Laser diode photoacoustic point source detection: machine learning-based denoising and reconstruction.

A new development in photoacoustic (PA) imaging has been the use of compact, portable and low-cost laser diodes (LDs), but LD-based PA imaging suffers from low signal intensity recorded by the conventional transducers. A common method to improve signal strength is temporal averaging, which reduces frame rate and increases laser exposure to patients. To tackle this problem, we propose a deep learning method that will denoise point source PA radio-frequency (RF) data before beamforming with a very few frames, even one. We also present a deep learning method to automatically reconstruct point sources from noisy pre-beamformed data. Finally, we employ a strategy of combined denoising and reconstruction, which can supplement the reconstruction algorithm for very low signal-to-noise ratio inputs.

A framework for optimization-based design of motion encoding in magnetic resonance elastography.

PURPOSE: In conventional three-dimensional magnetic resonance elastography, motion encoding gradients (MEGs) synchronized to a mechanical excitation are applied separately in each direction to encode tissue displacement generated by the corresponding waves. This requires long acquisition times that introduce errors due to patient motion and may hinder clinical deployment of magnetic resonance elastography. In this article, a framework for MEGs sequence design is proposed to reduce scanning time and increase signal-to-noise ratio. THEORY AND METHODS: The approach is based on applying MEGs in all three directions simultaneously with varying parameters, and formulation of the problem as a linear estimation of the wave properties. Multidirectional MEGs sequences are derived by setting the problem in an experimental design framework. Such designs are implemented and evaluated on simulation and phantom data. RESULTS: Estimation error of the displacement using the proposed MEGs designs is reduced up to a factor of two in comparison with a unidirectional design with a same number of acquisitions. Alternatively, for the same error, scanning time is reduced up to a factor of three using the multidirectional designs. CONCLUSION: The proposed framework generalizes acquisition of magnetic resonance elastography, and allows quantification of design performance, and optimization-based derivation of designs.

Intraoperative registered transrectal ultrasound guidance for robot-assisted laparoscopic radical prostatectomy.

PURPOSE: To provide unencumbered real-time ultrasound image guidance during robot-assisted laparoscopic radical prostatectomy, we developed a robotic transrectal ultrasound system that tracks the da Vinci® Surgical System instruments. We describe our initial clinical experience with this system. MATERIALS AND METHODS: After an evaluation in a canine model, 20 patients were enrolled in the study. During each procedure the transrectal ultrasound transducer was manually positioned using a brachytherapy stabilizer to provide good imaging of the prostate. Then the transrectal ultrasound was registered to the da Vinci robot by a previously validated procedure. Finally, automatic rotation of the transrectal ultrasound was enabled such that the transrectal ultrasound imaging plane safely tracked the tip of the da Vinci instrument controlled by the surgeon, while real-time transrectal ultrasound images were relayed to the surgeon at the da Vinci console. Tracking was activated during all critical stages of the surgery. RESULTS: The transrectal ultrasound robot was easy to set up and use, adding 7 minutes (range 5 to 14) to the procedure. It did not require an assistant or additional control devices. Qualitative feedback was acquired from the surgeons, who found transrectal ultrasound useful in identifying the urethra while passing the dorsal venous complex suture, defining the prostate-bladder interface during bladder neck dissection, identifying the seminal vesicles and their location with respect to the rectal wall, and identifying the distal prostate boundary at the apex. CONCLUSIONS: Real-time, registered robotic transrectal ultrasound guidance with automatic instrument tracking during robot-assisted laparoscopic radical prostatectomy is feasible and potentially useful. The results justify further studies to establish whether the approach can improve procedure outcomes.

MR elastography and diffusion-weighted imaging of ex vivo prostate cancer: quantitative comparison to histopathology.

The purpose of this work was (1) to develop a magnetic resonance elastography (MRE) system for imaging of the ex vivo human prostate and (2) to assess the diagnostic power of mono-frequency and multi-frequency MRE and diffusion weighted imaging (DWI) alone and combined as correlated with histopathology in a patient study. An electromagnetic driver was designed specifically for MRE studies in small-bore MR scanners. Ex vivo prostate specimens (post-fixation) of 14 patients who underwent radical prostatectomy were imaged with MRE at 7 T (nine cases had DWI). In six patients, the MRE examination was performed at three frequencies (600, 800, 1000 Hz) to extract the power-law exponent Gamma. The images were registered to wholemount pathology slides marked with the Gleason score. The areas under the receiver-operator-characteristic curves (AUC) were calculated. The methods were validated in a phantom study and it was demonstrated that (i) the driver does not interfere with the acquisition process and (ii) the driver can generate amplitudes greater than 100 µm for frequencies less than 1 kHz. In the quantitative study, cancerous tissue with Gleason score at least 3 + 3 was distinguished from normal tissue in the peripheral zone (PZ) with an average AUC of 0.75 (Gd ), 0.75 (Gl ), 0.70 (Gamma-Gd ), 0.68 (apparent diffusion coefficient, ADC), and 0.82 (Gd + Gl + ADC). The differentiation between PZ and central gland was modest for Gd (p < 0.07), Gl (p < 0.06) but not significant for Gamma (p < 0.2). A correlation of 0.4 kPa/h was found between the fixation time of the prostate specimen and the stiffness of the tissue, which could affect the diagnostic power results. DWI and MRE may provide complementary information; in fact MRE performed better than ADC in distinguishing normal from cancerous tissue in some cases. Multi-frequency (Gamma) analysis did not appear to improve the results. However, in light of the effect of tissue fixation, the clinical implication of our results may be inconclusive and more experiments are needed.

MR elastography of prostate cancer: quantitative comparison with histopathology and repeatability of methods.

The purpose of this work was to assess trans-perineal prostate magnetic resonance elastography (MRE) for (1) repeatability in phantoms/volunteers and (2) diagnostic power as correlated with histopathology in prostate cancer patients. The three-dimensional (3D) displacement field was obtained using a fractionally encoded gradient echo sequence using a custom-made transducer. The repeatability of the method was assessed based on three repeat studies and by changing the driving frequency by 3% in studies on a phantom and six healthy volunteers. Subsequently, 11 patients were examined with MRE prior to radical prostatectomy. The areas under the receiver operating characteristic curves were calculated using a windowed voxel-to-voxel approach by comparing the 2D registered slides, masked with the Gleason score. For the repeatability study, the average intraclass correlation coefficient for elasticity images was 99% for repeat phantom studies, 98% for ±6 Hz phantom studies, 95% for volunteer repeat studies with 2 min acquisition time, 82% for ±2 Hz volunteer studies with 2 min acquisition time and 73% for repeat volunteer studies with 8 min acquisition time. For the patient study, the average elasticity was 8.2 ± 1.7 kPa in the prostate capsule, 7.5 ± 1.9 kPa in the peripheral zone (PZ), 9.7 ± 3.0 kPa in the central gland (CG) and 9.0 ± 3.4 kPa in the transition zone. In the patient study, cancerous tissue with Gleason score at least 3 + 3 was significantly (p < 0.05) different from normal tissue in 10 out of 11 cases with tumors in the PZ, and 6 out of 9 cases with tumors in the CG. However, the overall case-averaged area under the curve was 0.72 in the PZ and 0.67 in the CG. Cancerous tissue was not always stiffer than normal tissue. The inversion algorithm was sensitive to (i) vibration amplitude and displacement nodes and (ii) misalignment of the 3D wave field due to subject movement.

Tracking and mapping in medical computer vision: A review.

As computer vision algorithms increase in capability, their applications in clinical systems will become more pervasive. These applications include: diagnostics, such as colonoscopy and bronchoscopy; guiding biopsies, minimally invasive interventions, and surgery; automating instrument motion; and providing image guidance using pre-operative scans. Many of these applications depend on the specific visual nature of medical scenes and require designing algorithms to perform in this environment. In this review, we provide an update to the field of camera-based tracking and scene mapping in surgery and diagnostics in medical computer vision. We begin with describing our review process, which results in a final list of 515 papers that we cover. We then give a high-level summary of the state of the art and provide relevant background for those who need tracking and mapping for their clinical applications. After which, we review datasets provided in the field and the clinical needs that motivate their design. Then, we delve into the algorithmic side, and summarize recent developments. This summary should be especially useful for algorithm designers and to those looking to understand the capability of off-the-shelf methods. We maintain focus on algorithms for deformable environments while also reviewing the essential building blocks in rigid tracking and mapping since there is a large amount of crossover in methods. With the field summarized, we discuss the current state of the tracking and mapping methods along with needs for future algorithms, needs for quantification, and the viability of clinical applications. We then provide some research directions and questions. We conclude that new methods need to be designed or combined to support clinical applications in deformable environments, and more focus needs to be put into collecting datasets for training and evaluation.

Surgical Tattoos in Infrared: A Dataset for Quantifying Tissue Tracking and Mapping.

Quantifying performance of methods for tracking and mapping tissue in endoscopic environments is essential for enabling image guidance and automation of medical interventions and surgery. Datasets developed so far either use rigid environments, visible markers, or require annotators to label salient points in videos after collection. These are respectively: not general, visible to algorithms, or costly and error-prone. We introduce a novel labeling methodology along with a dataset that uses said methodology, Surgical Tattoos in Infrared (STIR). STIR has labels that are persistent but invisible to visible spectrum algorithms. This is done by labelling tissue points with IR-fluorescent dye, indocyanine green (ICG), and then collecting visible light video clips. STIR comprises hundreds of stereo video clips in both in vivo and ex vivo scenes with start and end points labelled in the IR spectrum. With over 3,000 labelled points, STIR will help to quantify and enable better analysis of tracking and mapping methods. After introducing STIR, we analyze multiple different frame-based tracking methods on STIR using both 3D and 2D endpoint error and accuracy metrics. STIR is available at https://dx.doi.org/10.21227/w8g4-g548.

Arc-to-line frame registration method for ultrasound and photoacoustic image-guided intraoperative robot-assisted laparoscopic prostatectomy.

PURPOSE: To achieve effective robot-assisted laparoscopic prostatectomy, the integration of transrectal ultrasound (TRUS) imaging system which is the most widely used imaging modality in prostate imaging is essential. However, manual manipulation of the ultrasound transducer during the procedure will significantly interfere with the surgery. Therefore, we propose an image co-registration algorithm based on a photoacoustic marker (PM) method, where the ultrasound/photoacoustic (US/PA) images can be registered to the endoscopic camera images to ultimately enable the TRUS transducer to automatically track the surgical instrument. METHODS: An optimization-based algorithm is proposed to co-register the images from the two different imaging modalities. The principle of light propagation and an uncertainty in PM detection were assumed in this algorithm to improve the stability and accuracy of the algorithm. The algorithm is validated using the previously developed US/PA image-guided system with a da Vinci surgical robot. RESULTS: The target-registration-error (TRE) is measured to evaluate the proposed algorithm. In both simulation and experimental demonstration, the proposed algorithm achieved a sub-centimeter accuracy which is acceptable in practical clinics (i.e., 1.15 ± 0.29 mm from the experimental evaluation). The result is also comparable with our previous approach (i.e., 1.05 ± 0.37 mm), and the proposed method can be implemented with a normal white light stereo camera and does not require highly accurate localization of the PM. CONCLUSION: The proposed frame registration algorithm enabled a simple yet efficient integration of commercial US/PA imaging system into laparoscopic surgical setting by leveraging the characteristic properties of acoustic wave propagation and laser excitation, contributing to automated US/PA image-guided surgical intervention applications.

Transperineal prostate MR elastography: initial in vivo results.

This article presents a new approach to magnetic resonance elastography of the prostate using transperineal mechanical excitation. This approach is validated using a prostate elasticity phantom and in vivo studies of healthy volunteers. It is demonstrated that the transperineal approach can generate shear wave amplitudes on the order of 6-30 µm in the mid-gland region. The driver was implemented using an electromagnetic actuator with a hydraulic transmission system. The magnetic resonance elastography acquisition time has been reduced significantly by using a "second harmonic" approach. Displacement fields are processed using the established three-dimensional local frequency estimation algorithm. The three-dimensional curl-based direct inversion was used to calculate the local wavelength. The traveling wave expansion algorithm was used to reconstruct the wave damping image for one case. Using the proposed method, it was possible to resolve lesions of 0.5 cc in the phantom study. Repeatability experiments were performed and analyzed. The results from this study indicate that transperineal magnetic resonance elastography--without an endorectal coil--is a suitable candidate for a patient study involving multiparametric magnetic resonance imaging of prostate cancer, where magnetic resonance elastography may provide additional information for improved diagnosis and image-based surveillance.

Robotic ultrasound imaging: State-of-the-art and future perspectives.

Ultrasound (US) is one of the most widely used modalities for clinical intervention and diagnosis due to the merits of providing non-invasive, radiation-free, and real-time images. However, free-hand US examinations are highly operator-dependent. Robotic US System (RUSS) aims at overcoming this shortcoming by offering reproducibility, while also aiming at improving dexterity, and intelligent anatomy and disease-aware imaging. In addition to enhancing diagnostic outcomes, RUSS also holds the potential to provide medical interventions for populations suffering from the shortage of experienced sonographers. In this paper, we categorize RUSS as teleoperated or autonomous. Regarding teleoperated RUSS, we summarize their technical developments, and clinical evaluations, respectively. This survey then focuses on the review of recent work on autonomous robotic US imaging. We demonstrate that machine learning and artificial intelligence present the key techniques, which enable intelligent patient and process-specific, motion and deformation-aware robotic image acquisition. We also show that the research on artificial intelligence for autonomous RUSS has directed the research community toward understanding and modeling expert sonographers' semantic reasoning and action. Here, we call this process, the recovery of the "language of sonography". This side result of research on autonomous robotic US acquisitions could be considered as valuable and essential as the progress made in the robotic US examination itself. This article will provide both engineers and clinicians with a comprehensive understanding of RUSS by surveying underlying techniques. Additionally, we present the challenges that the scientific community needs to face in the coming years in order to achieve its ultimate goal of developing intelligent robotic sonographer colleagues. These colleagues are expected to be capable of collaborating with human sonographers in dynamic environments to enhance both diagnostic and intraoperative imaging.

Robotically controlled three-dimensional micro-ultrasound for prostate biopsy guidance.

PURPOSE: Prostate imaging to guide biopsy remains unsatisfactory, with current solutions suffering from high complexity and poor accuracy and reliability. One novel entrant into this field is micro-ultrasound (microUS), which uses a high-frequency imaging probe to achieve very high spatial resolution, and achieves prostate cancer detection rates equivalent to multiparametric magnetic resonance imaging (mpMRI). However, the ExactVu transrectal microUS probe has a unique geometry that makes it challenging to acquire controlled, repeatable three-dimensional (3D) transrectal ultrasound (TRUS) volumes. We describe the design, fabrication, and validation of a 3D acquisition system that allows for the accurate use of the ExactVu microUS device for volumetric prostate imaging. METHODS: The design uses a motorized, computer-controlled brachytherapy stepper to rotate the ExactVu transducer about its axis. We perform geometric validation using a phantom with known dimensions and compare performance with magnetic resonance imaging (MRI) using a commercial quality assurance anthropomorphic prostate phantom. RESULTS: Our geometric validation shows accuracy of 1 mm or less in all three directions, and images of an anthropomorphic phantom qualitatively match those acquired using MRI and show good agreement quantitatively. CONCLUSION: We describe the first system to acquire robotically controlled 3D microUS images using the ExactVu microUS system. The reconstructed 3D microUS images are accurate, which will allow for future applications of the ExactVu microUS system in prostate specimen and in vivo imaging.

Automatic search for photoacoustic marker using automated transrectal ultrasound.

Real-time transrectal ultrasound (TRUS) image guidance during robot-assisted laparoscopic radical prostatectomy has the potential to enhance surgery outcomes. Whether conventional or photoacoustic TRUS is used, the robotic system and the TRUS must be registered to each other. Accurate registration can be performed using photoacoustic (PA markers). However, this requires a manual search by an assistant [IEEE Robot. Autom. Lett8, 1287 (2023).10.1109/LRA.2022.3191788]. This paper introduces the first automatic search for PA markers using a transrectal ultrasound robot. This effectively reduces the challenges associated with the da Vinci-TRUS registration. This paper investigated the performance of three search algorithms in simulation and experiment: Weighted Average (WA), Golden Section Search (GSS), and Ternary Search (TS). For validation, a surgical prostate scenario was mimicked and various ex vivo tissues were tested. As a result, the WA algorithm can achieve 0.53°±0.30° average error after 9 data acquisitions, while the TS and GSS algorithm can achieve 0.29∘±0.31∘ and 0.48°±0.32° average errors after 28 data acquisitions.

3-D Ultrafast Shear Wave Absolute Vibro-Elastography Using a Matrix Array Transducer.

Real-time ultrasound imaging plays an important role in ultrasound-guided interventions. The 3-D imaging provides more spatial information compared to conventional 2-D frames by considering the volumes of data. One of the main bottlenecks of 3-D imaging is the long data acquisition time, which reduces practicality and can introduce artifacts from unwanted patient or sonographer motion. This article introduces the first shear wave absolute vibro-elastography (S-WAVE) method with real-time volumetric acquisition using a matrix array transducer. In S-WAVE, an external vibration source generates mechanical vibrations inside the tissue. The tissue motion is then estimated and used in solving a wave equation inverse problem to provide the tissue elasticity. A matrix array transducer is used with a Verasonics ultrasound machine and a frame rate of 2000 volumes/s to acquire 100 radio frequency (RF) volumes in 0.05 s. Using plane wave (PW) and compounded diverging wave (CDW) imaging methods, we estimate axial, lateral, and elevational displacements over 3-D volumes. The curl of the displacements is used with local frequency estimation to estimate elasticity in the acquired volumes. Ultrafast acquisition extends substantially the possible S-WAVE excitation frequency range, now up to 800 Hz, enabling new tissue modeling and characterization. The method was validated on three homogeneous liver fibrosis phantoms and on four different inclusions within a heterogeneous phantom. The homogeneous phantom results show less than 8% (PW) and 5% (CDW) difference between the manufacturer values and the corresponding estimated values over a frequency range of 80-800 Hz. The estimated elasticity values for the heterogeneous phantom at 400-Hz excitation frequency show the average errors of 9% (PW) and 6% (CDW) compared to the provided average values by magnetic resonance elastography (MRE). Furthermore, both imaging methods were able to detect the inclusions within the elasticity volumes. An ex vivo study on a bovine liver sample shows less than 11% (PW) and 9% (CDW) difference between the estimated elasticity ranges by the proposed method and the elasticity ranges provided by MRE and acoustic radiation force impulse (ARFI).

3-D Transducer Mounted Shear Wave Absolute Vibro-Elastography: Proof of Concept.

Quantitative tissue stiffness characterization using ultrasound (US) has been shown to improve prostate cancer (PCa) detection in multiple studies. Shear wave absolute vibro-elastography (SWAVE) allows quantitative and volumetric assessment of tissue stiffness using external multifrequency excitation. This article presents a proof of concept of a first-of-a-kind 3-D hand-operated endorectal SWAVE system designed to be used during systematic prostate biopsy. The system is developed with a clinical US machine, requiring only an external exciter that can be mounted directly to the transducer. Subsector acquisition of radio frequency (RF) data allows imaging of shear waves with a high effective frame rate (up to 250 Hz). The system was characterized using eight different quality assurance phantoms. Due to the invasive nature of prostate imaging, at this early stage of development, validation of in vivo human tissue was instead carried out by intercostally scanning the livers of n = 7 healthy volunteers. The results are compared with 3-D magnetic resonance elastography (MRE) and an existing 3-D SWAVE system with a matrix array transducer (M-SWAVE). High correlations were found with MRE (99% in phantoms, 94% in liver data) and with M-SWAVE (99% in phantoms, 98% in liver data).

Towards transcervical ultrasound image guidance for transoral robotic surgery.

PURPOSE: Trans-oral robotic surgery (TORS) using the da Vinci surgical robot is a new minimally-invasive surgery method to treat oropharyngeal tumors, but it is a challenging operation. Augmented reality (AR) based on intra-operative ultrasound (US) has the potential to enhance the visualization of the anatomy and cancerous tumors to provide additional tools for decision-making in surgery. METHODS: We propose a US-guided AR system for TORS, with the transducer placed on the neck for a transcervical view. Firstly, we perform a novel MRI-to-transcervical 3D US registration study, comprising (i) preoperative MRI to preoperative US registration, and (ii) preoperative to intraoperative US registration to account for tissue deformation due to retraction. Secondly, we develop a US-robot calibration method with an optical tracker and demonstrate its use in an AR system that displays anatomy models in the surgeon's console in real-time. RESULTS: Our AR system achieves a projection error from the US to the stereo cameras of 27.14 and 26.03 pixels (image is 540[Formula: see text]960) in a water bath experiment. The average target registration error (TRE) for MRI to 3D US is 8.90 mm for the 3D US transducer and 5.85 mm for freehand 3D US, and the TRE for pre-intra operative US registration is 7.90 mm. CONCLUSION: We demonstrate the feasibility of each component of the first complete pipeline for MRI-US-robot-patient registration for a proof-of-concept transcervical US-guided AR system for TORS. Our results show that trans-cervical 3D US is a promising technique for TORS image guidance.

Real-time intraoperative surgical guidance system in the da Vinci surgical robot based on transrectal ultrasound/photoacoustic imaging with photoacoustic markers: an ex vivo demonstration.

This paper introduces the first integrated real-time intraoperative surgical guidance system, in which an endoscope camera of da Vinci surgical robot and a transrectal ultrasound (TRUS) transducer are co-registered using photoacoustic markers that are detected in both fluorescence (FL) and photoacoustic (PA) imaging. The co-registered system enables the TRUS transducer to track the laser spot illuminated by a pulsed-laser-diode attached to the surgical instrument, providing both FL and PA images of the surgical region-of-interest (ROI). As a result, the generated photoacoustic marker is visualized and localized in the da Vinci endoscopic FL images, and the corresponding tracking can be conducted by rotating the TRUS transducer to display the PA image of the marker. A quantitative evaluation revealed that the average registration and tracking errors were 0.84 mm and 1.16°, respectively. This study shows that the co-registered photoacoustic marker tracking can be effectively deployed intraoperatively using TRUS+PA imaging providing functional guidance of the surgical ROI.

Multi-Frequency 3D Shear Wave Absolute Vibro-Elastography (S-WAVE) System for the Prostate.

This article describes a novel system for quantitative and volumetric measurement of tissue elasticity in the prostate using simultaneous multi-frequency tissue excitation. Elasticity is computed by using a local frequency estimator to measure the three-dimensional local wavelengths of steady-state shear waves within the prostate gland. The shear wave is created using a mechanical voice coil shaker which transmits simultaneous multi-frequency vibrations transperineally. Radio frequency data is streamed directly from a BK Medical 8848 transrectal ultrasound transducer to an external computer where tissue displacement due to the excitation is measured using a speckle tracking algorithm. Bandpass sampling is used that eliminates the need for an ultra-fast frame rate to track the tissue motion and allows for accurate reconstruction at a sampling frequency that is below the Nyquist rate. A roll motor with computer control is used to rotate the transducer and obtain 3D data. Two commercially available phantoms were used to validate both the accuracy of the elasticity measurements as well as the functional feasibility of using the system for in vivo prostate imaging. The phantom measurements were compared with 3D Magnetic Resonance Elastography (MRE), where a high correlation of 96% was achieved. In addition, the system has been used in two separate clinical studies as a method for cancer identification. Qualitative and quantitative results of 11 patients from these clinical studies are presented here. Furthermore, an AUC of 0.87±0.12 was achieved for malignant vs. benign classification using a binary support vector machine classifier trained with data from the latest clinical study with leave one patient out cross-validation.

Multiparametric MRI maps for detection and grading of dominant prostate tumors.

PURPOSE: To develop an image-based technique capable of detection and grading of prostate cancer, which combines features extracted from multiparametric MRI into a single parameter map of cancer probability. MATERIALS AND METHODS: A combination of features extracted from diffusion tensor MRI and dynamic contrast enhanced MRI was used to characterize biopsy samples from 29 patients. Support vector machines were used to separate the cancerous samples from normal biopsy samples and to compute a measure of cancer probability, presented in the form of a cancer colormap. The classification results were compared with the biopsy results and the classifier was tuned to provide the largest area under the receiver operating characteristic (ROC) curve. Based solely on the tuning of the classifier on the biopsy data, cancer colormaps were also created for whole-mount histopathology slices from four radical prostatectomy patients. RESULTS: An area under ROC curve of 0.96 was obtained on the biopsy dataset and was validated by a "leave-one-patient-out" procedure. The proposed measure of cancer probability shows a positive correlation with Gleason score. The cancer colormaps created for the histopathology patients do display the dominant tumors. The colormap accuracy increases with measured tumor area and Gleason score. CONCLUSION: Dynamic contrast enhanced imaging and diffusion tensor imaging, when used within the framework of supervised classification, can play a role in characterizing prostate cancer.

Registration of trans-perineal template mapping biopsy cores to volumetric ultrasound.

PURPOSE: Pathology from trans-perineal template mapping biopsy (TTMB) can be used as labels to train prostate cancer classifiers. In this work, we propose a framework to register TTMB cores to advanced volumetric ultrasound data such as multi-parametric transrectal ultrasound (mpTRUS). METHODS: The framework has mainly two steps. First, needle trajectories are calculated with respect to the needle guiding template-considering deflections in their paths. In standard TTMB, a sparsely sampled ultrasound volume is taken prior to the procedure which contains the template overlaid on top of it. The position of this template is detected automatically, and the cores are mapped following the calculated needle trajectories. Second, the TTMB volume is aligned to the mpTRUS volume by a two-step registration method. Using the same transformations from the registration step, the cores are registered from the TTMB volume to the mpTRUS volume. RESULTS: TTMB and mpTRUS of 10 patients were available for this work. The target registration errors (TRE) of the volumes using landmarks picked by three research assistants (RA) and one radiation oncologist (RO) were on average 1.32 ± 0.7 mm and 1.03 ± 0.6 mm, respectively. Additionally, on average, our framework takes only 97 s to register the cores. CONCLUSION: Our proposed framework allows a quick way to find the spatial location of the cores with respect to volumetric ultrasound. Furthermore, knowing the correct location of the pathology will facilitate focal treatment and will aid in training imaging-based cancer classifiers.

Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis.

PURPOSE: Accurate localization of prostate implants from several C-arm images is necessary for ultrasound-fluoroscopy fusion and intraoperative dosimetry. The authors propose a computational motion compensation method for tomosynthesis-based reconstruction that enables 3D localization of prostate implants from C-arm images despite C-arm oscillation and sagging. METHODS: Five C-arm images are captured by rotating the C-arm around its primary axis, while measuring its rotation angle using a protractor or the C-arm joint encoder. The C-arm images are processed to obtain binary seed-only images from which a volume of interest is reconstructed. The motion compensation algorithm, iteratively, compensates for 2D translational motion of the C-arm by maximizing the number of voxels that project on a seed projection in all of the images. This obviates the need for C-arm full pose tracking traditionally implemented using radio-opaque fiducials or external trackers. The proposed reconstruction method is tested in simulations, in a phantom study and on ten patient data sets. RESULTS: In a phantom implanted with 136 dummy seeds, the seed detection rate was 100% with a localization error of 0.86 ± 0.44 mm (Mean ± STD) compared to CT. For patient data sets, a detection rate of 99.5% was achieved in approximately 1 min per patient. The reconstruction results for patient data sets were compared against an available matching-based reconstruction method and showed relative localization difference of 0.5 ± 0.4 mm. CONCLUSIONS: The motion compensation method can successfully compensate for large C-arm motion without using radio-opaque fiducial or external trackers. Considering the efficacy of the algorithm, its successful reconstruction rate and low computational burden, the algorithm is feasible for clinical use.