Faculty Bibliography

PURPOSE/OBJECTIVE:Tissue textures have been recognized as biomarkers for various clinical tasks. In computed tomography (CT) image reconstruction, it is important but challenging to preserve the texture when lowering x-ray exposure from full- toward low-/ultra-low dose level. Therefore, this paper aims to explore the texture-dose relationship within one tissue-specific pre-log Bayesian CT reconstruction algorithm. METHODS:To enhance the texture in ultra-low dose CT (ULdCT) reconstruction, this paper presents a Bayesian type algorithm. A shifted Poisson model is adapted to describe the statistical properties of pre-log data, and a tissue-specific Markov random field prior (MRFt) is used to incorporate tissue texture from previous full-dose CT, thus called SP-MRFt algorithm. Utilizing the SP-MRFt algorithm, we investigated tissue texture degradation as a function of x-ray dose levels from full dose (100 mAs/120 kVp) to ultralow dose (1 mAs/120 kVp) by using quantitative texture-based evaluation metrics. RESULTS:Experimental results show the SP-MRFt algorithm outperforms conventional filtered back projection (FBP) and post-log domain penalized weighted least square MRFt (PWLS-MRFt) in terms of noise suppression and texture preservation. Comparable results are also obtained with shifted Poisson model with 7 × 7 Huber MRF weights (SP-Huber7). The investigation on texture-dose relationship shows that the quantified texture measures drop monotonically as dose level decreases, and interestingly a turning point is observed on the texture-dose response curve. CONCLUSIONS:This important observation implies that there exists a minimum dose level, at which a given CT scanner (hardware configuration and image reconstruction software) can achieve without compromising clinical tasks. Moreover, the experiment results show that the variance of electronic noise has higher impact than the mean to the texture-dose relationship.

Background/UNASSIGNED:Computed tomographic (CT) features have demonstrated their value in classifying and assessing pulmonary nodules. Additionally, recent studies have shown the presence of keratin 17 (K17) in lung cancer is associated with increased mortality compared to patients with low/no K17 expression. The purpose of this study is to determine if there are CT imaging features that correlate with overexpression of K17 in patients with lung cancer. Methods/UNASSIGNED:This retrospective cohort study was approved by an Institutional Review Board. Lung cancer in 67 consecutive patients, who consented to have their lung cancer tissue stored in a tissue bank, were revaluated by immunohistochemical staining for the presence or absence of K17. Pre-operative imaging studies were collected on all patients. Two blinded independent radiologists evaluated multiple imaging features for each lung cancer. Results/UNASSIGNED:The overexpression of K17 was documented in 38.8% (26/67) of all lung cancers included in this cohort. Of the CT features recorded, the presence of the CT feature of lobulated borders was positively associated with over expression of K17 (P=0.02). No other imaging feature was associated with the presence or absence of K17. Conclusions/UNASSIGNED:The presence of a lobulated border, suggesting differential growth pattern of the lung cancer appears to be associated with the expression of K17.

Purpose/UNASSIGNED:To evaluate pulmonary embolism (PE) prevalence at CT pulmonary angiography in patients testing positive for coronavirus disease 2019 (COVID-19) and factors associated with PE severity. Materials and Methods/UNASSIGNED:value < .05 was considered significant. Results/UNASSIGNED:< .001). One additional patient with negative results at CT pulmonary angiography had deep venous thrombosis, thus resulting in 38.7% with PE or deep venous thrombosis, despite 40% receiving prophylactic anticoagulation. Other factors did not demonstrate significant PE association. Conclusion/UNASSIGNED:© RSNA, 2020.

Pyrite FeS2 has long been considered a potentially ideal photovoltaic material, but solar cells utilizing pyrite exhibit low open-circuit voltages (VOC) and have failed to achieve conversion efficiencies >3%. The recent discovery of a conductive p-type surface layer on n-type pyrite single crystals raises the intriguing possibility that the low VOC results from a leaky internal p-n junction between the surface and interior. Here, we reveal this internal junction, for the first time, through horizontal electronic transport measurements on sulfur vacancy (VS)- and Co-doped n-type pyrite single crystals. We observe a steep increase in resistance upon cooling heavily VS-doped crystals below ∼200 K, as the dominant charge transport crosses over from interior to surface conduction. The frequently employed two-resistor equivalent circuit model for lightly-doped pyrite crystals cannot reproduce this steep rise, but it can be accounted for, quantitatively, and with high fidelity, by adding an internal Schottky junction resistance between the surface and the interior. The average extracted Schottky barrier height is 320 meV (varying from 130-560 meV), significantly below expectations from band bending calculations (>750 meV) but similar in magnitude to VOC values reported for pyrite heterojunction solar cells. This internal p-n junction is thus implicated as the potential origin of the long-standing low-VOC problem in pyrite.

PURPOSE/OBJECTIVE:The right ventricular outflow tract (RVOT) velocity time integral (VTI), an echocardiographic measure of stroke distance, correlates with cardiac index. We sought to determine the prognostic significance of low RVOT VTI on clinical outcomes among patients with acute pulmonary embolism (PE). MATERIALS AND METHODS/METHODS:We conducted a retrospective review of echocardiograms on Pulmonary Embolism Response Team (PERT) activations at our institution. The main outcome was a composite of death, cardiac arrest, or hemodynamic deterioration. RESULTS:Of 188 patients, 30 met the combined outcome (16%) and had significantly lower RVOT VTI measurements (9.0 cm v 13.4 cm, p < 0.0001). The AUC for RVOT VTI at a cutoff of 10 cm was 0.78 (95% CI 0.67-0.90) with a sensitivity, specificity, negative predictive value, and positive predictive value of 0.72, 0.81, 0.94, and 0.42, respectively. Fifty-two patients of the cohort were classified as intermediate-high-risk PE and 21% of those met the combined outcome. RVOT VTI was lower among outcome positive patients (7.3 cm v 10.7 cm, p = 0.02). CONCLUSIONS:Low RVOT VTI is associated with poor clinical outcomes among patients with acute PE.

Background We observed a high number of patients with COVID-19 pneumonia who had barotrauma related to invasive mechanical ventilation at our institution. Purpose To determine if the rate of barotrauma in patients with COVID-19 infection was greater than other patients requiring invasive mechanical ventilation at our institution. Methods In this retrospective study, clinical and imaging data of patients seen between 03/01/2020 and 04/06/2020 who tested positive for COVID-19 and experienced barotrauma associated with invasive mechanical ventilation were compared to patients without COVID-19 infection during the same period. Historical comparison was made to barotrauma rates of patients with acute respiratory distress syndrome (ARDS) from 02/01/2016 to 02/01/2020 at our institution. Comparison of patient groups was performed using categorical or continuous statistical testing as appropriate with multivariable regression analysis. Patient survival was assessed using Kaplan-Meier curves analysis. Results 601 patients with COVID-19 infection underwent invasive mechanical ventilation (63 ± 15 years, 71% men). There were 89/601 (15%) patients with one or more barotrauma events, for a total of 145 barotrauma events (24% overall events) (95% CI 21-28%). During the same period, 196 patients without COVID-19 infection (64 ± 19 years, 52% male) with invasive mechanical ventilation had 1 barotrauma event (.5% 95% CI, 0-3%, p<.001 vs. the group with COVID-19 infection). Of 285 patients with ARDS over the prior 4 years on invasive mechanical ventilation (68 ± 17 years, 60% men), 28 patients (10%) had 31 barotrauma events, with overall barotrauma rate of 11% (95% CI 8-15%, p<.001 vs. the group with COVID-19 infection). Barotrauma is an independent risk factor for death in COVID-19 (OR=2.2, p=.03), and is associated with longer hospital length of stay (OR=.92, p<.001). Conclusion Patients with COVID-19 infection and invasive mechanical ventilation had a higher rate of barotrauma than patients with ARDS and patients without COVID-19 infection.

Localizing and characterizing clinically-significant lung nodules, a potential precursor to lung cancer, at the lowest achievable radiation dose is demanded to minimize the stochastic radiation effects from x-ray computed tomography (CT). A minimal dose level is heavily dependent on the image reconstruction algorithms and clinical task, in which the tissue texture always plays an important role. This study aims to investigate the dependence through a task-based evaluation at multiple dose levels and variable textures in reconstructions with prospective patient studies. 133 patients with a suspicious pulmonary nodule scheduled for biopsy were recruited and the data was acquired at120kVp with three different dose levels of 100, 40 and 20mAs. Three reconstruction algorithms were implemented: analytical filtered back-projection (FBP) with optimal noise filtering; statistical Markov random field (MRF) model with optimal Huber weighting (MRF-H) for piecewise smooth reconstruction; and tissue-specific texture model (MRF-T) for texture preserved statistical reconstruction. Experienced thoracic radiologists reviewed and scored all images at random, blind to the CT dose and reconstruction algorithms. The radiologists identified the nodules in each image including the 133 biopsy target nodules and 66 other non-target nodules. For target nodule characterization, only MRF-T at 40mAs showed no statistically significant difference from FBP at 100mAs. For localizing both the target nodules and the non-target nodules, some as small as 3mm, MRF-T at 40 and 20mAs levels showed no statistically significant difference from FBP at 100mAs, respectively. MRF-H and FBP at 40 and 20mAs levels performed statistically differently from FBP at 100mAs. This investigation concluded that (1) the textures in the MRF-T reconstructions improves both the tasks of localizing and characterizing nodules at low dose CT and (2) the task of characterizing nodules is more challenging than the task of localizing nodules and needs more dose or enhanced textures from reconstruction.

Artificial intelligence (AI) is a broad field of computational science that includes many subsets. Today the most widely used subset in medical imaging is machine learning (ML). Many articles have focused on the use of ML for pattern recognition to detect and potentially diagnose various pathologies. However, AI algorithm development is now directed toward workflow management. AI can impact patient care at multiple stages of their imaging experience and assist in efficient and effective scheduling, imaging performance, worklist prioritization, image interpretation, and quality assurance. The purpose of this manuscript was to review the potential AI applications in radiology focusing on workflow management and discuss how ML will affect cardiothoracic imaging.

OBJECTIVE. The response to coronavirus disease (COVID-19) is evolving in New York City. We would like to share our experiences, thoughts, and perspectives on coping with the pandemic. CONCLUSION. This article presents experiences that are meant to help foster discussion as the wave of COVID-19 continues. Thoughtful leadership and careful continuous communication will help us minimize anxiety and frustration during this difficult time.