Ultrahigh-Resolution K-Edge Imaging of Coronary Arteries With Prototype Deep-Silicon Photon-Counting CT: Initial Results in Phantoms.

Background Photon-counting CT (PCCT) represents a recent advancement in CT, offering improved spatial resolution and spectral separability. By using multiple adjustable energy bins, PCCT enables K-edge imaging, allowing mixed contrast agent distinction. Deep-silicon is a new type of photon-counting detector with different characteristics compared with cadmium photon-counting detectors. Purpose To evaluate the performance of a prototype deep-Si PCCT scanner and compare it with that of a state-of-the-art dual-energy energy-integrating detector (EID) scanner in imaging coronary artery plaques enhanced with iodine and K-edge contrast agents. Materials and Methods A series of 10 three-dimensional-printed inserts (diameter, 3.5 mm) was prepared, and materials mimicking soft and calcified plaques were added to simulate stenosed coronary arteries. Inserts filled with an iodine- or gadolinium-based contrast agent (GBCA) were scanned. Virtual monoenergetic images (VMIs) and iodine maps were generated using two- and eight-energy bin data from EID CT and PCCT, respectively. Gadolinium maps were calculated for PCCT. The CT numbers of VMIs and iodine maps were compared. Spatial resolution and blooming artifacts were compared on the 70-keV VMIs in plaque-free and calcified coronary arteries. Results No evidence of a significant difference in the CT number of 70-keV images was found except in inserts containing GBCAs. In the absence of a GBCA, excellent (r > 0.99) agreement for iodine was found. PCCT could quantify the GBCA within 0.2 mg Gd/mL ± 0.8 accuracy of the ground truth, whereas EID CT failed to detect the GBCA. Lumen measurements were more accurate for PCCT than for EID CT, with mean errors of 167 versus 442 µm (P < .001) compared with the 3.5-mm ground truth. Conclusion Deep-Si PCCT demonstrated good accuracy in iodine quantification and could accurately decompose mixtures of two contrast agents. Its improved spatial resolution resulted in sharper images with blooming artifacts reduced by 50% compared with a state-of-the-art dual-energy EID CT scanner. © RSNA, 2024.

Deep-silicon photon-counting x-ray projection denoising through reinforcement learning.

BACKGROUND: In recent years, deep reinforcement learning (RL) has been applied to various medical tasks and produced encouraging results. OBJECTIVE: In this paper, we demonstrate the feasibility of deep RL for denoising simulated deep-silicon photon-counting CT (PCCT) data in both full and interior scan modes. PCCT offers higher spatial and spectral resolution than conventional CT, requiring advanced denoising methods to suppress noise increase. METHODS: In this work, we apply a dueling double deep Q network (DDDQN) to denoise PCCT data for maximum contrast-to-noise ratio (CNR) and a multi-agent approach to handle data non-stationarity. RESULTS: Using our method, we obtained significant image quality improvement for single-channel scans and consistent improvement for all three channels of multichannel scans. For the single-channel interior scans, the PSNR (dB) and SSIM increased from 33.4078 and 0.9165 to 37.4167 and 0.9790 respectively. For the multichannel interior scans, the channel-wise PSNR (dB) increased from 31.2348, 30.7114, and 30.4667 to 31.6182, 30.9783, and 30.8427 respectively. Similarly, the SSIM improved from 0.9415, 0.9445, and 0.9336 to 0.9504, 0.9493, and 0.0326 respectively. CONCLUSIONS: Our results show that the RL approach improves image quality effectively, efficiently, and consistently across multiple spectral channels and has great potential in clinical applications.

Deep learning-based auto-segmentation of clinical target volumes for radiotherapy treatment of cervical cancer.

OBJECTIVES: Because radiotherapy is indispensible for treating cervical cancer, it is critical to accurately and efficiently delineate the radiation targets. We evaluated a deep learning (DL)-based auto-segmentation algorithm for automatic contouring of clinical target volumes (CTVs) in cervical cancers. METHODS: Computed tomography (CT) datasets from 535 cervical cancers treated with definitive or postoperative radiotherapy were collected. A DL tool based on VB-Net was developed to delineate CTVs of the pelvic lymph drainage area (dCTV1) and parametrial area (dCTV2) in the definitive radiotherapy group. The training/validation/test number is 157/20/23. CTV of the pelvic lymph drainage area (pCTV1) was delineated in the postoperative radiotherapy group. The training/validation/test number is 272/30/33. Dice similarity coefficient (DSC), mean surface distance (MSD), and Hausdorff distance (HD) were used to evaluate the contouring accuracy. Contouring times were recorded for efficiency comparison. RESULTS: The mean DSC, MSD, and HD values for our DL-based tool were 0.88/1.32 mm/21.60 mm for dCTV1, 0.70/2.42 mm/22.44 mm for dCTV2, and 0.86/1.15 mm/20.78 mm for pCTV1. Only minor modifications were needed for 63.5% of auto-segmentations to meet the clinical requirements. The contouring accuracy of the DL-based tool was comparable to that of senior radiation oncologists and was superior to that of junior/intermediate radiation oncologists. Additionally, DL assistance improved the performance of junior radiation oncologists for dCTV2 and pCTV1 contouring (mean DSC increases: 0.20 for dCTV2, 0.03 for pCTV1; mean contouring time decrease: 9.8 min for dCTV2, 28.9 min for pCTV1). CONCLUSIONS: DL-based auto-segmentation improves CTV contouring accuracy, reduces contouring time, and improves clinical efficiency for treating cervical cancer.

Cardiac CT motion artifact grading via semi-automatic labeling and vessel tracking using synthetic image-augmented training data.

Cardiac CT provides critical information for the evaluation of cardiovascular diseases. However, involuntary patient motion and physiological movement of the organs during CT scanning cause motion blur in the reconstructed CT images, degrading both cardiac CT image quality and its diagnostic value. In this paper, we propose and demonstrate an effective and efficient method for CT coronary angiography image quality grading via semi-automatic labeling and vessel tracking. These algorithms produce scores that accord with those of expert readers to within 0.85 points on a 5-point scale. We also train a neural network model to perform fully-automatic motion artifact grading. We demonstrate, using XCAT simulation tools to generate realistic phantom CT data, that supplementing clinical data with synthetic data improves the scoring performance of this network. With respect to ground truth scores assigned by expert operators, the mean square error of grading motion of the right coronary artery is reduced by 36% by synthetic data supplementation. This demonstrates that augmentation of clinical training data with realistically synthesized images can potentially reduce the number of clinical studies needed to train the network.

The effects of intra-detector Compton scatter on low-frequency DQE for photon-counting CT using edge-on-irradiated silicon detectors.

BACKGROUND: Edge-on-irradiated silicon detectors are currently being investigated for use in full-body photon-counting computed tomography (CT) applications. The low atomic number of silicon leads to a significant number of incident photons being Compton scattered in the detector, depositing a part of their energy and potentially being counted multiple times. Even though the physics of Compton scatter is well established, the effects of Compton interactions in the detector on image quality for an edge-on-irradiated silicon detector have still not been thoroughly investigated. PURPOSE: To investigate and explain effects of Compton scatter on low-frequency detective quantum efficiency (DQE) for photon-counting CT using edge-on-irradiated silicon detectors. METHODS: We extend an existing Monte Carlo model of an edge-on-irradiated silicon detector with 60 mm active absorption depth, previously used to evaluate spatial-frequency-based performance, to develop projection and image domain performance metrics for pure density and pure spectral imaging tasks with 30 and 40 cm water backgrounds. We show that the lowest energy threshold of the detector can be used as an effective discriminator of primary counts and cross-talk caused by Compton scatter. We study the developed metrics as functions of the lowest threshold energy for root-mean-square electronic noise levels of 0.8, 1.6, and 3.2 keV, where the intermediate level 1.6 keV corresponds to the noise level previously measured on a single sensor element in isolation. We also compare the performance of a modeled detector with 8, 4, and 2 optimized energy bins to a detector with 1-keV-wide bins. RESULTS: In terms of low-frequency DQE for density imaging, there is a tradeoff between using a threshold low enough to capture Compton interactions and avoiding electronic noise counts. For 30 cm water phantom, 4 energy bins, and a root-mean-square electronic noise of 0.8, 1.6, and 3.2 keV, it is optimal to put the lowest energy threshold at 3, 6, and 1 keV, which gives optimal projection-domain DQEs of 0.64, 0.59, and 0.52, respectively. Low-frequency DQE for spectral imaging also benefits from measuring Compton interactions with respective optimal thresholds of 12, 12, and 13 keV. No large dependence on background thickness was observed. For the intermediate noise level (1.6 keV), increasing the lowest threshold from 5 to 35 keV increases the variance in a iodine basis image by 60%-62% (30 cm phantom) and 67%-69% (40 cm phantom), with 8 bins. Both spectral and density DQE are adversely affected by increasing the electronic noise level. Image-domain DQE exhibits similar qualitative behavior as projection-domain DQE. CONCLUSIONS: Compton interactions contribute significantly to the density imaging performance of edge-on-irradiated silicon detectors. With the studied detector topology, the benefit of counting primary Compton interactions outweighs the penalty of multiple counting at all lowest threshold energies. Compton interactions also contribute significantly to the spectral imaging performance for measured energies above 10 keV.

Hybrid U-Net and Swin-transformer network for limited-angle cardiac computed tomography.

Objective.Cardiac computed tomography (CT) is widely used for diagnosis of cardiovascular disease, the leading cause of morbidity and mortality in the world. Diagnostic performance depends strongly on the temporal resolution of the CT images. To image the beating heart, one can reduce the scanning time by acquiring limited-angle projections. However, this leads to increased image noise and limited-angle-related artifacts. The goal of this paper is to reconstruct high quality cardiac CT images from limited-angle projections.Approach. The ability to reconstruct high quality images from limited-angle projections is highly desirable and remains a major challenge. With the development of deep learning networks, such as U-Net and transformer networks, progresses have been reached on image reconstruction and processing. Here we propose a hybrid model based on the U-Net and Swin-transformer (U-Swin) networks. The U-Net has the potential to restore structural information due to missing projection data and related artifacts, then the Swin-transformer can gather a detailed global feature distribution.Main results. Using synthetic XCAT and clinical cardiac COCA datasets, we demonstrate that our proposed method outperforms the state-of-the-art deep learning-based methods.Significance. It has a great potential to freeze the beating heart with a higher temporal resolution.

Standardizing technical parameters and terms for abdominopelvic photon-counting CT: laying the groundwork for innovation and evidence sharing.

Photon-counting detector CT (PCD-CT) is a new technology that has multiple diagnostic benefits including increased spatial resolution, iodine signal, and radiation dose efficiency, as well as multi-energy imaging capability, but which also has unique challenges in abdominal imaging. The purpose of this work is to summarize key features, technical parameters, and terms, which are common amongst current abdominopelvic PCD-CT systems and to propose standardized terminology (where none exists). In addition, user-selectable protocol parameters are highlighted to facilitate both scientific evaluation and early clinical adoption. Unique features of PCD-CT systems include photon-counting detectors themselves, energy thresholds and bins, and tube potential considerations for preserved spectral separation. Key parameters for describing different PCD-CT systems are reviewed and explained. While PCD-CT can generate multi-energy images like dual-energy CT, there are new types of images such as threshold images, energy bin images, and special spectral images. The standardized terms and concepts herein build upon prior interdisciplinary consensus and have been endorsed by the newly created Society of Abdominal Radiology Photon-counting CT Emerging Technology Commission.

Automation of ultrasonographic optic nerve sheath diameter measurement using convolutional neural networks.

BACKGROUND AND PURPOSE: Ultrasonographic optic nerve sheath (ONS) diameter is a noninvasive intracranial pressure (ICP) surrogate. ICP is monitored invasively in specialized intensive care units. Noninvasive ICP monitoring is important in less specialized settings. However, noninvasive ICP monitoring using ONS diameter (ONSD) is limited by the need for experts to obtain and perform measurements. We aim to automate ONSD measurements using a deep convolutional neural network (CNN) with a novel masking technique. METHODS: We trained a CNN to reproduce masks that mark the ONS. The edges of the mask are defined by an expert. Eight models were trained with 1000 epochs per model. The Dice-similarity-coefficient-weighted averaged outputs of the eight models yielded the final predicted mask. Eight hundred and seventy-three images were obtained from 52 transorbital cine-ultrasonography sessions, performed on 46 patients with brain injuries. Eight hundred and fourteen images from 48 scanning sessions were used for training and validation and 59 images from four sessions for testing. Bland-Altman and Pearson linear correlation analyses were used to evaluate the agreement between CNN and expert measurements. RESULTS: Expert ONSD measurements and CNN-derived ONSD estimates had strong agreement (r = 0.7, p < .0001). The expert mean ONSD (standard deviation) is 5.27 mm (0.43) compared to CNN mean estimate of 5.46 mm (0.37). Mean difference (95% confidence interval, p value) is 0.19 mm (0.10-0.27 mm, p = .0011), and root mean square error is 0.27 mm. CONCLUSION: A CNN can learn ONSD measurement using masking without image segmentation or landmark detection.

Ultra-high-resolution spectral silicon-based photon-counting detector CT for coronary CT angiography: Initial results in a dynamic phantom.

BACKGROUND: Recent improvements in CT detector technology have led to smaller detector pixels resolving frequencies beyond 20 lp/cm and enabled ultra-high-resolution CT. Silicon-based photon-counting detector (PCD) CT is one such technology that promises improved spatial and spectral resolution. However, when the detector pixel sizes are reduced, the impact of cardiac motion on CT images becomes more pronounced. Here, we investigated the effects cardiac motion on the image quality of a clinical prototype Si-PCD scanner in a dynamic heart phantom. METHODS: A series of 3D-printed vessels were created to simulate coronary arteries with diameter in the 1-3.5 â€‹mm range. Four coronary stents were set inside the d â€‹= â€‹3.5 â€‹mm vessels and all vessels were filled with contrast agents and were placed inside a dynamic cardiac phantom. The phantom was scanned in motion (60 bpm) and at rest on a prototype clinical Si-PCD CT scanner in 8-bin spectral UHR mode. Virtual monoenergetic images (VMI) were generated at 70 â€‹keV and CT number accuracy and effective spatial resolution (blooming) of rest and motion VMIs were compared. RESULTS: Linear regression analysis of CT numbers showed excellent agreement (r â€‹> â€‹0.99) between rest and motion. We did not observe a significant difference (p â€‹> â€‹0.48) in estimating free lumen diameters. Differences in in-stent lumen diameter and stent strut thickness were non-significant with maximum mean difference of approximately 70 â€‹µm. CONCLUSION: We found no significant degradation in CT number accuracy or spatial resolution due to cardiac motion. The results demonstrate the potential of spectral UHR coronary CT angiography enabled by Si-PCD.

Development of metaverse for intelligent healthcare.

The metaverse integrates physical and virtual realities, enabling humans and their avatars to interact in an environment supported by technologies such as high-speed internet, virtual reality, augmented reality, mixed and extended reality, blockchain, digital twins and artificial intelligence (AI), all enriched by effectively unlimited data. The metaverse recently emerged as social media and entertainment platforms, but extension to healthcare could have a profound impact on clinical practice and human health. As a group of academic, industrial, clinical and regulatory researchers, we identify unique opportunities for metaverse approaches in the healthcare domain. A metaverse of 'medical technology and AI' (MeTAI) can facilitate the development, prototyping, evaluation, regulation, translation and refinement of AI-based medical practice, especially medical imaging-guided diagnosis and therapy. Here, we present metaverse use cases, including virtual comparative scanning, raw data sharing, augmented regulatory science and metaversed medical intervention. We discuss relevant issues on the ecosystem of the MeTAI metaverse including privacy, security and disparity. We also identify specific action items for coordinated efforts to build the MeTAI metaverse for improved healthcare quality, accessibility, cost-effectiveness and patient satisfaction.

Image quality improvement in megavoltage cone beam CT using an imaging beam line and a sintered pixelated array system.

PURPOSE: To quantify the improvement in megavoltage cone beam computed tomography (MVCBCT) image quality enabled by the combination of a 4.2 MV imaging beam line (IBL) with a carbon electron target and a detector system equipped with a novel sintered pixelated array (SPA) of translucent Gd(2)O(2)S ceramic scintillator. Clinical MVCBCT images are traditionally acquired with the same 6 MV treatment beam line (TBL) that is used for cancer treatment, a standard amorphous Si (a-Si) flat panel imager, and the Kodak Lanex Fast-B (LFB) scintillator. The IBL produces a greater fluence of keV-range photons than the TBL, to which the detector response is more optimal, and the SPA is a more efficient scintillator than the LFB. METHODS: A prototype IBL + SPA system was installed on a Siemens Oncor linear accelerator equipped with the MVision(TM) image guided radiation therapy (IGRT) system. A SPA strip consisting of four neighboring tiles and measuring 40 cm by 10.96 cm in the crossplane and inplane directions, respectively, was installed in the flat panel imager. Head- and pelvis-sized phantom images were acquired at doses ranging from 3 to 60 cGy with three MVCBCT configurations: TBL + LFB, IBL + LFB, and IBL + SPA. Phantom image quality at each dose was quantified using the contrast-to-noise ratio (CNR) and modulation transfer function (MTF) metrics. Head and neck, thoracic, and pelvic (prostate) cancer patients were imaged with the three imaging system configurations at multiple doses ranging from 3 to 15 cGy. The systems were assessed qualitatively from the patient image data. RESULTS: For head and neck and pelvis-sized phantom images, imaging doses of 3 cGy or greater, and relative electron densities of 1.09 and 1.48, the CNR average improvement factors for imaging system change of TBL + LFB to IBL + LFB, IBL + LFB to IBL + SPA, and TBL + LFB to IBL + SPA were 1.63 (p < 10(- 8)), 1.64 (p < 10(- 13)), 2.66 (p < 10(- 9)), respectively. For all imaging doses, soft tissue contrast was more easily differentiated on IBL + SPA head and neck and pelvic images than TBL + LFB and IBL + LFB. IBL + SPA thoracic images were comparable to IBL + LFB images, but less noisy than TBL + LFB images at all imaging doses considered. The mean MTFs over all imaging doses were comparable, at within 3%, for all imaging system configurations for both the head- and pelvis-sized phantoms. CONCLUSIONS: Since CNR scales with the square root of imaging dose, changing from TBL + LFB to IBL + LFB and IBL + LFB to IBL + SPA reduces the imaging dose required to obtain a given CNR by factors of 0.38 and 0.37, respectively. MTFs were comparable between imaging system configurations. IBL + SPA patient image quality was always better than that of the TBL + LFB system and as good as or better than that of the IBL + LFB system, for a given dose.

Fixed gantry tomosynthesis system for radiation therapy image guidance based on a multiple source x-ray tube with carbon nanotube cathodes.

The authors present the design and simulation of an imaging system that employs a compact multiple source x-ray tube to produce a tomosynthesis image from a set of projections obtained at a single tube position. The electron sources within the tube are realized using cold cathode carbon nanotube technology. The primary intended application is tomosynthesis-based 3D image guidance during external beam radiation therapy. The tube, which is attached to the gantry of a medical linear accelerator (linac) immediately below the multileaf collimator, operates within the voltage range of 80-160 kVp and contains a total of 52 sources that are arranged in a rectilinear array. This configuration allows for the acquisition of tomographic projections from multiple angles without any need to rotate the linac gantry. The x-ray images are captured by the same amorphous silicon flat panel detector employed for portal imaging on contemporary linacs. The field of view (FOV) of the system corresponds to that part of the volume that is sampled by rays from all sources. The present tube and detector configuration provides an 8 x 8 cm2 FOV in the plane of the linac isocenter when the 40.96 x 40.96 cm2 imaging detector is placed 40 cm from the isocenter. Since this tomosynthesis application utilizes the extremities of the detector to record image detail relating to structures near the isocenter, simultaneous treatment and imaging is possible for most clinical cases, where the treated target is a small region close to the linac isocenter. The tomosynthesis images are reconstructed using the simultaneous iterative reconstruction technique, which is accelerated using a graphic processing unit. The authors present details of the system design as well as simulated performance of the imaging system based on reprojections of patient CT images.

Automatic coregistration of volumetric images based on implanted fiducial markers.

The accurate delivery of external beam radiation therapy is often facilitated through the implantation of radio-opaque fiducial markers (gold seeds). Before the delivery of each treatment fraction, seed positions can be determined via low dose volumetric imaging. By registering these seed locations with the corresponding locations in the previously acquired treatment planning computed tomographic (CT) scan, it is possible to adjust the patient position so that seed displacement is accommodated. The authors present an unsupervised automatic algorithm that identifies seeds in both planning and pretreatment images and subsequently determines a rigid geometric transformation between the two sets. The algorithm is applied to the imaging series of ten prostate cancer patients. Each test series is comprised of a single multislice planning CT and multiple megavoltage conebeam (MVCB) images. Each MVCB dataset is obtained immediately prior to a subsequent treatment session. Seed locations were determined to within 1 mm with an accuracy of 97 +/- 6.1% for datasets obtained by application of a mean imaging dose of 3.5 cGy per study. False positives occurred in three separate instances, but only when datasets were obtained at imaging doses too low to enable fiducial resolution by a human operator, or when the prostate gland had undergone large displacement or significant deformation. The registration procedure requires under nine seconds of computation time on a typical contemporary computer workstation.

Focused beam-stop array for the measurement of scatter in megavoltage portal and cone beam CT imaging.

We describe a focused beam-stop array (BSA) for the measurement of object scatter in imaging systems that utilize x-ray beams in the megavoltage (MV) energy range. The BSA consists of 64 doubly truncated tungsten cone elements of 0.5 cm maximum diameter that are arranged in a regular array on an acrylic slab. The BSA is placed in the accessory tray of a medical linear accelerator at a distance of approximately 50 cm from the focal spot. We derive an expression that allows us to estimate the scatter in an image taken without the array present, given image values in a second image with the array in place. The presence of the array reduces fluence incident on the imaged object. This leads to an object-dependent underestimation bias in the scatter measurements. We apply corrections in order to address this issue. We compare estimates of the flat panel detector response to scatter obtained using the BSA to those derived from Monte Carlo simulations. We find that the two estimates agree to within 10% in terms of RMS error for 30 cm x 30 cm water slabs in the thickness range of 10-30 cm. Larger errors in the scatter estimates are encountered for thinner objects, probably owing to extrafocal radiation sources. However, RMS errors in the estimates of primary images are no more than 5% for water slab thicknesses in the range of 1-30 cm. The BSA scatter estimates are also used to correct cone beam tomographic projections. Maximum deviations of central profiles of uniform water phantoms are reduced from 193 to 19 HU after application of corrections for scatter, beam hardening, and lateral truncation that are based on the BSA-derived scatter estimate. The same corrections remove the typical cupping artifact from both phantom and patient images. The BSA proves to be a useful tool for quantifying and removing image scatter, as well as for validating models of MV imaging systems.

Evaluation of arterial endothelial function using transit times of artificially induced pulses.

Impairment of arterial endothelial function is an early event in atherosclerosis and correlates with the major risk factors for cardiovascular disease. The most widely employed non-invasive measure of endothelial function involves brachial artery (BA) diameter measurement using ultrasound imaging before and after several minutes of blood flow occlusion. The change in arterial diameter is a measure of flow-mediated vasorelaxation (FMVR). The high between-laboratory variability of results and cost of instrumentation render this technique unsuitable for routine clinical use. We induce artificial pulses at the superficial radial artery using a linear actuator. An ultrasonic Doppler stethoscope detects these pulses 10-30 cm proximal to the point of pulse induction. The delay between pulse application and detection provides the pulse transit time (PTT). By measuring PTT before and after 5 min of BA occlusion and ensuing reactive hyperemia, FMVR may be measured based on the changes in PTT caused by changes in vessel caliber, smooth muscle tone and wall thickness. We (1) validate the sensitivity of this technique to arterial wall tone using sublingual nitroglycerin and (2) compare measurements of endothelial function to ultrasound BA diameter measurements in 12 human subjects. The PTT-based method is verified to measure arterial wall tone and is shown to provide 37% greater sensitivity (p < 0.05) to FMVR than BA diameter measurements. By measuring the change in pulse transit time before and after endothelial stimulus, a sensitive, reproducible and convenient measure of endothelial function may be obtained at a low cost.

Measurement of brachial artery endothelial function using a standard blood pressure cuff.

The integrity of endothelial function in major arteries (EFMA) is a powerful independent predictor of heart attack and stroke. Existing ultrasound-based non-invasive assessment methods are technically challenging and suitable only for laboratory settings. EFMA, like blood pressure (BP), is both acutely and chronically affected by factors such as lifestyle and medication. Consequently, laboratory-based measurements cannot fully gauge the effects of medical interventions on EFMA. EFMA and BP have, arguably, comparable (but complementary) value in the assessment of cardiovascular health. Widespread deployment of EFMA assessment is thus a desirable clinical goal. To this end, we propose a device based on modifying the measurement protocol of a standard electronic sphygmomanometer. The protocol involves inflating the cuff to sub-diastolic levels to enable recording of the pulse waveform before and after vasodilatory stimulus. The mechanical unloading of the arterial wall provided by the cuff amplifies the distension that occurs with each pulse, which is measured as a pressure variation in the cuff. We show that the height of the rising edge of each pulse is proportional to the change in lumen area between diastole and systole. This allows the effect of vasodilatory stimuli on the artery to be measured with high sensitivity. We compare the proposed cuff flow-mediated dilation (cFMD) method to ultrasound flow-mediated dilation (uFMD). We find significant correlation (r = 0.55, p = 0.003, N = 27) between cFMD- and uFMD-based metrics obtained when the release of a 5 min cuff occlusion is employed to induce endothelial stimulus via reactive hyperemia. cFMD is approximately proportional to the square of uFMD, representing a typical increase in sensitivity to vasodilation of 300-600%. This study illustrates the potential for an individual to conveniently measure his/her EFMA by using a low-cost reprogrammed home sphygmomanometer.

Enhanced cutaneous vascular response in AD subjects under donepezil therapy.

OBJECTIVE: Abnormal cutaneous vasodilatory responses to the iontophoresis of vasodilators were previously observed in Alzheimer's disease (AD). We sought to replicate these observations and further identify peripheral vascular components of AD pathology. METHODS: Methacholine chloride (MCh), acetylcholine chloride (ACh), and sodium nitroprusside (SNP) were applied iontophoretically to forearm skin. Laser Doppler imaging of treated areas yielded total perfusion response values. RESULTS: Response to MCh was enhanced 78% ( P=0.003 ) in AD subjects under therapy with the acetylcholinesterase inhibitor (AChEI) donepezil ( N=9 ), relative to age- and sex-matched controls ( N=12 ). Significant increases in perfusion were also observed after application of ACh (68%, P=0.03 ) and SNP (46%, P=0.04 ). CONCLUSIONS: A previous study reported attenuated response to ACh in AD. Paradoxically, we observed a substantially enhanced response that is likely a consequence of donepezil therapy. The increased response to the endothelium-independent vasodilator SNP indicates improved general vasodilatory response, perhaps due to preservation of endogenous ACh by donepezil. Cerebral perfusion in response to functional activation may be improved in this way, suggesting a secondary therapeutic mode of donepezil.

Parsimonious basis selection in exponential spectral analysis.

Sums of decaying real exponentials (SDREs) are frequently used in models of time-varying processes. First-order compartmental models are widely employed to describe mass transit in chemical and biological systems. In these models the evolution of compartment concentration versus time is represented as the convolution of an input function with an SDRE. In exponential spectral analysis (ESA) the nonlinear problem of estimating the SDRE rate constants is replaced by the linear estimation of the coefficients of a preselected set of exponential basis functions (EBFs). This work addresses the problem of selecting the number of EBFs and the rate constant of each basis element. Basis dimension is established via model selection, in which approximation error and parameter redundancy are the criteria. The latter is estimated via simulation of the fitted model over multiple noise realizations. A constrained Cramér-Rao lower bound is derived for ESA parameters. The resulting parsimonious ESA algorithm (PESA) ameliorates the inherent problem of non-uniqueness in ESA parameters. Consequently, sets of time series may be compared in a statistically meaningfully way in terms of physically or physiologically significant parameters. PESA is applied to compare the retention of two radiotracers in the artificially perfused rabbit heart.

Dynamic single photon emission computed tomography--basic principles and cardiac applications.

The very nature of nuclear medicine, the visual representation of injected radiopharmaceuticals, implies imaging of dynamic processes such as the uptake and wash-out of radiotracers from body organs. For years, nuclear medicine has been touted as the modality of choice for evaluating function in health and disease. This evaluation is greatly enhanced using single photon emission computed tomography (SPECT), which permits three-dimensional (3D) visualization of tracer distributions in the body. However, to fully realize the potential of the technique requires the imaging of in vivo dynamic processes of flow and metabolism. Tissue motion and deformation must also be addressed. Absolute quantification of these dynamic processes in the body has the potential to improve diagnosis. This paper presents a review of advancements toward the realization of the potential of dynamic SPECT imaging and a brief history of the development of the instrumentation. A major portion of the paper is devoted to the review of special data processing methods that have been developed for extracting kinetics from dynamic cardiac SPECT data acquired using rotating detector heads that move as radiopharmaceuticals exchange between biological compartments. Recent developments in multi-resolution spatiotemporal methods enable one to estimate kinetic parameters of compartment models of dynamic processes using data acquired from a single camera head with slow gantry rotation. The estimation of kinetic parameters directly from projection measurements improves bias and variance over the conventional method of first reconstructing 3D dynamic images, generating time-activity curves from selected regions of interest and then estimating the kinetic parameters from the generated time-activity curves. Although the potential applications of SPECT for imaging dynamic processes have not been fully realized in the clinic, it is hoped that this review illuminates the potential of SPECT for dynamic imaging, especially in light of new developments that enable measurement of dynamic processes directly from projection measurements.

Algorithm for X-ray scatter, beam-hardening, and beam profile correction in diagnostic (kilovoltage) and treatment (megavoltage) cone beam CT.

Quantitative reconstruction of cone beam X-ray computed tomography (CT) datasets requires accurate modeling of scatter, beam-hardening, beam profile, and detector response. Typically, commercial imaging systems use fast empirical corrections that are designed to reduce visible artifacts due to incomplete modeling of the image formation process. In contrast, Monte Carlo (MC) methods are much more accurate but are relatively slow. Scatter kernel superposition (SKS) methods offer a balance between accuracy and computational practicality. We show how a single SKS algorithm can be employed to correct both kilovoltage (kV) energy (diagnostic) and megavoltage (MV) energy (treatment) X-ray images. Using MC models of kV and MV imaging systems, we map intensities recorded on an amorphous silicon flat panel detector to water-equivalent thicknesses (WETs). Scattergrams are derived from acquired projection images using scatter kernels indexed by the local WET values and are then iteratively refined using a scatter magnitude bounding scheme that allows the algorithm to accommodate the very high scatter-to-primary ratios encountered in kV imaging. The algorithm recovers radiological thicknesses to within 9% of the true value at both kV and megavolt energies. Nonuniformity in CT reconstructions of homogeneous phantoms is reduced by an average of 76% over a wide range of beam energies and phantom geometries.