Sreeram Narayanan

An on-line replanning scheme for interfractional variations.

Ability of online adaptive replanning is desirable to correct for interfraction anatomic changes. A full-scope replanning/reoptimization with the current planning techniques takes too long to be practical. A novel online replanning strategy to correct for interfraction anatomic changes in real time is presented. The scheme consists of three steps: (1) rapidly delineating targets and organs at risk on the computed tomography of the day by modifying original planning contours using robust tools in a semiautomatic manner, (2) online segment aperture morphing (SAM) (adjusting beam/segment apertures) by applying the spatial relationship between the planning target contour and the apertures to the new target contour, and (3) performing segment weight optimization (SWO) for the new apertures if necessary. The entire scheme was tested for direct-aperture-based IMRT on representative prostate and abdomen cases. Dose volume histograms obtained with the online scheme are practically equivalent to those obtained with full-scope reoptimization. For the days of small to moderate organ deformations, only the SAM is necessary, while for the large deformation days, both SAM and SWO are required to adequately account for the deformation. Both the SAM and SWO programs can be completed within 1 min, and the overall process can be completed within 10 min. The proposed SAM-SWO scheme is practically comparable to full-scope reoptimization, but is fast enough to be implemented for on-line adaptive replanning, enabling dose-guided RT.

Fast cross-projection algorithm for reconstruction of seeds in prostate brachytherapy

A fast method of seed matching and reconstruction in prostate brachytherapy is proposed. Previous approaches have required all seeds to be matched with all other seeds in other projections. The fast cross-projection algorithm for the reconstruction of seeds (Fast-CARS) allows for matching of a given seed with a subset of seeds in other projections. This subset lies in a proximal region centered about the projection of a line, connecting the seed to its source, onto other projection planes. The proposed technique permits a significant reduction in computational overhead, as measured by the required number of matching tests. The number of multiplications and additions is also vastly reduced at no trade-off in accuracy. Because of its speed, Fast-CARS can be used in applications requiring real-time performance such as intraoperative dosimetry of prostate brachytherapy. Furthermore, the proposed method makes practical the use of a larger number of views as opposed to previous techniques limited to a maximum use of three views.

Three-dimensional seed reconstruction from an incomplete data set for prostate brachytherapy

Intra-operative dosimetry in prostate brachytherapy requires 3D coordinates of the implanted, radioactive seeds. Since CT is not readily available during the implant operation, projection x-rays are commonly used for intra-operative seed localization. Three x-ray projections are usually used. The requirement of the current seed reconstruction algorithms is that the seeds must be identified on all three projections. However, in practice this is often difficult to accomplish due to the problem of heavily clustered and overlapping seeds. We have developed an algorithm that permits seed reconstruction from an incomplete data set. Instead of all three projections, the new algorithm requires only one of the three projections to be complete. Furthermore, even if all three projections are incomplete, it can reconstruct 100% of the implanted seeds depending on how the undetected seeds are distributed among the projections. The method utilizes the principles of epipolar imaging geometry and pseudo-matching of the undetected seeds. The algorithm was successfully applied to a large number of clinical cases where seeds imperceptibly overlap in some projections.

Three-dimensional seed reconstruction for prostate brachytherapy using Hough trajectories.

In order to perform intra-operative or post-implant dosimetry in prostate brachytherapy, the 3D coordinates of the implanted radioactive seeds must be determined. Film or fluoroscopy based seed reconstruction techniques use back projection of x-ray data obtained at two or three x-ray positions. These methods, however, do not perform well when some of the seed images are undetected. To overcome this problem we have developed an alternate technique for 3D seed localization using the principle of Hough transform. The Hough method utilizes the fact that, for each seed coordinate in three dimensions, there exists a unique trajectory in Hough feature space. In this paper we present the Hough transform parametric equations to describe the path of the seed projections from one view to the next and a method to reconstruct the 3D seed coordinates. The results of simulation and phantom studies indicate that the Hough trajectory method can accurately determine the 3D seed positions even from an incomplete dataset.

Seed-based transrectal ultrasound-fluoroscopy registration method for intraoperative dosimetry analysis of prostate brachytherapy

Prostate brachytherapy is an effective treatment option for early-stage prostate cancer. During a prostate brachytherapy procedure, transrectal ultrasound (TRUS) and fluoroscopy imaging modalities complement each other by providing good visualization of soft tissue and implanted seeds, respectively. Therefore, the registration of these two imaging modalities, which are readily available in the operating room, could facilitate intraoperative dosimetry, thus enabling physicians to implant additional seeds into the underdosed portions of the prostate while the patient is still on the operating table. It is desirable to register TRUS and fluoroscopy images by using the seeds as fiducial markers. Although the locations of all the implanted seeds can be reconstructed from three fluoroscopy images, only a fraction of these seeds can be located in TRUS images. It is challenging to register the TRUS and fluoroscopy images by using the identified seeds, since the correspondence between them is unknown. Furthermore, misdetection of nonseed structures as seeds can lead to the inclusion of spurious points in the data set. We developed a new method called iterative optimal assignment (IOA) to overcome these challenges in TRUS-fluoroscopy registration. By using the Hungarian method in an optimization framework, IOA computes a set of transformation parameters that yield the one-to-one correspondence with minimum cost. We have evaluated our registration method at varying noise levels, seed detection rates, and number of spurious points using data collected from 25 patients. We have found that IOA can perform registration with an average root mean square error of about 0.2 cm even when the seed detection rate is only 10%. We believe that IOA can offer a robust solution to seed-based TRUS-fluoroscopy registration, thus making intraoperative dosimetry possible.

Seed-based ultrasound and fluoroscopy registration using iterative optimal assignment for intraoperative prostate brachytherapy dosimetry

Prostate brachytherapy involves permanent implantation of radioactive sources into the prostate gland. Since fluoroscopy and transrectal ultrasound (TRUS) imaging modalities currently complement each other by providing good visualization of seeds and soft tissue, respectively, the registration of these two imaging modalities could lead to the intraoperative dosimetry analysis of brachytherapy procedures, thus improving patient outcome and reducing costs. Although it is desirable to register TRUS and fluoroscopy images by using the implanted seeds as fiducial markers, an operator, based on our experience, can locate only a small fraction of implanted seeds in axial TRUS images. Therefore, to perform TRUS-fluoroscopy registration in a clinical setting, there is a need for (1) a new method that can reliably perform registration at low seed detection rates and (2) a new imaging technique to enhance the seed visibility. We previously developed iterative optimal assignment (IOA), which can perform registration at seed detection rates below 20%, to address the former. In this paper, we present a new TRUS acquisition method where we acquire images of the prostate by rotating the longitudinal transducer of a biplanar probe in the clockwise/counter-clockwise direction. We acquired post-implant fluoroscopy and TRUS images from 35 patients who underwent a seed implant procedure. The results show that the combined use of IOA and rotational images makes TRUS-fluoroscopy registration possible and practical, thus our goal of intraoperative dosimetry can be realized.

Detection and correction of patient movement in prostate brachytherapy seed reconstruction

Intraoperative dosimetry of prostate brachytherapy can help optimize the dose distribution and potentially improve clinical outcome. Evaluation of dose distribution during the seed implant procedure requires the knowledge of 3D seed coordinates. Fluoroscopy-based seed localization is a viable option. From three x-ray projections obtained at different gantry angles, 3D seed positions can be determined. However, when local anaesthesia is used for prostate brachytherapy, the patient movement during fluoroscopy image capture becomes a practical problem. If uncorrected, the errors introduced by patient motion between image captures would cause seed mismatches. Subsequently, the seed reconstruction algorithm would either fail to reconstruct or yield erroneous results. We have developed an algorithm that permits detection and correction of patient movement that may occur between fluoroscopy image captures. The patient movement is decomposed into translational shifts along the tabletop and rotation about an axis perpendicular to the tabletop. The property of spatial invariance of the co-planar imaging geometry is used for lateral movement correction. Cranio-caudal movement is corrected by analysing the perspective invariance along the x-ray axis. Rotation is estimated by an iterative method. The method can detect and correct for the range of patient movement commonly seen in the clinical environment. The algorithm has been implemented for routine clinical use as the preprocessing step for seed reconstruction.

Interpolation of discrete periodic nonuniform decimation using alias unraveling

We consider the problem of signal restoration when P of every N samples in a discrete time system are uniformly decimated. The degraded signal is an aliased form of the original signal. The aliasing can, in certain cases, be unraveled by application of multiplicative discrete time trigonometric polynomials followed by filtering. The filter output is the restored discrete time signal. Conditions required for this restoration are presented. The condition - and thus the noise sensitivity - of the restoration process is also analyzed.

A perspective matrix-based seed reconstruction algorithm with applications to C-arm based intra-operative dosimetry

Currently available seed reconstruction algorithms are based on the assumption that accurate information about the imaging geometry is known. The assumption is valid for isocentric x-ray units such as radiotherapy simulators. However, the large majority of the clinics performing prostate brachytherapy today use C-arms for which imaging parameters such as source to axis distance, image acquisition angles, central axis of the image are not accurately known. We propose a seed reconstruction algorithm that requires no such knowledge of geometry. The new algorithm makes use of perspective projection matrix, which can be easily derived from a set of known reference points. The perspective matrix calculates the transformation of a point in 3D space to the imaging coordinate system. An accurate representation of the imaging geometry can be derived from the generalized projection matrix (GPM) with eleven degrees of freedom. In this paper we show how GPM can be derived given a theoretical minimum number of reference points. We propose an algorithm to compute the line equation that defines the backprojection operation given the GPM. The algorithm can be extended to any ray-tracing based seed reconstruction algorithms. Reconstruction using the GPM does not require calibration of C-arms and the images can be acquired at arbitrary angles. The reconstruction is performed in near real-time. Our simulations show that reconstruction using GPM is robust and accuracy is independent of the source to detector distance and location of the reference points used to generate the GPM. Seed reconstruction from C-arm images acquired at unknown geometry provides a useful tool for intra-operative dosimetry in prostate brachytherapy.

Privacy enhanced group communication in clinical environment

Privacy protection of medical records has always been an important issue and is mandated by the recent Health Insurance Portability and Accountability Act (HIPAA) standards. In this paper, we propose security architectures for a tele-referring system that allows electronic group communication among professionals for better quality treatments, while protecting patient privacy against unauthorized access. Although DICOM defines the much-needed guidelines for confidentiality of medical data during transmission, there is no provision in the existing medical security systems to guarantee patient privacy once the data has been received. In our design, we address this issue by enabling tracing back to the recipient whose received data is disclosed to outsiders, using watermarking technique. We present security architecture design of a tele-referring system using a distributed approach and a centralized web-based approach. The resulting tele-referring system (i) provides confidentiality during the transmission and ensures integrity and authenticity of the received data, (ii) allows tracing of the recipient who has either distributed the data to outsiders or whose system has been compromised, (iii) provides proof of receipt or origin, and (iv) can be easy to use and low-cost to employ in clinical environment.