenced the volume of the upper and lower ventricle. Results For the first cohort who did not have their posture changed, the mean of the right and left ventricle volumes were 23.81 ± 15.51 and 21.61 ± 16.19 cm3, respectively, for the 15 images obtained in a right lateral posture and 13.96 ± 8.69 and 14.92 ± 8.77 cm3, respectively, for the 16 images obtained in the left lateral posture. Similarly, for the second cohort who had their posture changed, the mean of right and left ventricle volumes were 20.92 ± 17.3 and 32.74 ± 32.33 cm3, respectively, after 30 minutes in the right lateral posture, and 21.25 ± 18.4 and 32.65 ± 31.58 cm3, respectively, after 30 minutes in the left lateral posture. Our results failed to show a statistically significant difference in ventricular volumes dependence on posture. Conclusion Head positioned to any lateral side for 30 minutes does not have any effect on the lateral ventricular volumes of neonates. Key Points

Preoperative treatment planning is key to ensure successful thermal ablation of liver tumors. The planning aims to minimize the number of electrodes required for complete ablation and the damage to the surrounding tissues while satisfying multiple clinical constraints. This is a challenging multiple objective planning problem, in which the trade-off between different objectives must be considered. We propose a novel method to solve the multiple objective planning problem, which combines the set cover-based model and Pareto optimization. The set cover-based model considers multiple clinical constraints and generates several clinically feasible treatment plans, among which the Pareto optimization is performed to find the trade-off between different objectives. We evaluated the proposed method on 20 tumors of 11 patients in two different situations used in common thermal ablation approaches: with and without the pull-back technique. Pareto optimal plans were found and verified to be clinically acceptable in all cases, which can find the trade-off between the number of electrodes and the damage to the surrounding tissues. The proposed method performs well in the two different situations we considered: with or without the pull-back technique. It can generate Pareto optimal plans satisfying multiple clinical constraints. These plans consider the trade-off between different planning objectives.

The purpose of this study was to evaluate the use of a semiautomatic algorithm to simultaneously segment multiple high-dose-rate (HDR) gynecologic interstitial brachytherapy (ISBT) needles in three-dimensional (3D) transvaginal ultrasound (TVUS) images, with the aim of providing a clinically useful tool for intraoperative implant assessment.A needle segmentation algorithm previously developed for HDR prostate brachytherapy was adapted and extended to 3D TVUS images from gynecologic ISBT patients with vaginal tumors. Two patients were used for refining/validating the modified algorithm and five patients (8-12 needles/patient) were reserved as an unseen test data set. The images were filtered to enhance needle edges, using intensity peaks to generate feature points, and leveraged the randomized 3D Hough transform to identify candidate needle trajectories. Algorithmic segmentations were compared against manual segmentations and calculated dwell positions were evaluated.All 50 test data set needles were successfully segmented with 96% of algorithmically segmented needles having angular differences3° compared with manually segmented needles and the maximum Euclidean distance was2.1 mm. The median distance between corresponding dwell positions was 0.77 mm with 86% of needles having maximum differences3 mm. The mean segmentation time using the algorithm was30 s/patient.We successfully segmented multiple needles simultaneously in intraoperative 3D TVUS images from gynecologic HDR-ISBT patients with vaginal tumors and demonstrated the robustness of the algorithmic approach to image artifacts. This method provided accurate segmentations within a clinically efficient timeframe, providing the potential to be translated into intraoperative clinical use for implant assessment.

Prostate cancer (PCa) is a common, serious form of cancer in men that is still prevalent despite ongoing developments in diagnostic oncology. Current detection methods lead to high rates of inaccurate diagnosis. We present a method to directly model and exploit temporal aspects of temporal enhanced ultrasound (TeUS) for tissue characterization, which improves malignancy prediction. We employ a probabilistic-temporal framework, namely, hidden Markov models (HMMs), for modeling TeUS data obtained from PCa patients. We distinguish malignant from benign tissue by comparing the respective log-likelihood estimates generated by the HMMs. We analyze 1100 TeUS signals acquired from 12 patients. Our results show improved malignancy identification compared to previous results, demonstrating over 85% accuracy and AUC of 0.95. Incorporating temporal information directly into the models leads to improved tissue differentiation in PCa. We expect our method to generalize and be applied to other types of cancer in which temporal-ultrasound can be recorded.

Radiofrequency ablation (RFA) is now a widely used minimally invasive treatment method for hepatic tumors. Preoperative planning plays a vital role in RFA therapy. With increasing tumor size, multiple overlapping ablations are needed, which are challenging to optimize while considering clinical constraints. In this paper, we present a new automatic RFA planning method. First, a 2-steps set cover-based model is formulated, which can integrate multiple clinical constraints for optimization of overlapping ablations. To ensure that the planning model can be solved in a reasonable time, a search space reducing strategy is then proposed. We also developed an algorithm for automatic RFA electrode selection, which provides a proper electrode ablation zone for the planning model. The proposed method was evaluated with 20 tumors of varying sizes (0.92 cm3 to 28.4 cm3). Results showed that the proposed method can generate clinical feasible RFA plans with a minimum number of RFA electrodes and ablations, complete tumor coverage and minimized ablation of normal tissue.