OBJECTIVES:Flexible fiberoptic nasolaryngoscopy is among the most common procedures performed by otolaryngologists worldwide. Despite this, there is no standard training method. High-fidelity approaches typically require trainees to learn on live patients and provide general qualitative information about the scope's path. However, trainees lack objective quantitative procedural feedback to optimize their technique, and patients may be subjected to pain and epistaxis. A trainer that provides a safe, reusable interface and quantitative report would transform this learning experience. METHODS:Our team developed a cost-effective 3D-printed task trainer for flexible fiberoptic nasolaryngoscopy and coupled this with a calibrated electromagnetic tracker to evaluate scope trajectory across users. Thirty-one subjects ranging from secondary school student to practicing otolaryngologist used the trainer. Participant confidence and perceived model realism were assessed with surveys. Scope trajectory was assessed using the electronic tracker. RESULTS:Mean score on the realism of endoscopic appearance was 7.5 on a 10-point visual analog scale. All subjects reported stable or increased confidence in flexible nasolaryngoscopy after using the model, with novices demonstrating the most significant change (P = .005). Trajectory data from the fine-wire tracker demonstrated that less experienced trainees paused and backtracked more than more experienced trainees (P = .004). CONCLUSIONS:This novel 3D-printed model offers a feasible task trainer for flexible nasolaryngoscopy and yields trajectory information that distinguishes between novices and experts. This model can provide an accessible training method that does not compromise patient experience, while simultaneously offering objective feedback to trainees as they grow their skills.

Robin Sequence (RS) is a congenital condition in which patients experience dynamic, periodic obstruction or collapse of the upper airway due to an underdeveloped jaw and a posteriorly displaced tongue. Current clinical techniques for evaluating airway obstruction do not provide quantifiable data and fail to account for the dynamic nature of obstruction or collapse. There is no standardized criterion to characterize obstruction or collapse severity. This study presents the first method that extracts airway motion from 4-dimensional computed tomography and performs a patient-specific, moving-mesh computational fluid dynamics (CFD) analysis of RS patients with complete airway collapse or obstruction. To quantify the effects of airway collapse, airflow dynamics are analyzed using both instantaneous metrics (velocity, pressure, and energy dissipation rate) and cycle-averaged metrics (resistive work of breathing). These results are compared between a collapsing airway and its synthetic non-collapsing counterpart. To validate the synthetic non-collapsing case, it is further compared with a patient-specific non-collapsing airway. The results show that, to achieve the same tidal volume, the collapsing case requires significantly greater computed breathing effort (7.55 mJ/cycle) than the synthetic non-collapsing case (3.68 mJ/cycle). The shorter inspiration time due to the collapse leads to a higher inlet velocity, resulting in 1.7 times the maximum velocity during peak inspiration (just prior to collapse) and a 2.7-fold higher pressure drop in the collapsing case compared to the synthetic non-collapsing case. At the onset of collapse, a sharp spike in localized energy dissipation rate is observed due to the abrupt deceleration and dissipation of peak flow velocities. This methodology provides a novel approach to understanding the airflow dynamics of RS patients with airway collapse. It enables quantitative comparison between collapsing and non-collapsing airways, thereby offering the potential to support more informed and objective clinical decision-making.

Objective(s) Flexible nasolaryngoscopy (FNL) is a fundamental skill in otolaryngology. It is typically learned in clinical settings, with impacts on patient comfort and safety. Objective assessment, specific feedback, and a better understanding of learner trajectory in a simulation setting could improve the efficiency of FNL training and ultimately improve the patient experience. This study sought to employ a novel FNL model with trajectory tracking to identify metrics and critical steps that distinguish less and more experienced trainees and identify indicators of proficiency. Methods FNL trainees in an otolaryngology simulation course performed three FNL trials on a novel CT-based 3D-printed FNL model with embedded location and trajectory tracking. Participants were stratified by prior experience. Outcomes included procedure time, number of pauses or backtracks, and undesirable contact time with critical anatomic regions. Results A total of 29 trainees, ranging from medical students to fourth year residents, participated in this study. More experienced trainees demonstrated shorter procedure time, fewer pauses and backtracks, and less time in contact with the posterior nasopharynx (p < 0.05). There was a statistically significant difference between participant groups who had performed 1-5 and > 15 prior FNL. Conclusions Procedure time, pauses, backtracks, and contact with critical structures represent objective, measurable metrics of proficiency in FNL simulation training. Post hoc analyses suggest the threshold for procedural proficiency occurs with intermediate prior experience, overlapping with prior literature reports from video-rating of proficiency. Future study could examine how metrics change with FNL practice to optimize targeted feedback that improves efficiency and ultimately reduces patient risk and discomfort. Level of Evidence N/A

Dynamic airway computed topography (4D-CT) can be used to evaluate the trachea in pediatric patients with tracheomalacia. The 4D-CT enables objective and quantitative evaluation throughout all phases of respiration; however, current systems focus on qualitative review of generated 4D images. Few analytic workflows are available to assist in the extraction of the quantitative geomorphic data generated. In this study, we share a protocol developed within the 3D Slicer framework that performs semi-automatic tracheal segmentation and subsequent geomorphic analysis. This methodology is applied to 4 sample cases with varying degrees of tracheal collapse throughout all phases of respiration to demonstrate output of cross-sectional area, aspect ratio (defined as the ratio between minor-to-major luminal axis lengths), and tracheal volume (bound by the subglottis and carina) metrics.

ABSTRACT Objectives To assess the utility of a novel 3D‐printed model incorporating user‐directed head position adjustments for flexible fiberoptic nasolaryngoscopy (FNL) training and simulation. Methods This proof‐of‐concept study utilized a CT‐based, 3D‐printed airway model permitting adjustments in head protrusion, flexion, and extension, with associated anatomical changes in oropharyngeal shape. Cervical flexion and atlantoaxial extension (“sniffing position”) represented the optimal head position (OHP) for laryngeal visualization, as determined by attending faculty otolaryngologists. During FNL trials, trainees simulated patient instruction for head adjustment and were asked to indicate their perceived OHP. Standardized photographs of trainees' OHP were taken and compared by training level using fiducial marker‐based image analysis. Surveys evaluated trainee experience. Results A total of 26 medical students and residents (PGY‐1 to PGY‐4), completed FNL trials. Senior residents (R3+) showed little variability in their chosen OHP. While intermediate learners (R1–R2) showed the greatest variability in OHP there were no significant differences in final OHP among participants. Trainees rated the helpfulness of positional adjustments 8 ± 1.80 on a 10‐point Likert scale. Conclusions Head position maneuverability improves fidelity and the FNL training experience. Using the model, participants at all training levels were able to achieve OHPs comparable with experienced practitioners. Greater OHP variability among those with moderate experience suggests this model feature may be used by trainees to optimize technique. This novel model presents an affordable, portable, and easily replicable tool to enhance FNL simulation and training.

OBJECTIVES:To demonstrate the feasibility and impact of auditory feedback in flexible fiberoptic nasolaryngoscopy (FNL) training with a novel model incorporating audio triggers based on known anatomical loci of negative patient feedback. METHODS:This proof-of-concept study used a CT-based 3D-printed and silicone-casted model of nares to mainstem bronchi to teach FNL during an otolaryngology simulation training. The spatially tracked laryngoscope tip triggered simulated responses (pain, gag, cough) when co-localized to specific anatomic landmarks: the nasal septum, epiglottis, and trachea. Participants wearing heart rate (HR) monitors completed three FNL trials, two without and one with auditory patient responses. Outcomes, stratified by prior trainee experience, included participant HR, survey-based changes in confidence, and assessment of auditory feedback utility. RESULTS:Twenty-nine trainees ranging from medical students to fourth-year otolaryngology residents rated model realism and tactile experience 7.4 ± 1.6 and 6.9 ± 2.2, respectively, on a 10-point Likert scale (mean ± standard deviation). Average HR increased from resting baseline during all trials, decreased during the second trial, and increased in the final trial that included audio feedback (p = 0.02). The least-experienced participants reported the greatest change in confidence (novice: +175%, low: +165%, intermediate: +73%, experienced: +13%). All trainees felt auditory feedback added value and improved fidelity. CONCLUSION:Heart rate increased from baseline during simulated FNL on a novel 3D-printed model, implying sympathetic activation and increased stress. HR decreased with repetition, implying improved comfort, but increased with simulated auditory patient responses, suggesting that patient feedback can increase trainee attentiveness. Future studies may analyze the widespread implementation of this model for multi-disciplinary learners. LEVEL OF EVIDENCE:N/A.

The pathophysiology of Idiopathic Intracranial Hypertension (IIH) is poorly understood making the disease difficult to properly diagnose and treat. Endovascular venous stenting has emerged as an effective non-invasive treatment option for a select cohort of IIH patients with venous sinus stenosis and elevated venous sinus pressure gradient. Unfortunately, current methods of determining patient eligibility for stenting treatment depend on highly invasive and insufficient measurement methods such as venous manometry, which can only measure pressure gradients and not other components of the complex 3D hemodynamic environment. Thus, there is a need for a non-invasive methodology for determining the 3D flow environment of the dural venous sinuses. To develop a novel method of non-invasive, patient-specific computational fluid dynamic (CFD) simulation of venous sinus hemodynamics for evaluating stenting eligibility. A patient with IIH and elevated sinus pressure gradient underwent MR venography, phase-contrast MR venography, and venous manometry. Patient-specific dural venous anatomy was segmented from the MR venography to construct 3D models of the venous sinuses. 3D transient patient-specific computational fluid dynamic simulations were conducted using flow velocities measured with phase-contrast MR venography as boundary conditions. Successful computational simulations were completed, allowing for the calculation of the spatio-temporal evolution of blood flow through the dural venous sinuses, and the quantitative examination of pressure gradients. Calculated pressure gradients from CFD were validated against venous manometry with an error of only ∼5%. We have successfully developed time-resolved, patient-specific 3D computational simulations of the dural venous sinuses without assumptions at the boundary conditions for the first time. The methodology can accurately and non-invasively measure venous pressure gradients. This preliminary study serves as a proof of concept for our method to be used as a diagnostic tool for determining venous stenting eligibility, as well as a tool for advancing the general understanding of IIH pathophysiology.

Objective: Head and neck lymphatic malformation (HNLM) treatment involves a combination of observation, surgery, sclerotherapy, and targeted medical therapy. Objective comparison of these differing treatments is unstandardized due to heterogeneity of HNLM location, size, and variable components. Our objective was to develop a protocol for standardized assessment of magnetic resonance imaging (MRI) image sets through novel semiautomated algorithms. We aimed to obtain reproducible multimodal tissue level data that can be analyzed for interval HNLM treatment response. Methods: Patients who were undergoing therapy for HNLM were queried from an institutional database between 2015 and 2020. MRI sequences were registered in 3D Slicer, and in MATLAB a multimodal tool was developed to quantitate HNLM volume and changes in composition. Volume measures were normalized to normal childhood growth using the nasion-basion distance. Reproducibility studies were conducted to evaluate interrater reliability. Results: HNLM undergoing excision (n = 3) had a 92.3%–96.7% decrease malformation volume. HNLM having medical treatment with sirolimus and aspirin had a 7.3%–36.4% decrease in normalized volume, the majority of which was due to a decrease in cystic fluid content (reduced by 27.0%–36.4%). HNLM treated with sclerotherapy had no normalized volume change following treatment. One HNLM first treated with sirolimus had a 27.8% decrease in normalized volume and then combined normalized volume reduction of 75.6% after resection. Conclusion: This proof-of-concept use of longitudinal HNLM MRI in pediatric patients undergoing treatment demonstrates that objective information can be obtained through this method. This information can be used to determine treatment efficacy and optimize lesion specific treatment strategies.

Four-dimensional data sets are increasingly common in MRI and CT. While clinical visualization often focuses on individual temporal phases capturing the tissue(s) of interest, it may be possible to gain additional insight through exploring animated 3D reconstructions of physiological motion made possible by augmented or virtual reality representations of 4D patient imaging. Cardiac CT acquisitions can provide sufficient spatial resolution and temporal data to support advanced visualization, however, there are no open-source tools readily available to facilitate the transformation from raw medical images to dynamic and interactive augmented or virtual reality representations. To address this gap, we developed a workflow using free and open-source tools to process 4D cardiac CT imaging starting from raw DICOM data and ending with dynamic AR representations viewable on a phone, tablet, or computer. In addition to assembling the workflow using existing platforms (3D Slicer and Unity), we also contribute two new features: 1. custom software which can propagate a segmentation created for one cardiac phase to all others and export to surface files in a fully automated fashion, and 2. a user interface and linked code for the animation and interactive review of the surfaces in augmented reality. Validation of the surface-based areas demonstrated excellent correlation with radiologists’ image-based areas (R > 0.99). While our tools were developed specifically for 4D cardiac CT, the open framework will allow it to serve as a blueprint for similar applications applied to 4D imaging of other tissues and using other modalities. We anticipate this and related workflows will be useful both clinically and for educational purposes.

Background: Abnormal cerebrospinal fluid (CSF) flow is associated with a variety of poorly understood neurological disorders such as Alzheimer's Disease and hydrocephalus. The lack of comprehensive understanding of the fluid and solid mechanics of CSF flow remains a critical barrier in the development of diagnostic assessment and potential treatment options for these diseases. We have developed a whole brain, patient-specific computational fluid dynamics (CFD) simulation of CSF flow in the cranial cavity as a step towards comprehensive understanding of CSF dynamics and how they relate to neurodegenerative diseases. Methods: A patient-specific 3D geometry of the CSF filled spaces was segmented from structural MRI. Patient-specific boundary conditions were measured using phase contrast MRI. A rigid wall three-dimensional CFD simulation was conducted using only patient-specific waveforms as boundary conditions. Deformation of brain tissue is accounted for using volumetric flowrate boundary conditions calculated via the conservation of mass. Phase contrast MRI measurement of maximum velocity at the cerebral aqueduct was used to validate the simulation with excellent agreement. Results: The CSF dynamics across the cardiac cycle are presented, illustrating the relationship between arterial flow and CSF flow. Flow in and out of the ventricles was shown to have a slight phase delay (similar to 20 % of the cardiac cycle) from flow in the subarachnoid space. Intracranial pressure dynamics are presented, with pressure in the Lateral Ventricles demonstrating less significant transient effects than pressure in the subarachnoid space. Conclusions: This work presents a quantitatively validated whole-brain simulation of CSF flow for a single healthy subject. The computational methodology improves over the state of the art by eliminating non-physiological boundary conditions and unnecessary assumptions about the mechanical properties of brain tissue, providing an essential step towards clinically useful tools for assessing the development of neurodegenerative disorders.

PURPOSE:PIK3CA-related overgrowth spectrum (PROS) conditions of the head and neck are treatment challenges. Traditionally, these conditions require multiple invasive interventions, with incomplete malformation removal, disfigurement, and possible dysfunction. Use of the PI3K inhibitor alpelisib, previously shown to be effective in PROS, has not been reported in PIK3CA-associated head and neck lymphatic malformations (HNLMs) or facial infiltrating lipomatosis (FIL). We describe prospective treatment of 5 children with PIK3CA-associated HNLMs or head and neck FIL with alpelisib monotherapy.METHODS:A total of 5 children with PIK3CA-associated HNLMs (n = 4) or FIL (n = 1) received alpelisib monotherapy (aged 2-12 years). Treatment response was determined by parental report, clinical evaluation, diary/questionnaire, and standardized clinical photography, measuring facial volume through 3-dimensional photos and magnetic resonance imaging.RESULTS:All participants had reduction in the size of lesion, and all had improvement or resolution of malformation inflammation/pain/bleeding. Common invasive therapy was avoided (ie, tracheotomy). After 6 or more months of alpelisib therapy, facial volume was reduced (range 1%-20%) and magnetic resonance imaging anomaly volume (range 0%-23%) were reduced, and there was improvement in swallowing, upper airway patency, and speech clarity.CONCLUSION:Individuals with head and neck PROS treated with alpelisib had decreased malformation size and locoregional overgrowth, improved function and symptoms, and fewer invasive procedures.

Objectives To evaluate the performance of 4-dimensional computed tomography (4D-CT) in assessing upper airway obstruction (UAO) in patients with Robin sequence (RS) and compare the accuracy and reliability of 4D-CT and flexible fiber-optic laryngoscopy (FFL). Study Design Prospective survey of retrospective clinical data. Setting Single, tertiary care pediatric hospital. Methods At initial and 30-day time points, a multidisciplinary group of 11 clinicians who treat RS rated UAO severity in 32 sets of 4D-CT visualizations and FFL videos (dynamic modalities) and static CT images. Raters assessed UAO at the velopharynx and oropharynx (1 = none to 5 = complete) and noted confidence levels of each rating. Intraclass correlation and Krippendorff alpha were used to assess intra- and interrater reliability, respectively. Accuracy was assessed by comparing clinician ratings with quantitative percentage constriction (QPC) ratings, calculated based on 4D-CT airway cross-sectional area. Results were compared using Wilcoxon rank-sum and signed-rank tests. Results There was similar intrarater agreement (moderate to substantial) with 4D-CT and FFL, and both demonstrated fair interrater agreement. Both modalities underestimated UAO severity, although 4D-CT ratings were significantly more accurate, as determined by QPC similarity, than FFL (-1.06 and -1.46 vs QPC ratings, P = .004). Overall confidence levels were similar for 4D-CT and FFL, but other specialists were significantly less confident in FFL ratings than were otolaryngologists (2.25 and 3.92, P < .0001). Conclusion Although 4D-CT may be more accurate in assessing the degree of UAO in patients with RS, 4D-CT and FFL assessments demonstrate similar reliability. Additionally, 4D-CT may be interpreted with greater confidence by nonotolaryngologists who care for these patients.

Thorough assessment of dynamic upper airway obstruction (UAO) in Robin sequence (RS) is critical, but traditional evaluation modalities have significant limitations. Four-dimensional computed tomography (4D-CT) is promising in that it enables objective and quantitative evaluation throughout all phases of respiration. However, there exist few protocols or analysis tools to assist in obtaining and interpreting the vast amounts of obtained data. A protocol and set of data analysis tools were developed to enable quantification and visualization of dynamic 4D-CT data. This methodology was applied to a sample case at 2 time points. In the patient with RS, overall increases in normalized airway caliber were observed from 5 weeks to 1 year. There was, however, continued dynamic obstruction at all airway levels, though objective measures of UAO did improve at the nasopharynx and oropharynx. Use of 4D-CT and novel analyses provide additional quantitative information to evaluate UAO in patients with RS.

Chest radiographs are a common diagnostic tool in pediatric care, and several computer-augmented decision tasks for radiographs would benefit from knowledge of the anatomic locations within the thorax. For example, a pre-segmented chest radiograph could provide context for algorithms designed for automatic grading of catheters and tubes. This work develops a deep learning approach to automatically segment chest radiographs into multiple regions to provide anatomic context for future automatic methods. This type of segmentation offers challenging aspects in its goal of multi-class segmentation with extreme class imbalance between regions. In an IRB-approved study, pediatric chest radiographs were collected and annotated with custom software in which users drew boundaries around seven regions of the chest: left and right lung, left and right subdiaphragm, spine, mediastinum, and carina. We trained a U-Net-style architecture on 328 annotated radiographs, comparing model performance with various combinations of loss functions, weighting schemes, and data augmentation. On a test set of 70 radiographs, our best-performing model achieved 93.8% mean pixel accuracy and a mean Dice coefficient of 0.83. We find that (1) cross-entropy consistently outperforms generalized Dice loss, (2) light augmentation, including random rotations, improves overall performance, and (3) pre-computed pixel weights that account for class frequency provide small performance boosts. Overall, our approach produces realistic eight-class chest segmentations that can provide anatomic context for line placement and potentially other medical applications.

Background Facioscapulohumeral muscular dystrophy (FSHD) is a patchy and slowly progressive disease of skeletal muscle. MRI short tau inversion recovery (STIR) sequences of patient muscles often show increased hyperintensity that is hypothesized to be associated with inflammation. This is supported by the presence of inflammatory changes on biopsies of STIR-positive muscles. We hypothesized that the STIR positivity would normalize with targeted immunosuppressive therapy. Case presentation 45-year-old male with FSHD type 1 was treated with 12 weeks of immunosuppressive therapy, tacrolimus and prednisone. Tacrolimus was treated to a goal serum trough of > 5 ng/mL and prednisone was tapered every month. Quantitative strength exam, functional outcome measures, and muscle MRI were performed at baseline, week 6, and week 12. The patient reported subjective worsening as reflected in quantitative strength exam. The MRI STIR signal was slightly increased from 0.02 to 0.03 of total muscle; while the T1 fat fraction was stable. Functional outcome measures also were stable. Conclusions Immunosuppressive therapy in refractive autoimmune myopathy in other contexts has been shown to reverse STIR signal hyperintensity, however this treatment did not reverse STIR signal in this patient with FSHD. In fact, STIR signal slightly increased throughout the treatment period. This is the first study of using MRI STIR and T1 fat fraction to follow treatment effect in FSHD. We find that STIR might not be a dynamic marker for suppressing inflammation in FSHD.

Background: The accuracy of absolute myocardial blood flow (MBF) from dynamic contrast-enhanced cardiac computed tomography acquisitions has not been fully characterized. We evaluate computed tomography (CT) compared with rubidium-82 positron emission tomography (PET) MBF estimates in a high-risk population. Methods: In a prospective trial, patients receiving clinically indicated rubidium-82 PET exams were recruited to receive a dynamic contrast-enhanced cardiac computed tomography exam. The CT protocol included a rest and stress dynamic portion each acquiring 12 to 18 cardiac-gated frames. The global MBF was estimated from the PET and CT exam. Results: Thirty-four patients referred for cardiac rest-stress PET were recruited. Of the 68 dynamic contrast-enhanced cardiac computed tomography scans, 5 were excluded because of injection errors or mismatched hemodynamics. The CT-derived global MBF was highly correlated with the PET MBF (r=0.92; P <0.001) with a mean difference of 0.7±26.4%. The CT MBF estimates were within 20% of PET estimates ( P <0.02) with a mean of (1) MBF for resting flow of PET versus CT of 0.9±0.3 versus 1.0±0.2 mL/min per gram and (2) MBF for stress flow of 2.1±0.7 versus 2.0±0.8 mL/min per gram. Myocardial flow reserve was −14±28% underestimated with CT (PET versus CT myocardial flow reserve, 2.5±0.6 versus 2.2±0.6). The proposed rest+stress+computed tomography angiography protocol had a dose length product of 598±76 mGy×cm resulting in an approximate effective dose of 8.4±1.1 mSv. Conclusions: In a high-risk clinical population, a clinically practical dynamic contrast-enhanced cardiac computed tomography provided unbiased MBF estimates within 20% of rubidium-82 PET. Although unbiased, the CT estimates contain substantial variance with an standard error of the estimate of 0.44 mL/min per gram. Myocardial flow reserve estimation was not as accurate as individual MBF estimates.

Quantitative myocardial blood flow (MBF) estimation by dynamic contrast enhanced cardiac computed tomography (CT) requires multi-frame acquisition of contrast transit through the blood pool and myocardium to inform the arterial input and tissue response functions. Both the input and the tissue response functions for the entire myocardium are sampled with each acquisition. However, the long breath holds and frequent sampling can result in significant motion artifacts and relatively high radiation dose. To address these limitations, we propose and evaluate a new static cardiac and dynamic arterial (SCDA) quantitative MBF approach where (1) the input function is well sampled using either prediction from pre-scan timing bolus data or measured from dynamic thin slice ‘bolus tracking’ acquisitions, and (2) the whole-heart tissue response data is limited to one contrast enhanced CT acquisition. A perfusion model uses the dynamic arterial input function to generate a family of possible myocardial contrast enhancement curves corresponding to a range of MBF values. Combined with the timing of the single whole-heart acquisition, these curves generate a lookup table relating myocardial contrast enhancement to quantitative MBF. We tested the SCDA approach in 28 patients that underwent a full dynamic CT protocol both at rest and vasodilator stress conditions. Using measured input function plus single (enhanced CT only) or plus double (enhanced and contrast free baseline CT’s) myocardial acquisitions yielded MBF estimates with root mean square (RMS) error of 1.2 ml/min/g and 0.35 ml/min/g, and radiation dose reductions of 90% and 83%, respectively. The prediction of the input function based on timing bolus data and the static acquisition had an RMS error compared to the measured input function of 26.0% which led to MBF estimation errors greater than threefold higher than using the measured input function. SCDA presents a new, simplified approach for quantitative perfusion imaging with an acquisition strategy offering substantial radiation dose and computational complexity savings over dynamic CT.

Dynamic contrast enhanced cardiac CT acquisitions can quantify myocardial blood flow (MBF) in absolute units (ml/min/g), but repeated scans increase X-ray radiation dose to the patient. We propose a novel approach using high temporal sampling of the input function with reduced temporal sampling of the myocardial tissue response. This type of data could be acquired with current bolus tracking acquisitions or with new acquisition sequences offering reduced radiation dose and potentially easier data processing and flow estimation. To evaluate this type of data, we prospectively acquired a full dynamic series [12 - 18 frames (mean 14.5 +/- 1.4) over 23 to 44 seconds (mean 31.3 +/- 5.0 sec)] on 28 patients at rest and stress (N=56 studies) and examined the relative performance of myocardial perfusion estimation when the myocardial data is subsampled down to 8, 4, 2 or 1 frame(s). Unlike previous studies, for all frame rates, we consider a well-sampled input function. As expected, subsampling linearly reduces radiation dose while progressively decreasing estimation accuracy, with the typical absolute error in MBF (as compared to the full-length series) increasing from 0.22 to 0.30 to 0.35 to 1.12 ml/min/g as the number of frames used for estimation decreases from 8 to 4 to 2 to 1, respectively. These results suggest that high temporal sampling of the input function with low temporal sampling of the myocardial response can provide much of the benefit of dynamic CT for MBF quantification with dramatic reductions in the required number of myocardial acquisitions and the associated radiation dose (e.g. 77% dose reduction for 2-frame case).

Quantification of myocardial blood flow (MBF) can aid in the diagnosis and treatment of coronary artery disease. However, there are no widely accepted clinical methods for estimating MBF. Dynamic cardiac perfusion computed tomography (CT) holds the promise of providing a quick and easy method to measure MBF quantitatively. However, the need for repeated scans can potentially result in a high patient radiation dose, limiting the clinical acceptance of this approach. In our previous work, we explored techniques to reduce the patient dose by either uniformly reducing the tube current or by uniformly reducing the number of temporal frames in the dynamic CT sequence. These dose reduction techniques result in noisy time-attenuation curves (TACs), which can give rise to significant errors in MBF estimation. We seek to investigate whether nonuniformly varying the tube current and/or sampling intervals can yield more accurate MBF estimates for a given dose. Specifically, we try to minimize the dose and obtain the most accurate MBF estimate by addressing the following questions: when in the TAC should the CT data be collected and at what tube current(s)? We hypothesize that increasing the sampling rate and/or tube current during the time frames when the myocardial CT number is most sensitive to the flow rate, while reducing them elsewhere, can achieve better estimation accuracy for the same dose. We perform simulations of contrast agent kinetics and CT acquisitions to evaluate the relative MBF estimation performance of several clinically viable variable acquisition methods. We find that variable temporal and tube current sequences can be performed that impart an effective dose of 5.5 mSv and allow for reductions in MBF estimation rootmean-square error on the order of 20% compared to uniform acquisition sequences with comparable or higher radiation doses. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE).