An Adaptive SCG-ECG Multimodal Gating Framework for Cardiac CTA.

Cardiovascular disease (CVD) is the leading cause of death worldwide. Coronary artery disease (CAD), a prevalent form of CVD, is typically assessed using catheter coronary angiography (CCA), an invasive, costly procedure with associated risks. While cardiac computed tomography angiography (CTA) presents a less invasive alternative, it suffers from limited temporal resolution, often resulting in motion artifacts that degrade diagnostic quality. Traditional ECG-based gating methods for CTA inadequately capture cardiac mechanical motion. To address this, we propose a novel multimodal approach that enhances CTA imaging by predicting cardiac quiescent periods using seismocardiogram (SCG) and ECG data, integrated through a weighted fusion (WF) approach and artificial neural networks (ANNs). We developed a regression-based ANN framework (r-ANN WF) designed to improve prediction accuracy and reduce computational complexity, which was compared with a classification-based framework (c-ANN WF), ECG gating, and US data. Our results demonstrate that the r-ANN WF approach improved overall diastolic and systolic cardiac quiescence prediction accuracy by 52.6% compared to ECG-based predictions, using ultrasound (US) as the ground truth, with an average prediction time of 4.83 ms. Comparative evaluations based on reconstructed CTA images show that both r-ANN WF and c-ANN WF offer diagnostic quality comparable to US-based gating, underscoring their clinical potential. Additionally, the lower computational complexity of r-ANN WF makes it suitable for real-time applications. This approach could enhance CTA's diagnostic quality, offering a more accurate and efficient method for CVD diagnosis and management.

Prospective Evaluation of Artificial Intelligence Triage of Intracranial Hemorrhage on Noncontrast Head CT Examinations.

Background: Retrospective studies evaluating artificial intelligence (AI) algorithms for intracranial hemorrhage (ICH) detection on noncontrast CT (NCCT) have shown promising results but lack prospective validation. Objective: To evaluate the impact on radiologists' real-world aggregate performance for ICH detection and report turnaround times for ICH-positive examinations of a radiology department's implementation of an AI triage and notification system for ICH detection on head NCCT examinations. Methods: This prospective single-center study included adult patients who underwent head NCCT examinations from May 12, 2021 to June 30, 2021 (phase 1) or September 30, 2021 to December 4, 2021 (phase 2). Before phase 1, the radiology department implemented a commercial AI triage system for ICH detection that processed head NCCT examinations and notified radiologists of positive results through a widget with a floating pop-up display. Examinations were interpreted by neuroradiologists or emergency radiologists, who evaluated examinations without and with AI assistance in phase 1 and phase 2, respectively. A panel of radiologists conducted a review process for all examinations with discordance between the radiology report and AI and a subset of remaining examinations, to establish the reference standard. Diagnostic performance and report turnaround times were compared using Pearson chi-square test and Wilcoxon rank-sum test, respectively. Bonferroni correction was used to account for five diagnostic performance metrics (adjusted significance threshold, .01 [α=.05/5]). Results: A total of 9954 examinations from 7371 patients (mean age, 54.8±19.8 years; 3773 female, 3598 male) were included. In phases 1 and 2, 19.8% (735/3716) and 21.9% (1368/6238) of examinations, respectively, were positive for ICH (P=.01). Radiologists without versus with AI showed no significant difference in accuracy (99.5% vs 99.2%), sensitivity (98.6% vs 98.9%), PPV (99.0% vs 99.7%), or NPV (99.7% vs 99.7%) (all P>.01); specificity was higher for radiologists without than with AI (99.8% vs 99.3%, respectively, P=.004). Mean report turnaround time for ICH-positive examinations was 147.1 minutes without AI versus 149.9 minutes with AI (P=.11). Conclusion: An AI triage system for ICH detection did not improve radiologists' diagnostic performance or report turnaround times. Clinical Impact: This large prospective real-world study does not support use of AI assistance for ICH detection.

Prospective Evaluation of Artificial Intelligence Triage of Incidental Pulmonary Emboli on Contrast-Enhanced CT Examinations of the Chest or Abdomen.

BACKGROUND. Artificial intelligence (AI) algorithms improved detection of incidental pulmonary embolism (IPE) on contrast-enhanced CT (CECT) examinations in retrospective studies; however, prospective validation studies are lacking. OBJECTIVE. The purpose of this study was to assess the effect on radiologists' real-world diagnostic performance and report turnaround times of a radiology department's clinical implementation of an AI triage system for detecting IPE on CECT examinations of the chest or abdomen. METHODS. This prospective single-center study included consecutive adult patients who underwent CECT of the chest or abdomen for reasons other than pulmonary embolism (PE) detection from May 12, 2021, to June 30, 2021 (phase 1), or from September 30, 2021, to December 4, 2021 (phase 2). Before phase 1, the radiology department installed a commercially available AI triage algorithm for IPE detection that automatically processed CT examinations and notified radiologists of positive results through an interactive floating widget. In phase 1, the widget was inactive, and radiologists interpreted examinations without AI assistance. In phase 2, the widget was activated, and radiologists interpreted examinations with AI assistance. A review process involving a panel of radiologists was implemented to establish the reference standard for the presence of IPE. Diagnostic performance and report turnaround times were compared using the Pearson chi-square test and Wilcoxon rank sum test, respectively. RESULTS. Phase 1 included 1467 examinations in 1434 patients (mean age, 53.8 ± 18.5 [SD] years; 753 men, 681 women); phase 2 included 3182 examinations in 2886 patients (mean age, 55.4 ± 18.2 years; 1520 men, 1366 women). The frequency of IPE was 1.4% (20/1467) in phase 1 and 1.6% (52/3182) in phase 2. Radiologists without AI, in comparison to radiologists with AI, showed significantly lower sensitivity (80.0% vs 96.2%, respectively; p = .03), without a significant difference in specificity (99.9% vs 99.9%, p = .58), for the detection of IPE. The mean report turnaround time for IPE-positive examinations was not significantly different between radiologists without AI and radiologists with AI (78.3 vs 74.6 minutes, p = .26). CONCLUSION. An AI triage system improved radiologists' sensitivity for IPE detection on CECT examinations of the chest or abdomen without significant change in report turnaround times. CLINICAL IMPACT. This prospective real-world study supports the use of AI assistance for maximizing IPE detection.

Interpretation time efficiency with radiographs: a comparison study between standard 6 and 12 MP high-resolution display monitors.

Purpose: The purpose of this study is to compare interpretation efficiency of radiologists reading radiographs on 6 megapixel (MP) versus 12 MP monitors. Approach: Our method compares two sets of monitors in two phases: in phase I, radiologists interpreted using a 6 MP, 30.4 in. (Barco Coronis Fusion) and in phase II, a 12 MP, 30.9 in. (Barco Nio Fusion). Nine chest and three musculoskeletal radiologists each batch interpreted an average of 115 radiographs in phase I and 115 radiographs in phase II as a part of routine clinical work. Radiologists were blinded to monitor resolution. Results: Interpretation times per radiograph were noted from dictation logs. Interpretation time was significantly decreased utilizing a 12 MP monitor by 6.88 s ( p = 0.002 ) and 6.76 s (8.7%) ( p < 0.001 ) for chest radiographs only and combined chest and musculoskeletal radiographs, respectively. When evaluating musculoskeletal radiographs alone, the improvement in reading times with 12 MP monitor was 6.76 s, however, this difference was not statistically significant ( p = 0.111 ). Interpretation of radiographs on 12 MP monitors was 8.7% faster than on 6 MP monitors. Conclusion: Higher resolution diagnostic displays can enable radiologists to interpret radiographs more efficiently.

Nine Steps in the Entrepreneurial Journey for Academic Radiologists.

In this article, we explore the nine steps that we have found to be critical for success in our journeys in taking ideas in imaging to commercial products. These nine steps include 1) findings ideas that resonate, 2) protecting your intellectual property, 3) developing a great team that shares in the vision for the product, 4) building a low-fidelity prototype, 5) customer discovery to test your business hypothesis, 6) forming a company, 7) serving on a study section as a prelude to 8) seeking non-dilutive funding, and finally, 9) angel/venture funding.

Prospective Evaluation of AI Triage of Pulmonary Emboli on CT Pulmonary Angiograms.

Background Artificial intelligence (AI) algorithms have shown high accuracy for detection of pulmonary embolism (PE) on CT pulmonary angiography (CTPA) studies in academic studies. Purpose To determine whether use of an AI triage system to detect PE on CTPA studies improves radiologist performance or examination and report turnaround times in a clinical setting. Materials and Methods This prospective single-center study included adult participants who underwent CTPA for suspected PE in a clinical practice setting. Consecutive CTPA studies were evaluated in two phases, first by radiologists alone (n = 31) (May 2021 to June 2021) and then by radiologists aided by a commercially available AI triage system (n = 37) (September 2021 to December 2021). Sixty-two percent of radiologists (26 of 42 radiologists) interpreted studies in both phases. The reference standard was determined by an independent re-review of studies by thoracic radiologists and was used to calculate performance metrics. Diagnostic accuracy and turnaround times were compared using Pearson χ2 and Wilcoxon rank sum tests. Results Phases 1 and 2 included 503 studies (participant mean age, 54.0 years ± 17.8 [SD]; 275 female, 228 male) and 1023 studies (participant mean age, 55.1 years ± 17.5; 583 female, 440 male), respectively. In phases 1 and 2, 14.5% (73 of 503) and 15.9% (163 of 1023) of CTPA studies were positive for PE (P = .47). Mean wait time for positive PE studies decreased from 21.5 minutes without AI to 11.3 minutes with AI (P < .001). The accuracy and miss rate, respectively, for radiologist detection of any PE on CTPA studies was 97.6% and 12.3% without AI and 98.6% and 6.1% with AI, which was not significantly different (P = .15 and P = .11, respectively). Conclusion The use of an AI triage system to detect any PE on CTPA studies improved wait times but did not improve radiologist accuracy, miss rate, or examination and report turnaround times. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Murphy and Tee in this issue.

Lessons Learned in Change Management in Deploying Novel Informatics Solutions: Experience Implementing a Point-of-Care Patient Photography System with Radiography.

We describe implementation of a point-of-care system for simultaneous acquisition of patient photographs along with portable radiographs at a large academic hospital. During the implementation process, we observed several technical challenges in the areas of (1) hardware-automatic triggering for photograph acquisition, camera hardware enclosure, networking, and system server hardware and (2) software-post-processing of photographs. Additionally, we also faced cultural challenges involving workflow issues, communication with technologists and users, and system maintenance. We describe our solutions to address these challenges. We anticipate that these experiences will provide useful insights into deploying and iterating new technologies in imaging informatics.

Ultrasound-Based Grading System for Radiation-Induced Acute Breast Toxicity.

OBJECTIVES: To introduce an ultrasound-based scoring system for radiation-induced breast toxicity and test its reliability. METHODS: Breast ultrasound (BUS) was performed on 32 patients receiving breast radiotherapy (RT) to assess the radiation-induced acute toxicity. For each patient, both the untreated and irradiated breasts were scanned at five locations: 12:00, 3:00, 6:00, 9:00, and tumor bed to evaluate for heterogenous responses to radiation within the entire breast. In total, 314 images were analyzed. Based on ultrasound findings such as skin thickening, dermis boundary irregularity, and subcutaneous edema, a 4-level, Likert-like grading scheme is proposed: none (G0), mild (G1), moderate (G2), and severe (G3) toxicity. Two ultrasound experts graded the severity of breast toxicity independently and reported the inter- and intra-observer reliability of the grading system. Imaging findings were compared with standard clinical toxicity assessments using Common Terminology Criteria for Adverse Events (CTCAE). RESULTS: The inter-observer Pearson correlation coefficient (PCC) was 0.87 (95% CI: 0.83-0.90, P < .001). For intra-observer repeatability, the PCC of the repeated scores was 0.83 (95% CI: 0.78-0.87, P < .001). Imaging findings were compared with standard clinical toxicity assessments using CTCAE scales. The PCC between BUS scores and CTCAE results was 0.62 (95% CI: 0.35-0.80, P < .001). Among all locations, 6:00 and tumor bed showed significantly greater toxicity compared with 12:00 (P = .04). CONCLUSIONS: BUS can investigate the cutaneous and subcutaneous tissue changes after RT. This BUS-based grading system can complement subjective clinical assessments of radiation-induced breast toxicity with cutaneous and subcutaneous sonographic information.

A Thin Transducer With Integrated Acoustic Metamaterial for Cardiac CT Imaging and Gating.

Coronary artery disease (CAD) is a leading cause of death globally. Computed tomography coronary angiography (CTCA) is a noninvasive imaging procedure for diagnosis of CAD. However, CTCA requires cardiac gating to ensure that diagnostic-quality images are acquired in all patients. Gating reliability could be improved by utilizing ultrasound (US) to provide a direct measurement of cardiac motion; however, commercially available US transducers are not computed tomography (CT) compatible. To address this challenge, a CT-compatible 2.5-MHz cardiac phased array transducer is developed via modeling, and then, an initial prototype is fabricated and evaluated for acoustic and radiographic performance. This 92-element piezoelectric array transducer is designed with a thin acoustic backing (6.5 mm) to reduce the volume of the radiopaque acoustic backing that typically causes arrays to be incompatible with CT imaging. This thin acoustic backing contains two rows of air-filled, triangular prism-shaped voids that operate as an acoustic diode. The developed transducer has a bandwidth of 50% and a single-element SNR of 9.9 dB compared to 46% and 14.7 dB for a reference array without an acoustic diode. In addition, the acoustic diode reduces the time-averaged reflected acoustic intensity from the back wall of the acoustic backing by 69% compared to an acoustic backing of the same composition and thickness without the acoustic diode. The feasibility of real-time echocardiography using this array is demonstrated in vivo, including the ability to image the position of the interventricular septum, which has been demonstrated to effectively predict cardiac motion for prospective, low radiation CTCA gating.

Trainee and Faculty Perceptions of Remote PACS Workstations and Next Steps in a Large US Academic Medical Institution.

OBJECTIVE: Remote workstations were rapidly deployed in our academic radiology practice in late March 2020 in response to the COVID-19 pandemic. Although well-received by faculty, there were concerns for the impact on resident education. MATERIALS AND METHODS: Surveys of the radiology trainees and faculty were conducted online seven- and thirteen-months following workstation deployment as a part of a quality improvement project to assess the impact on radiology education and faculty wellness, as well as assess the desired trajectory of remote work in an academic setting. RESULTS: The majority of trainees (52%) reported the implementation had negatively impacted resident education, greatest among lower level residents (p < .001). This perception did not change despite interventions and perceived improvement in teleconferencing. Greater than 75% of radiologists with remote workstations reported improved wellness and lower stress levels compared to the onsite radiologists. The majority of all respondents voted to continue or expand remote work following the COVID-19 pandemic in both surveys. CONCLUSIONS: Onsite teaching is important for the education of residents, particularly for lower-level residents. However, the adoption of a hybrid model in an academic setting may prove beneficial for faculty wellness and recruitment of the next generation.

Coronary computed tomographic angiography: A review of the techniques, protocols, pitfalls, and radiation dose.

Coronary computed tomographic angiography (CCTA) is a viable alternative to catheter coronary angiography for several clinical indications, chiefly because it is fast and non-invasive. For effective clinical use of CCTA, various technical and patient factors should be considered. In this brief review article, we discuss the indication and contraindications for CCTA, technical requirements for CCTA including radiation dose, patient preparation principles, image post-processing, and pitfalls and artifacts of CCTA.

Combining Optical Character Recognition With Paper ECG Digitization.

OBJECTIVE: We propose a MATLAB-based tool to convert electrocardiography (ECG) waveforms from paper-based ECG records into digitized ECG signals that is vendor-agnostic. The tool is packaged as an open source standalone graphical user interface (GUI) based application. METHODS AND PROCEDURES: To reach this objective we: (1) preprocess the ECG records, which includes skew correction, background grid removal and linear filtering; (2) segment ECG signals using Connected Components Analysis (CCA); (3) implement Optical Character Recognition (OCR) for removal of overlapping ECG lead characters and for interfacing of patients' demographic information with their research records or their electronic medical record (EMR). The ECG digitization results are validated through a reader study where clinically salient features, such as intervals of QRST complex, between the paper ECG records and the digitized ECG records are compared. RESULTS: Comparison of clinically important features between the paper-based ECG records and the digitized ECG signals, reveals intra- and inter-observer correlations of 0.86-0.99 and 0.79-0.94, respectively. The kappa statistic was found to average at 0.86 and 0.72 for intra- and inter-observer correlations, respectively. CONCLUSION: The clinically salient features of the ECG waveforms such as the intervals of QRST complex, are preserved during the digitization procedure. Clinical and Healthcare Impact: This open-source digitization tool can be used as a research resource to digitize paper ECG records thereby enabling development of new prediction algorithms to risk stratify individuals with cardiovascular disease, and/or allow for development of ECG-based cardiovascular diagnoses relying upon automated digital algorithms.

Ultrasound-gated computed tomography coronary angiography: Development of ultrasound transducers with improved computed tomography compatibility.

PURPOSE: Cardiovascular disease (CVD) is a leading cause of death worldwide, with coronary artery disease (CAD) accounting for nearly half of all CVD deaths. The current gold standard for CAD diagnosis is catheter coronary angiography (CCA), an invasive, expensive procedure. Computed tomography coronary angiography (CTCA) represents an attractive non-invasive alternative to CCA, however, CTCA requires gated acquisition of CT data during periods of minimal cardiac motion (quiescent periods) to avoid non-diagnostic scans. Current gating methods either expose patients to high levels of radiation (retrospective gating) or lead to high rates of non-diagnostic scans (prospective gating) due to the challenge of predicting cardiac quiescence based on ECG alone. Alternatively, ultrasound (US) imaging has been demonstrated as an effective indicator of cardiac quiescence, however, ultrasound transducers produce prominent streak artifacts that disrupt CTCA scans. In this study, a proof-of-concept array transducer with improved CT-compatibility was developed for utilization in an integrated US-CTCA system. METHODS: Alternative materials were tested radiographically and acoustically to replace the radiopaque acoustic backings utilized in low frequency (1-4 MHz) cardiac US transducers. The results of this testing were used to develop alternative acoustic backings consisting of varying concentrations of aluminum oxide in an epoxy matrix via simulations. On the basis of these simulations, single element test transducers designed to operate at 2.5 MHz were fabricated, and the performance of these devices was characterized via acoustic and radiographic testing with micro-computed tomography (micro-CT). Finally, a first proof-of-concept cardiac phased array transducer was developed and its US imaging performance was evaluated. Micro-CT images of the developed US array with improved CT-compatibility were compared with those of a conventional array. RESULTS: Materials testing with micro-CT identified an acoustic backing with a measured radiopacity of 1008 HU, more than an order of magnitude lower than that of the acoustic backing (24,000 HU) typically used in cardiac transducers operating in the 1-4 MHz range. When utilized in a simulated transducer design, this acoustic backing yielded a -6-dB fractional bandwidth of 57%, similar to the 54% bandwidth of the transducer with the radiopaque acoustic backing. The developed 2.5 MHz, single element transducer based on these simulations exhibited a fractional bandwidth of 51% and signal-to-noise ratio (SNR) of 14.7 dB. Finally, the array transducer developed with the acoustic backing having decreased radiopacity exhibited a 56% fractional bandwidth and 10.4 dB single channel SNR, with penetration depth >10 cm in phantom and in vivo imaging using the full array. CONCLUSIONS: The first attempt at developing a CT-compatible ultrasound transducer is described. The developed CT-compatible transducer exhibits improved radiographic compatibility relative to conventional cardiac array transducers with similar SNR, bandwidth, and penetration depth for US imaging, according to phantom and in vivo cardiac imaging. A CT-compatible US transducer might be used to identify cardiac quiescence and prospectively gate CTCA acquisition, reducing challenges associated with current gating approaches, specifically relatively high rates of non-diagnostic scans for prospective ECG gating and high radiation dose for retrospective gating.

Multiinstitutional U.S. Academic Radiology Perspectives on Inpatient Diagnostic Imaging of Patients With Coronavirus Disease (COVID-19) and Persons Under Investigation.

OBJECTIVE. This article presents the perspectives of radiologists in different sub-specialties at three institutions across the United States regarding inpatient imaging of patients confirmed to have coronavirus disease (COVID-19) and persons under investigation (i.e., patients suspected to have COVID-19). CONCLUSION. The COVID-19 pandemic has prompted radiologists to become aware of imaging findings related to the disease and to develop workflows for the imaging of patients with COVID-19 and persons under investigation, to optimize care for all patients and preserve the health of health care workers.

Rapid Deployment of Home PACS Workstations to Enable Social Distancing in the Coronavirus Disease (COVID-19) Era.

OBJECTIVE. Social distancing is considered an effective mitigation strategy for coronavirus disease (COVID-19), and remote interpretation of radiologic studies is one approach to social distancing within the radiology department. We describe the rapid deployment of home workstations to achieve social distancing in the radiology department at the University of Alabama at Birmingham. CONCLUSION. Transitioning from on-site interpretation to remote interpretation requires a careful balancing of hospital and departmental finances, engineering choices, and educational and philosophical workflow issues.

Initial Experience With Patient Visible Light Images Obtained Simultaneously With Portable Radiographs.

OBJECTIVE. Visible light images in the form of point-of-care photographs obtained at the time of medical imaging can be useful for detecting wrong-patient errors and providing image-related clinical context. Our goal was to implement a system to automatically obtain point-of-care patient photographs along with portable radiographs. CONCLUSION. We discuss one academic medical center's initial experience in integrating the system into the clinical workflow and initial use cases ranging from cardiothoracic and abdominal imaging to musculoskeletal imaging, for which such point-of-care photographs were deemed clinically beneficial.

Interpreting Radiographs with Concurrently Obtained Patient Photographs.

A technology for automatically obtaining patient photographs along with portable radiographs was implemented clinically at a large academic hospital. This article highlights several cases in which image-related clinical context, provided by the patient photographs, provided quality control information regarding patient identification, laterality, or position and assisted the radiologist with the interpretation. The information in the photographs can easily minimize unnecessary calls to the patient's nursing staff for clarifications and can lead to new methods of physically assessing patients. Published under a CC BY 4.0 license.