INTERRELATION BETWEEN PREOPERATIVE TESTS, INTRAOPERATIVE FINDINGS AND OUTCOMES OF 99M-TECHNETIUM-SESTAMIBI SCAN IN PRIMARY HYPERPARATHYROIDISM.

Context: Primary hyperparathyroidism is one of the most common endocrinological disorder and surgery of parathyroid glands is the main therapy of this disease. Minimally invasive surgery is getting more prominent in these days and its success in parathyroid surgery mostly depends on accuracy of the localization studies. Objective: The aim of this study is to understand the relationship between preoperative biochemical tests, intraoperative findings and Technetium-99m-methoxyisobutylisonitrile (MIBI) scan results. Design: Retrospective clinical study. Subjects and Methods: A total of 185 patients, who have been diagnosed with primary hyperparathyroidism (PHPT) and operated between January, 2010 and October, 2018, were included to the study. Patients with less than 6 months of follow up are excluded from the study. Results: Patients were divided into two groups according to their scintigraphy results; with positive scintigraphy findings as group 1 (n:135) and negative scintigraphy findings as group 2 (n:50). Mean preoperative serum parathyroid hormone (PTH) values were significantly different between the two groups (p<0.02). Mean preoperative serum calcium, creatinine, magnesium, phosphorus, alkaline phosphatase, 25-OH Vitamin D3 levels of both groups were analyzed and there were no statistical differences between the two groups considering these parameters. Also, mean diameter and mean volume of parathyroid adenomas were significantly higher in group 1 (2.1±1.0 cm vs. 1.55±0.72 cm, respectively, p<0.0001; 2.66±5.35 cm3 vs. 1±1.9 cm3, respectively, p<0.0001). Optimal cut-off values of parathyroid adenoma diameter for MIBI scan positivity were 1.55 cm, parathyroid volume for MIBI scan positivity were 0.48 cm3, preoperative serum PTH for MIBI scan positivity were 124.5 ng/L. Conclusions: Preoperative serum PTH levels, diameter and volume of adenomas might be helpful for the prediction of MIBI scan accuracy and possible need of another localization studies.

Multi-perspective region-based CNNs for vertebrae labeling in intraoperative long-length images.

PURPOSE: Effective aggregation of intraoperative x-ray images that capture the patient anatomy from multiple view-angles has the potential to enable and improve automated image analysis that can be readily performed during surgery. We present multi-perspective region-based neural networks that leverage knowledge of the imaging geometry for automatic vertebrae labeling in Long-Film images - a novel tomographic imaging modality with an extended field-of-view for spine imaging. METHOD: A multi-perspective network architecture was designed to exploit small view-angle disparities produced by a multi-slot collimator and consolidate information from overlapping image regions. A second network incorporates large view-angle disparities to jointly perform labeling on images from multiple views (viz., AP and lateral). A recurrent module incorporates contextual information and enforce anatomical order for the detected vertebrae. The three modules are combined to form the multi-view multi-slot (MVMS) network for labeling vertebrae using images from all available perspectives. The network was trained on images synthesized from 297 CT images and tested on 50 AP and 50 lateral Long-Film images acquired from 13 cadaveric specimens. Labeling performance of the multi-perspective networks was evaluated with respect to the number of vertebrae appearances and presence of surgical instrumentation. RESULTS: The MVMS network achieved an F1 score of >96% and an average vertebral localization error of 3.3 mm, with 88.3% labeling accuracy on both AP and lateral images - (15.5% and 35.0% higher than conventional Faster R-CNN on AP and lateral views, respectively). Aggregation of multiple appearances of the same vertebra using the multi-slot network significantly improved the labeling accuracy (p < 0.05). Using the multi-view network, labeling accuracy on the more challenging lateral views was improved to the same level as that of the AP views. The approach demonstrated robustness to the presence of surgical instrumentation, commonly encountered in intraoperative images, and achieved comparable performance in images with and without instrumentation (88.9% vs. 91.2% labeling accuracy). CONCLUSION: The MVMS network demonstrated effective multi-perspective aggregation, providing means for accurate, automated vertebrae labeling during spine surgery. The algorithms may be generalized to other imaging tasks and modalities that involve multiple views with view-angle disparities (e.g., bi-plane radiography). Predicted labels can help avoid adverse events during surgery (e.g., wrong-level surgery), establish correspondence with labels in preoperative modalities to facilitate image registration, and enable automated measurement of spinal alignment metrics for intraoperative assessment of spinal curvature.

The effect of strap muscle transection on voice and swallowing changes after thyroidectomy in patients without laryngeal nerve injury.

INTRODUCTION: Voice and swallowing symptoms are frequently reported after thyroidectomy even without laryngeal nerve injury. We aimed to evaluate the effect of strap muscle transection on voice and swallowing outcome after thyroidectomy. METHODS: Group 1 (G1) consisted of 17 patients who had their strap muscles transected during thyroidectomy and group 2 (G2) consisted of 17 patients who had their strap muscles preserved during thyroidectomy. None of the patients had laryngeal nerve injury. Voice impairment scores (VIS) and swallowing impairment scores (SIS) were obtained preoperatively and at 1 week and 1, 3 and 6 months postoperatively. Pre- and postoperative vocal cord examinations were performed for all patients. The external branch of the superior laryngeal nerve (EBSLN) was evaluated by intraoperative cricothyroid muscle electromyography. RESULTS: There was no significant difference in VIS and SIS between the two groups. At postoperative week 1, the VIS and SIS for each group were above preoperative values (G1: p = 0.005 and p = 0.035; G2: p = 0.031, p = 0.346, for VIS and SIS respectively). The VIS and SIS scores at 6 months postoperatively were significantly lower than those of the first week postoperatively (G1: p = 0.04 and p = 0.001; G2: p = 0.022 and p = 0.034 respectively) and similar to preoperative values (G1: p = 0.924 and p = 0.086; G2: p = 0.822 and p = 0.187 respectively). CONCLUSION: Although voice and swallowing complaints increased in the early postoperative period even without recurrent laryngeal nerve and EBSLN injuries, these symptoms are not related with the strap muscle transection.

3D vertebrae labeling in spine CT: an accurate, memory-efficient (Ortho2D) framework.

Purpose.Accurate localization and labeling of vertebrae in computed tomography (CT) is an important step toward more quantitative, automated diagnostic analysis and surgical planning. In this paper, we present a framework (called Ortho2D) for vertebral labeling in CT in a manner that is accurate and memory-efficient.Methods. Ortho2D uses two independent faster R-convolutional neural network networks to detect and classify vertebrae in orthogonal (sagittal and coronal) CT slices. The 2D detections are clustered in 3D to localize vertebrae centroids in the volumetric CT and classify the region (cervical, thoracic, lumbar, or sacral) and vertebral level. A post-process sorting method incorporates the confidence in network output to refine classifications and reduce outliers. Ortho2D was evaluated on a publicly available dataset containing 302 normal and pathological spine CT images with and without surgical instrumentation. Labeling accuracy and memory requirements were assessed in comparison to other recently reported methods. The memory efficiency of Ortho2D permitted extension to high-resolution CT to investigate the potential for further boosts to labeling performance.Results. Ortho2D achieved overall vertebrae detection accuracy of 97.1%, region identification accuracy of 94.3%, and individual vertebral level identification accuracy of 91.0%. The framework achieved 95.8% and 83.6% level identification accuracy in images without and with surgical instrumentation, respectively. Ortho2D met or exceeded the performance of previously reported 2D and 3D labeling methods and reduced memory consumption by a factor of ∼50 (at 1 mm voxel size) compared to a 3D U-Net, allowing extension to higher resolution datasets than normally afforded. The accuracy of level identification increased from 80.1% (for standard/low resolution CT) to 95.1% (for high-resolution CT).Conclusions. The Ortho2D method achieved vertebrae labeling performance that is comparable to other recently reported methods with significant reduction in memory consumption, permitting further performance boosts via application to high-resolution CT.

MRI features of intra-axial histiocytic brain mass lesions.

AIM: To describe MRI features, including diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS), and perfusion-weighted imaging (PWI), of intra-axial tumour-like presentations of four different subtypes of histiocytosis. MATERIAL AND METHODS: The brain MRI findings of 23 patients with histologically proven histiocytosis were reviewed retrospectively (11 Langerhans cell histiocytosis [LCH], eight Erdheim-Chester disease [ECD], one overlap form LCH/ECD, two Rosai-Dorfman disease [RDD], and one haemophagocytic lymphohistiocytosis [HLH]) with single or multiple enhancing intraparenchymal brain lesions. RESULTS: Histiocytic brain mass lesions show some similar MRI features including Supra and/or infratentorial and/or paraventricular subcortical well-delineated masses, linear ependymal enhancement along the ventricles and brain stem lesions. Masses always present with mixed hyper- and hypointense signal on T2-weighted imaging (WI). Their enhancement is often homogeneous. Apparent diffusion coefficient (ADC) values are often normal or elevated. CONCLUSION: The presence of multiple periventricular and subcortical enhancing lesions with mixed signal intensity on T2WI and normal or high ADC values should lead radiologists to consider the diagnosis of histiocytic lesions and search for associated systemic lesions.

Cone-beam CT for imaging of the head/brain: Development and assessment of scanner prototype and reconstruction algorithms.

PURPOSE: Our aim was to develop a high-quality, mobile cone-beam computed tomography (CBCT) scanner for point-of-care detection and monitoring of low-contrast, soft-tissue abnormalities in the head/brain, such as acute intracranial hemorrhage (ICH). This work presents an integrated framework of hardware and algorithmic advances for improving soft-tissue contrast resolution and evaluation of its technical performance with human subjects. METHODS: Four configurations of a CBCT scanner prototype were designed and implemented to investigate key aspects of hardware (including system geometry, antiscatter grid, bowtie filter) and technique protocols. An integrated software pipeline (c.f., a serial cascade of algorithms) was developed for artifact correction (image lag, glare, beam hardening and x-ray scatter), motion compensation, and three-dimensional image (3D) reconstruction [penalized weighted least squares (PWLS), with a hardware-specific statistical noise model]. The PWLS method was extended in this work to accommodate multiple, independently moving regions with different resolution (to address both motion compensation and image truncation). Imaging performance was evaluated quantitatively and qualitatively with 41 human subjects in the neurosciences critical care unit (NCCU) at our institution. RESULTS: The progression of four scanner configurations exhibited systematic improvement in the quality of raw data by variations in system geometry (source-detector distance), antiscatter grid, and bowtie filter. Quantitative assessment of CBCT images in 41 subjects demonstrated: ~70% reduction in image nonuniformity with artifact correction methods (lag, glare, beam hardening, and scatter); ~40% reduction in motion-induced streak artifacts via the multi-motion compensation method; and ~15% improvement in soft-tissue contrast-to-noise ratio (CNR) for PWLS compared to filtered backprojection (FBP) at matched resolution. Each of these components was important to improve contrast resolution for point-of-care cranial imaging. CONCLUSIONS: This work presents the first application of a high-quality, point-of-care CBCT system for imaging of the head/ brain in a neurological critical care setting. Hardware configuration iterations and an integrated software pipeline for artifacts correction and PWLS reconstruction mitigated artifacts and noise to achieve image quality that could be valuable for point-of-care detection and monitoring of a variety of intracranial abnormalities, including ICH and hydrocephalus.

The effect of hyaluronic acid hydrogels on dental pulp stem cells behavior.

Dental caries and trauma, particularly in childhood, are among the most prevalent teeth problems, which result in the creation of cavities and probably tooth loss. Thus, novel regenerative approaches with high efficiency and less toxicity are required. Stem cell therapy along with the implementation of scaffolds has provided excellent opportunities in the regeneration of teeth structure. Hyaluronic acid (HA) hydrogels have enticed great attention in the field of regenerative medicine. The unique chemical and structural properties of HA and its derivatives have enabled their application in tissue engineering. Several factors such as the location and type of the lesion, teeth age, the type of capping materials determine the success rate of pulp therapy. HA hydrogels have been considered as biocompatible and safe scaffold supports in human dental cell therapies.

Statistical weights for model-based reconstruction in cone-beam CT with electronic noise and dual-gain detector readout.

Cone-beam CT (CBCT) systems commonly incorporate a flat-panel detector (FPD) with multiple-gain readout capability to reduce electronic noise and extend dynamic range. In this work, we report a penalized weighted least-squares (PWLS) method for CBCT image reconstruction with a system model that includes the electronic noise characteristics of FPDs, including systems with dynamic-gain or dual-gain (DG) readout in which the electronic noise is spatially varying. Statistical weights in PWLS were modified to account for the contribution of the electronic noise (algorithm denoted [Formula: see text]), and the method was combined with a certainty-based approach that improves the homogeneity of spatial resolution (algorithm denoted [Formula: see text]). The methods were tested in phantom studies designed to stress DG readout characteristics and translated to a clinical study for CBCT of patients with head traumas. The [Formula: see text] method demonstrated superior noise-resolution tradeoffs compared to filtered back-projection (FBP) and conventional PWLS. For example, with spatial resolution (edge-spread function width) matched at 0.65 mm, [Formula: see text] reduced variance by 28%-39% and 15%-25% compared to FBP and PWLS, respectively. The [Formula: see text] method achieved more homogeneous spatial resolution than [Formula: see text] while maintaining similar variance reduction. These findings were confirmed in clinical studies, which showed ~20% variance reduction in peripheral regions of the brain, potentially improving visual image quality in detection of epidural and/or subdural intracranial hemorrhage. The results are consistent with the general notion that incorporating a more accurate system model improves performance in optimization-based statistical CBCT reconstruction-in this case, a more accurate model for (spatially varying) electronic noise to improve detectability of low-contrast lesions.

Does the Presence or Absence of DESH Predict Outcomes in Adult Hydrocephalus?

BACKGROUND AND PURPOSE: The DESH (disproportionately enlarged subarachnoid-space hydrocephalus) pattern of "tight high-convexity and medial subarachnoid spaces, and enlarged Sylvian fissures with ventriculomegaly" is used to determine which patients undergo an operation for adult hydrocephalus at many centers. Our aim was to review adult hydrocephalus cases when DESH has not been a criterion for an operation to determine the prevalence of DESH among the cohort and compare the surgical outcomes in the presence or absence of DESH. MATERIALS AND METHODS: A retrospective cohort study was conducted at a single institution (Johns Hopkins Hospital) to include patients surgically treated for adult hydrocephalus between 2003 and 2014 drawn from a data base of patients who had undergone standardized hydrocephalus protocol MR imaging. Preoperative imaging was reviewed by 2 blinded neuroradiologists to characterize the presence of DESH. Preoperative and postoperative clinical symptomatology was recorded. Frequencies were compared using the Fisher exact test, and nonparametric means were compared using the Mann-Whitney U Test. RESULTS: One hundred thirty-three subjects were identified and included (96 DESH absent, 37 DESH present). Shunting led to significant improvement in gait and urinary and cognitive symptoms for the overall cohort and for patients with and without DESH (P < .05). The Fisher exact test did not demonstrate any significant differences in either gait or urinary or cognitive symptom improvement between patients with or without DESH (P > .05). CONCLUSIONS: The current study demonstrated symptom improvement in patients with adult hydrocephalus following shunting, with no significant differences between subjects with and without DESH. Thus, shunt insertion for patients with adult hydrocephalus should not rely solely on the presence of preoperative DESH findings.

Contrast-Enhanced CISS Imaging for Evaluation of Neurovascular Compression in Trigeminal Neuralgia: Improved Correlation with Symptoms and Prediction of Surgical Outcomes.

BACKGROUND AND PURPOSE: Thin-section MR imaging through the posterior fossa is frequently used for trigeminal neuralgia. Typical heavily T2-weighted imaging methods yield high anatomic detail and contrast between CSF and neurovascular structures, but poor contrast between vessels and nerves. We hypothesized that the addition of gadolinium-based contrast material to 3D-constructive interference in steady-state imaging would improve the characterization of trigeminal compression. MATERIALS AND METHODS: Retrospective review of high-resolution MRIs was performed in patients without prior microvascular decompression. 3D-CISS imaging without contrast and with contrast for 81 patients with trigeminal neuralgia and 15 controls was intermixed and independently reviewed in a blinded fashion. Cisternal segments of both trigeminal nerves were assessed for the grade of neurovascular conflict, cross-sectional area, and degree of flattening. Data were correlated with symptom side and pain relief after microvascular decompression using the Fisher exact test, receiver operating curve analysis, and a paired t test. RESULTS: Contrast-enhanced CISS more than doubled the prevalence of the highest grade of neurovascular conflict (14.8% versus 33.3%, P = .001) and yielded significantly lower cross-sectional area (P = 8.6 × 10-6) and greater degree of flattening (P = .02) for advanced-grade neurovascular conflict on the symptoms side compared with non-contrast-enhanced CISS. Patients with complete pain relief after microvascular decompression had significantly lower cross-sectional area on contrast-enhanced CISS compared with non-contrast-enhanced CISS on preoperative imaging (P = 2.0 × 10-7). Performance based on receiver operating curve analysis was significantly improved for contrast-enhanced CISS compared with non-contrast-enhanced CISS. CONCLUSIONS: The addition of contrast material to 3D-CISS imaging improves the performance of identifying unilateral neurovascular compression for symptomatic trigeminal neuralgia and predicting outcomes after microvascular decompression.

Reconstruction-of-difference (RoD) imaging for cone-beam CT neuro-angiography.

Timely evaluation of neurovasculature via CT angiography (CTA) is critical to the detection of pathology such as ischemic stroke. Cone-beam CTA (CBCT-A) systems provide potential advantages in the timely use at the point-of-care, although challenges of a relatively slow gantry rotation speed introduce tradeoffs among image quality, data consistency and data sparsity. This work describes and evaluates a new reconstruction-of-difference (RoD) approach that is robust to such challenges. A fast digital simulation framework was developed to test the performance of the RoD over standard reference reconstruction methods such as filtered back-projection (FBP) and penalized likelihood (PL) over a broad range of imaging conditions, grouped into three scenarios to test the trade-off between data consistency, data sparsity and peak contrast. Two experiments were also conducted using a CBCT prototype and an anthropomorphic neurovascular phantom to test the simulation findings in real data. Performance was evaluated primarily in terms of normalized root mean square error (NRMSE) in comparison to truth, with reconstruction parameters chosen to optimize performance in each case to ensure fair comparison. The RoD approach reduced NRMSE in reconstructed images by up to 50%-53% compared to FBP and up to 29%-31% compared to PL for each scenario. Scan protocols well suited to the RoD approach were identified that balance tradeoffs among data consistency, sparsity and peak contrast-for example, a CBCT-A scan with 128 projections acquired in 8.5 s over a 180° + fan angle half-scan for a time attenuation curve with ~8.5 s time-to-peak and 600 HU peak contrast. With imaging conditions such as the simulation scenarios of fixed data sparsity (i.e. varying levels of data consistency and peak contrast), the experiments confirmed the reduction of NRMSE by 34% and 17% compared to FBP and PL, respectively. The RoD approach demonstrated superior performance in 3D angiography compared to FBP and PL in all simulation and physical experiments, suggesting the possibility of CBCT-A on low-cost, mobile imaging platforms suitable to the point-of-care. The algorithm demonstrated accurate reconstruction with a high degree of robustness against data sparsity and inconsistency.

An overview application of silver nanoparticles in inhibition of herpes simplex virus.

Nanoscale particles and molecules are a potential different for the treatment of disease because they have distinctive biologic property based on their structure and size, which is different from traditional small-molecule drugs. The antimicrobial mechanisms of silver nanoparticles include the formation of free radicals damaging the bacterial membranes, interactions with DNA, adhesion to cell surface altering the membrane properties, and enzyme damage. In this review, we focus on applications of silver nanoparticles in inhibition of herpes simplex virus.

Synthesis and Evaluation of a Triblock Copolymer/ZnO Nanoparticles from Poly(ε-caprolactone) and Poly(Acrylic Acid) as a Potential Drug Delivery Carrier.

Through the present paper, a triblock copolymer containing pH-responsive (polyacrylic acid-b-polycaprolactone -b-polyacrylic acid) (PAA-b-PCL-b-PAA) was synthesized by using the ring-opening polymerization (ROP) of ε-caprolactone (ε-CL) and the reversible addition fragmentation chain transfer (RAFT) polymerization of the acrylic acid methods, as the drug carrier. Blends of the nanocrystalline zinc oxide nanoparticles (n-ZnO) and triblock copolymer treated from the solution have been used to make the hybrid polymer-metal oxide for the preparation of the drug loaded nanocomposite. The drug-release behavior of the nanocomposite was studied by using the Doxorubicin as a model drug. In addition to the self-assembly and pH-responsive behavior of the triblock copolymers/ZnO was studied in solution by the Fluorescence Spectroscopy, Scanning Electron Microscopy(SEM), Transmission Electron Microscopy (TEM), DLS, HNMR and FT-IR spectroscopy.

High-Resolution MRI Findings following Trigeminal Rhizotomy.

BACKGROUND AND PURPOSE: Patients with trigeminal neuralgia often undergo trigeminal rhizotomy via radiofrequency thermocoagulation or glycerol injection for treatment of symptoms. To date, radiologic changes in patients with trigeminal neuralgia post-rhizotomy have not been described, to our knowledge. The aim of this study was to evaluate patients after trigeminal rhizotomy to characterize post-rhizotomy changes on 3D high-resolution MR imaging. MATERIALS AND METHODS: A retrospective review of trigeminal neuralgia protocol studies was performed in 26 patients after rhizotomy compared with 54 treatment-naïve subjects with trigeminal neuralgia. Examinations were reviewed independently by 2 neuroradiologists blinded to the side of symptoms and treatment history. The symmetry of Meckel's cave on constructive interference in steady-state and the presence of contrast enhancement within the trigeminal nerves on volumetric interpolated breath-hold examination images were assessed subjectively. The signal intensity of Meckel's cave was measured on coronal noncontrast constructive interference in steady-state imaging on each side. RESULTS: Post-rhizotomy changes included subjective clumping of nerve roots and/or decreased constructive interference in steady-state signal intensity within Meckel's cave, which was identified in 17/26 (65%) patients after rhizotomy and 3/54 (6%) treatment-naïve patients (P < .001). Constructive interference in steady-state signal intensity within Meckel's cave was, on average, 13% lower on the side of the rhizotomy in patients posttreatment compared with a 1% difference in controls (P < .001). Small regions of temporal encephalomalacia were noted in 8/26 (31%) patients after rhizotomy and 0/54 (0%) treatment-naïve patients (P < .001). CONCLUSIONS: Post-trigeminal rhizotomy findings frequently include nerve clumping and decreased constructive interference in steady-state signal intensity in Meckel's cave. Small areas of temporal lobe encephalomalacia are encountered less frequently.

Imaging Appearance of SMARCB1 (INI1)-Deficient Sinonasal Carcinoma: A Newly Described Sinonasal Malignancy.

SMARCB1 (INI1)-deficient sinonasal carcinomas were first described in 2014, and this series of 17 cases represents the first imaging description. This tumor is part of a larger group of SMARCB1-deficient neoplasms, characterized by aggressive behavior and a rhabdoid cytopathologic appearance, that affect multiple anatomic sites. Clinical and imaging features overlap considerably with other aggressive sinonasal malignancies such as sinonasal undifferentiated carcinoma, which represents a common initial pathologic diagnosis in this entity. SMARCB1 (INI1)-deficient sinonasal tumors occurred most frequently in the nasoethmoidal region with invasion of the adjacent orbit and anterior cranial fossa. Avid contrast enhancement, intermediate to low T2 signal, and FDG avidity were frequent imaging features. Approximately half of the lesions demonstrated calcification, some with an unusual "hair on end" appearance, suggesting aggressive periosteal reaction.

Modeling and design of a cone-beam CT head scanner using task-based imaging performance optimization.

Detection of acute intracranial hemorrhage (ICH) is important for diagnosis and treatment of traumatic brain injury, stroke, postoperative bleeding, and other head and neck injuries. This paper details the design and development of a cone-beam CT (CBCT) system developed specifically for the detection of low-contrast ICH in a form suitable for application at the point of care. Recognizing such a low-contrast imaging task to be a major challenge in CBCT, the system design began with a rigorous analysis of task-based detectability including critical aspects of system geometry, hardware configuration, and artifact correction. The imaging performance model described the three-dimensional (3D) noise-equivalent quanta using a cascaded systems model that included the effects of scatter, scatter correction, hardware considerations of complementary metal-oxide semiconductor (CMOS) and flat-panel detectors (FPDs), and digitization bit depth. The performance was analyzed with respect to a low-contrast (40-80 HU), medium-frequency task representing acute ICH detection. The task-based detectability index was computed using a non-prewhitening observer model. The optimization was performed with respect to four major design considerations: (1) system geometry (including source-to-detector distance (SDD) and source-to-axis distance (SAD)); (2) factors related to the x-ray source (including focal spot size, kVp, dose, and tube power); (3) scatter correction and selection of an antiscatter grid; and (4) x-ray detector configuration (including pixel size, additive electronics noise, field of view (FOV), and frame rate, including both CMOS and a-Si:H FPDs). Optimal design choices were also considered with respect to practical constraints and available hardware components. The model was verified in comparison to measurements on a CBCT imaging bench as a function of the numerous design parameters mentioned above. An extended geometry (SAD = 750 mm, SDD = 1100 mm) was found to be advantageous in terms of patient dose (20 mGy) and scatter reduction, while a more isocentric configuration (SAD = 550 mm, SDD = 1000 mm) was found to give a more compact and mechanically favorable configuration with minor tradeoff in detectability. An x-ray source with a 0.6 mm focal spot size provided the best compromise between spatial resolution requirements and x-ray tube power. Use of a modest anti-scatter grid (8:1 GR) at a 20 mGy dose provided slight improvement (~5-10%) in the detectability index, but the benefit was lost at reduced dose. The potential advantages of CMOS detectors over FPDs were quantified, showing that both detectors provided sufficient spatial resolution for ICH detection, while the former provided a potentially superior low-dose performance, and the latter provided the requisite FOV for volumetric imaging in a centered-detector geometry. Task-based imaging performance modeling provides an important starting point for CBCT system design, especially for the challenging task of ICH detection, which is somewhat beyond the capabilities of existing CBCT platforms. The model identifies important tradeoffs in system geometry and hardware configuration, and it supports the development of a dedicated CBCT system for point-of-care application. A prototype suitable for clinical studies is in development based on this analysis.

3D-2D image registration for target localization in spine surgery: investigation of similarity metrics providing robustness to content mismatch.

In image-guided spine surgery, robust three-dimensional to two-dimensional (3D-2D) registration of preoperative computed tomography (CT) and intraoperative radiographs can be challenged by the image content mismatch associated with the presence of surgical instrumentation and implants as well as soft-tissue resection or deformation. This work investigates image similarity metrics in 3D-2D registration offering improved robustness against mismatch, thereby improving performance and reducing or eliminating the need for manual masking. The performance of four gradient-based image similarity metrics (gradient information (GI), gradient correlation (GC), gradient information with linear scaling (GS), and gradient orientation (GO)) with a multi-start optimization strategy was evaluated in an institutional review board-approved retrospective clinical study using 51 preoperative CT images and 115 intraoperative mobile radiographs. Registrations were tested with and without polygonal masks as a function of the number of multistarts employed during optimization. Registration accuracy was evaluated in terms of the projection distance error (PDE) and assessment of failure modes (PDE > 30 mm) that could impede reliable vertebral level localization. With manual polygonal masking and 200 multistarts, the GC and GO metrics exhibited robust performance with 0% gross failures and median PDE < 6.4 mm (±4.4 mm interquartile range (IQR)) and a median runtime of 84 s (plus upwards of 1-2 min for manual masking). Excluding manual polygonal masks and decreasing the number of multistarts to 50 caused the GC-based registration to fail at a rate of >14%; however, GO maintained robustness with a 0% gross failure rate. Overall, the GI, GC, and GS metrics were susceptible to registration errors associated with content mismatch, but GO provided robust registration (median PDE = 5.5 mm, 2.6 mm IQR) without manual masking and with an improved runtime (29.3 s). The GO metric improved the registration accuracy and robustness in the presence of strong image content mismatch. This capability could offer valuable assistance and decision support in spine level localization in a manner consistent with clinical workflow.

Task-Based Regularization Design for Detection of Intracranial Hemorrhage in Cone-Beam CT.

Prompt and reliable detection of acute intracranial hemorrhage (ICH) is critical to treatment of a number of neurological disorders. Cone-beam CT (CBCT) systems are potentially suitable for detecting ICH (contrast 40-80 HU, size down to 1 mm) at the point of care but face major challenges in image quality requirements. Statistical reconstruction demonstrates improved noise-resolution tradeoffs in CBCT head imaging, but its capability in improving image quality with respect to the task of ICH detection remains to be fully investigated. Moreover, statistical reconstruction typically exhibits nonuniform spatial resolution and noise characteristics, leading to spatially varying detectability of ICH for a conventional penalty. In this work, we propose a spatially varying penalty design that maximizes detectability of ICH at each location throughout the image. We leverage theoretical analysis of spatial resolution and noise for a penalized weighted least-squares (PWLS) estimator, and employ a task-based imaging performance descriptor in terms of detectability index using a nonprewhitening observer model. Performance prediction was validated using a 3D anthropomorphic head phantom. The proposed penalty achieved superior detectability throughout the head and improved detectability in regions adjacent to the skull base by ~10% compared to a conventional uniform penalty. PWLS reconstruction with the proposed penalty demonstrated excellent visualization of simulated ICH in different regions of the head and provides further support for development of dedicated CBCT head scanning at the point-of-care in the neuro ICU and OR.

Cone-Beam CT of Traumatic Brain Injury Using Statistical Reconstruction with a Post-Artifact-Correction Noise Model.

Traumatic brain injury (TBI) is a major cause of death and disability. The current front-line imaging modality for TBI detection is CT, which reliably detects intracranial hemorrhage (fresh blood contrast 30-50 HU, size down to 1 mm) in non-contrast-enhanced exams. Compared to CT, flat-panel detector (FPD) cone-beam CT (CBCT) systems offer lower cost, greater portability, and smaller footprint suitable for point-of-care deployment. We are developing FPD-CBCT to facilitate TBI detection at the point-of-care such as in emergent, ambulance, sports, and military applications. However, current FPD-CBCT systems generally face challenges in low-contrast, soft-tissue imaging. Model-based reconstruction can improve image quality in soft-tissue imaging compared to conventional filtered backprojection (FBP) by leveraging high-fidelity forward model and sophisticated regularization. In FPD-CBCT TBI imaging, measurement noise characteristics undergo substantial change following artifact correction, resulting in non-negligible noise amplification. In this work, we extend the penalized weighted least-squares (PWLS) image reconstruction to include the two dominant artifact corrections (scatter and beam hardening) in FPD-CBCT TBI imaging by correctly modeling the variance change following each correction. Experiments were performed on a CBCT test-bench using an anthropomorphic phantom emulating intra-parenchymal hemorrhage in acute TBI, and the proposed method demonstrated an improvement in blood-brain contrast-to-noise ratio (CNR = 14.2) compared to FBP (CNR = 9.6) and PWLS using conventional weights (CNR = 11.6) at fixed spatial resolution (1 mm edge-spread width at the target contrast). The results support the hypothesis that FPD-CBCT can fulfill the image quality requirements for reliable TBI detection, using high-fidelity artifact correction and statistical reconstruction with accurate post-artifact-correction noise models.

Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: application to high-quality head imaging.

Non-contrast CT reliably detects fresh blood in the brain and is the current front-line imaging modality for intracranial hemorrhage such as that occurring in acute traumatic brain injury (contrast ~40-80 HU, size > 1 mm). We are developing flat-panel detector (FPD) cone-beam CT (CBCT) to facilitate such diagnosis in a low-cost, mobile platform suitable for point-of-care deployment. Such a system may offer benefits in the ICU, urgent care/concussion clinic, ambulance, and sports and military theatres. However, current FPD-CBCT systems face significant challenges that confound low-contrast, soft-tissue imaging. Artifact correction can overcome major sources of bias in FPD-CBCT but imparts noise amplification in filtered backprojection (FBP). Model-based reconstruction improves soft-tissue image quality compared to FBP by leveraging a high-fidelity forward model and image regularization. In this work, we develop a novel penalized weighted least-squares (PWLS) image reconstruction method with a noise model that includes accurate modeling of the noise characteristics associated with the two dominant artifact corrections (scatter and beam-hardening) in CBCT and utilizes modified weights to compensate for noise amplification imparted by each correction. Experiments included real data acquired on a FPD-CBCT test-bench and an anthropomorphic head phantom emulating intra-parenchymal hemorrhage. The proposed PWLS method demonstrated superior noise-resolution tradeoffs in comparison to FBP and PWLS with conventional weights (viz. at matched 0.50 mm spatial resolution, CNR = 11.9 compared to CNR = 5.6 and CNR = 9.9, respectively) and substantially reduced image noise especially in challenging regions such as skull base. The results support the hypothesis that with high-fidelity artifact correction and statistical reconstruction using an accurate post-artifact-correction noise model, FPD-CBCT can achieve image quality allowing reliable detection of intracranial hemorrhage.