Intervention for critical aortic stenosis in Hutchinson-Gilford progeria syndrome

Hutchinson-Gilford Progeria Syndrome (HGPS) is an ultra-rare genetic premature aging disease that is historically fatal in teenage years, secondary to severe accelerated atherosclerosis. The only approved treatment is the farnesyltransferase inhibitor lonafarnib, which improves vascular structure and function, extending average untreated lifespan of 14.5 years by 4.3 years (30%). With this longer lifespan, calcific aortic stenosis (AS) was identified as an emerging critical risk factor for cardiac death in older patients. Intervention to relieve critical AS has the potential for immediate improvement in healthspan and lifespan. However, HGPS patient-device size mismatch, pervasive peripheral arterial disease, skin and bone abnormalities, and lifelong failure to thrive present unique challenges to intervention. An international group of experts in HGPS, pediatric and adult cardiology, cardiac surgery, and pediatric critical care convened to identify strategies for successful treatment. Candidate procedures were evaluated by in-depth examination of 4 cases that typify HGPS clinical pathology. Modified transcatheter aortic valve replacement (TAVR) and left ventricular Apico-Aortic Conduit (AAC) placement were deemed high risk but viable options. Two cases received TAVR and 2 received AAC post-summit. Three were successful and 1 patient died perioperatively due to cardiovascular disease severity, highlighting the importance of intervention timing and comparative risk stratification. These breakthrough interventions for treating critical aortic stenosis in HGPS patients could rewrite the current clinical perspective on disease course by greatly improving late-stage quality of life and increasing lifespan. Expanding worldwide medical and surgical competency for this ultra-rare disease through expert information-sharing could have high impact on treatment success.

Clinical situations for which 3D Printing is considered an appropriate representation or extension of data contained in a medical imaging examination: vascular conditions

BACKGROUND

Medical three-dimensional (3D) printing has demonstrated utility and value in anatomic models for vascular conditions. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (3DPSIG) provides appropriateness recommendations for vascular 3D printing indications.

METHODS

A structured literature search was conducted to identify all relevant articles using 3D printing technology associated with vascular indications. Each study was vetted by the authors and strength of evidence was assessed according to published appropriateness ratings.

RESULTS

Evidence-based recommendations for when 3D printing is appropriate are provided for the following areas: aneurysm, dissection, extremity vascular disease, other arterial diseases, acute venous thromboembolic disease, venous disorders, lymphedema, congenital vascular malformations, vascular trauma, vascular tumors, visceral vasculature for surgical planning, dialysis access, vascular research/development and modeling, and other vasculopathy. Recommendations are provided in accordance with strength of evidence of publications corresponding to each vascular condition combined with expert opinion from members of the 3DPSIG.

CONCLUSION

This consensus appropriateness ratings document, created by the members of the 3DPSIG, provides an updated reference for clinical standards of 3D printing for the care of patients with vascular conditions.

Clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: neurosurgical and otolaryngologic conditions

BACKGROUND

Medical three dimensional (3D) printing is performed for neurosurgical and otolaryngologic conditions, but without evidence-based guidance on clinical appropriateness. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (SIG) provides appropriateness recommendations for neurologic 3D printing conditions.

METHODS

A structured literature search was conducted to identify all relevant articles using 3D printing technology associated with neurologic and otolaryngologic conditions. Each study was vetted by the authors and strength of evidence was assessed according to published guidelines.

RESULTS

Evidence-based recommendations for when 3D printing is appropriate are provided for diseases of the calvaria and skull base, brain tumors and cerebrovascular disease. Recommendations are provided in accordance with strength of evidence of publications corresponding to each neurologic condition combined with expert opinion from members of the 3D printing SIG.

CONCLUSIONS

This consensus guidance document, created by the members of the 3D printing SIG, provides a reference for clinical standards of 3D printing for neurologic conditions.

Generalization optimizing machine learning to improve CT scan radiomics and assess immune checkpoint inhibitors' response in non-small cell lung cancer: a multicenter cohort study

Background

Recent developments in artificial intelligence suggest that radiomics may represent a promising non-invasive biomarker to predict response to immune checkpoint inhibitors (ICIs). Nevertheless, validation of radiomics algorithms in independent cohorts remains a challenge due to variations in image acquisition and reconstruction. Using radiomics, we investigated the importance of scan normalization as part of a broader machine learning framework to enable model external generalizability to predict ICI response in non-small cell lung cancer (NSCLC) patients across different centers.

Methods

Radiomics features were extracted and compared from 642 advanced NSCLC patients on pre-ICI scans using established open-source PyRadiomics and a proprietary DeepRadiomics deep learning technology. The population was separated into two groups: a discovery cohort of 512 NSCLC patients from three academic centers and a validation cohort that included 130 NSCLC patients from a fourth center. We harmonized images to account for variations in reconstruction kernel, slice thicknesses, and device manufacturers. Multivariable models, evaluated using cross-validation, were used to estimate the predictive value of clinical variables, PD-L1 expression, and PyRadiomics or DeepRadiomics for progression-free survival at 6 months (PFS-6).

Results

The best prognostic factor for PFS-6, excluding radiomics features, was obtained with the combination of Clinical + PD-L1 expression (AUC = 0.66 in the discovery and 0.62 in the validation cohort). Without image harmonization, combining Clinical + PyRadiomics or DeepRadiomics delivered an AUC = 0.69 and 0.69, respectively, in the discovery cohort, but dropped to 0.57 and 0.52, in the validation cohort. This lack of generalizability was consistent with observations in principal component analysis clustered by CT scan parameters. Subsequently, image harmonization eliminated these clusters. The combination of Clinical + DeepRadiomics reached an AUC = 0.67 and 0.63 in the discovery and validation cohort, respectively. Conversely, the combination of Clinical + PyRadiomics failed generalizability validations, with AUC = 0.66 and 0.59.

Conclusion

We demonstrated that a risk prediction model combining Clinical + DeepRadiomics was generalizable following CT scan harmonization and machine learning generalization methods. These results had similar performances to routine oncology practice using Clinical + PD-L1. This study supports the strong potential of radiomics as a future non-invasive strategy to predict ICI response in advanced NSCLC.

Medical 3D Printing Using Desktop Inverted Vat Photopolymerization: Background, Clinical Applications, and Challenges

Medical 3D printing is a complex, highly interdisciplinary, and revolutionary technology that is positively transforming the care of patients. The technology is being increasingly adopted at the Point of Care (PoC) as a consequence of the strong value offered to medical practitioners. One of the key technologies within the medical 3D printing portfolio enabling this transition is desktop inverted Vat Photopolymerization (VP) owing to its accessibility, high quality, and versatility of materials. Several reports in the peer-reviewed literature have detailed the medical impact of 3D printing technologies as a whole. This review focuses on the multitude of clinical applications of desktop inverted VP 3D printing which have grown substantially in the last decade. The principles, advantages, and challenges of this technology are reviewed from a medical standpoint. This review serves as a primer for the continually growing exciting applications of desktop-inverted VP 3D printing in healthcare.

3D printing exposure and perception in radiology residency: survey results of radiology chief residents

RATIONALE AND OBJECTIVES

The purpose of this study is to summarize a survey of radiology chief residents focused on 3D printing in radiology.

MATERIALS AND METHODS

An online survey was distributed to chief residents in North American radiology residencies by subgroups of the Association of University Radiologists. The survey included a subset of questions focused on the clinical use of 3D printing and perceptions of the role of 3D printing and radiology. Respondents were asked to define the role of 3D printing at their institution and asked about the potential role of clinical 3D printing in radiology and radiology residencies.

RESULTS

152 individual responses from 90 programs were provided, with a 46% overall program response rate (n = 90/194 radiology residencies). Most programs had 3D printing at their institution (60%; n = 54/90 programs). Among the institutions that perform 3D printing, 33% (n = 18/54) have structured opportunities for resident contribution. Most residents (60%; n = 91/152 respondents) feel they would benefit from 3D printing exposure or educational material. 56% of residents (n = 84/151) believed clinical 3D printing should be centered in radiology departments. 22% of residents (n = 34/151) believed it would increase communication and improve relationships between radiology and surgery colleagues. A minority (5%; 7/151) believe 3D printing is too costly, time-consuming, or outside a radiologist's scope of practice.

CONCLUSIONS

A majority of surveyed chief residents in accredited radiology residencies believe they would benefit from exposure to 3D printing in residency. 3D printing education and integration would be a valuable addition to current radiology residency program curricula.

Radiological Society of North America (RSNA) 3D Printing Special Interest Group (SIG) clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: breast conditions

The use of medical 3D printing has expanded dramatically for breast diseases. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (SIG) provides updated appropriateness criteria for breast 3D printing in various clinical scenarios. Evidence-based appropriateness criteria are provided for the following clinical scenarios: benign breast lesions and high-risk breast lesions, breast cancer, breast reconstruction, and breast radiation (treatment planning and radiation delivery).

2022 use of coronary computed tomographic angiography for patients presenting with acute chest pain to the emergency department: An expert consensus document of the Society of cardiovascular computed tomography (SCCT): Endorsed by the American College of Radiology (ACR) and North American Society for cardiovascular Imaging (NASCI)

Coronary computed tomography angiography (CTA) improves the quality of care for patients presenting with acute chest pain (ACP) to the emergency department (ED), particularly in patients with low to intermediate likelihood of acute coronary syndrome (ACS). The Society of Cardiovascular Computed Tomography Guidelines Committee was formed to develop recommendations for acquiring, interpreting, and reporting of coronary CTA to ensure appropriate, safe, and efficient use of this modality. Because of the increasing use of coronary CTA testing for the evaluation of ACP patients, the Committee has been charged with the development of the present document to assist physicians and technologists. These recommendations were produced as an educational tool for practitioners evaluating acute chest pain patients in the ED, in the interest of developing systematic standards of practice for coronary CTA based on the best available data or broad expert consensus. Due to the highly variable nature of medical care, approaches to patient selection, preparation, protocol selection, interpretation or reporting that differs from these guidelines may represent an appropriate variation based on a legitimate assessment of an individual patient's needs.

Utility and Costs During the Initial Year of 3D Printing in an Academic Hospital

OBJECTIVE

There is a paucity of utility and cost data regarding the launch of 3D printing in a hospital. The objective of this project is to benchmark utility and costs for radiology-based in-hospital 3D printing of anatomic models in a single, adult academic hospital.

METHODS

All consecutive patients for whom 3D printed anatomic models were requested during the first year of operation were included. All 3D printing activities were documented by the 3D printing faculty and referring specialists. For patients who underwent a procedure informed by 3D printing, clinical utility was determined by the specialist who requested the model. A new metric for utility termed Anatomic Model Utility Points with range 0 (lowest utility) to 500 (highest utility) was derived from the specialist answers to Likert statements. Costs expressed in United States dollars were tallied from all 3D printing human resources and overhead. Total costs, focused costs, and outsourced costs were estimated. The specialist estimated the procedure room time saved from the 3D printed model. The time saved was converted to dollars using hospital procedure room costs.

RESULTS

The 78 patients referred for 3D printed anatomic models included 11 clinical indications. For the 68 patients who had a procedure, the anatomic model utility points had an overall mean (SD) of 312 (57) per patient (range, 200-450 points). The total operation cost was $213,450. The total cost, focused costs, and outsourced costs were $2,737, $2,180, and $2,467 per model, respectively. Estimated procedure time saved had a mean (SD) of 29.9 (12.1) min (range, 0-60 min). The hospital procedure room cost per minute was $97 (theoretical $2,900 per patient saved with model).

DISCUSSION

Utility and cost benchmarks for anatomic models 3D printed in a hospital can inform health care budgets. Realizing pecuniary benefit from the procedure time saved requires future research.

CAD-RADS™ 2.0 - 2022 Coronary Artery Disease-Reporting and Data System: An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR), and the North America Society of Cardiovascular Imaging (NASCI)

Coronary Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management. The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in cardiac CT, including data from recent clinical trials and new clinical guidelines. The updated CAD-RADS classification will follow an established framework of stenosis, plaque burden, and modifiers, which will include assessment of lesion-specific ischemia using CT fractional-flow-reserve (CT-FFR) or myocardial CT perfusion (CTP), when performed. Similar to the method used in the original CAD-RADS version, the determinant for stenosis severity classification will be the most severe coronary artery luminal stenosis on a per-patient basis, ranging from CAD-RADS 0 (zero) for absence of any plaque or stenosis to CAD-RADS 5 indicating the presence of at least one totally occluded coronary artery. Given the increasing data supporting the prognostic relevance of coronary plaque burden, this document will provide various methods to estimate and report total plaque burden. The addition of P1 to P4 descriptors are used to denote increasing categories of plaque burden. The main goal of CAD-RADS, which should always be interpreted together with the impression found in the report, remains to facilitate communication of test results with referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will continue to provide a framework of standardization that may benefit education, research, peer-review, artificial intelligence development, clinical trial design, population health and quality assurance with the ultimate goal of improving patient care.

CAD-RADS™ 2.0 - 2022 Coronary Artery Disease - Reporting and Data System.: An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR) and the North America Society of Cardiovascular Imaging (NASCI)

Coronary Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management. The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in Cardiac CT, including data from recent clinical trials and new clinical guidelines. The updated CAD-RADS classification will follow an established framework of stenosis, plaque burden, and modifiers, which will include assessment of lesion-specific ischemia using CT fractional-flow-reserve (CT-FFR) or myocardial CT perfusion (CTP), when performed. Similar to the method used in the original CAD-RADS version, the determinant for stenosis severity classification will be the most severe coronary artery luminal stenosis on a per-patient basis, ranging from CAD-RADS 0 (zero) for absence of any plaque or stenosis to CAD-RADS 5 indicating the presence of at least one totally occluded coronary artery. Given the increasing data supporting the prognostic relevance of coronary plaque burden, this document will provide various methods to estimate and report total plaque burden. The addition of P1 to P4 descriptors are used to denote increasing categories of plaque burden. The main goal of CAD-RADS, which should always be interpreted together with the impression found in the report, remains to facilitate communication of test results with referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will continue to provide a framework of standardization that may benefit education, research, peer-review, artificial intelligence development, clinical trial design, population health and quality assurance with the ultimate goal of improving patient care.

ACR Appropriateness Criteria® Suspected Pulmonary Embolism: 2022 Update

Pulmonary embolism (PE) remains a common and important clinical condition that cannot be accurately diagnosed on the basis of signs, symptoms, and history alone. The diagnosis of PE has been facilitated by technical advancements and multidetector CT pulmonary angiography, which is the major diagnostic modality currently used. Ventilation and perfusion scans remain largely accurate and useful in certain settings. MR angiography can be useful in some clinical scenarios and lower-extremity ultrasound can substitute by demonstrating deep vein thrombosis; however, if negative, further studies to exclude PE are indicated. In all cases, correlation with the clinical status, particularly with risk factors, improves not only the accuracy of diagnostic imaging but also overall utilization. Other diagnostic tests have limited roles. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer-reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances in which peer-reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

CAD-RADS™ 2.0 - 2022 Coronary Artery Disease-Reporting and Data System: An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR), and the North America Society of Cardiovascular Imaging (NASCI)

Coronary Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management. The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in Cardiac CT, including data from recent clinical trials and new clinical guidelines. The updated CAD-RADS classification will follow an established framework of stenosis, plaque burden, and modifiers, which will include assessment of lesion-specific ischemia using CT fractional-flow-reserve (CT-FFR) or myocardial CT perfusion (CTP), when performed. Similar to the method used in the original CAD-RADS version, the determinant for stenosis severity classification will be the most severe coronary artery luminal stenosis on a per-patient basis, ranging from CAD-RADS 0 (zero) for absence of any plaque or stenosis to CAD-RADS 5 indicating the presence of at least one totally occluded coronary artery. Given the increasing data supporting the prognostic relevance of coronary plaque burden, this document will provide various methods to estimate and report total plaque burden. The addition of P1 to P4 descriptors are used to denote increasing categories of plaque burden. The main goal of CAD-RADS, which should always be interpreted together with the impression found in the report, remains to facilitate communication of test results with referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will continue to provide a framework of standardization that may benefit education, research, peer-review, artificial intelligence development, clinical trial design, population health and quality assurance with the ultimate goal of improving patient care.

CAD-RADS™ 2.0 - 2022 Coronary Artery Disease - Reporting and Data System An Expert Consensus Document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Cardiology (ACC), the American College of Radiology (ACR) and the North America Society of Cardiovascular Imaging (NASCI)

Coronary Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management. The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in Cardiac CT, including data from recent clinical trials and new clinical guidelines. The updated CAD-RADS classification will follow an established framework of stenosis, plaque burden, and modifiers, which will include assessment of lesion-specific ischemia using CT fractional-flow-reserve (CT-FFR) or myocardial CT perfusion (CTP), when performed. Similar to the method used in the original CAD-RADS version, the determinant for stenosis severity classification will be the most severe coronary artery luminal stenosis on a per-patient basis, ranging from CAD-RADS 0 (zero) for absence of any plaque or stenosis to CAD-RADS 5 indicating the presence of at least one totally occluded coronary artery. Given the increasing data supporting the prognostic relevance of coronary plaque burden, this document will provide various methods to estimate and report total plaque burden. The addition of P1 to P4 descriptors are used to denote increasing categories of plaque burden. The main goal of CAD-RADS, which should always be interpreted together with the impression found in the report, remains to facilitate communication of test results with referring physicians along with suggestions for subsequent patient management. In addition, CAD-RADS will continue to provide a framework of standardization that may benefit education, research, peer-review, artificial intelligence development, clinical trial design, population health and quality assurance with the ultimate goal of improving patient care. Keywords: Coronary Artery Disease, Coronary CTA, CAD-RADS, Reporting and Data System, Stenosis Severity, Report Standardization Terminology, Plaque Burden, Ischemia Supplemental material is available for this article. This article is published synchronously in Radiology: Cardiothoracic Imaging, Journal of Cardiovascular Computed Tomography, JACC: Cardiovascular Imaging, Journal of the American College of Radiology, and International Journal for Cardiovascular Imaging. © 2022 Society of Cardiovascular Computed Tomography. Published by RSNA with permission.

Evaluation of a deep learning method for the automated detection of supraspinatus tears on MRI

OBJECTIVE

To evaluate if deep learning is a feasible approach for automated detection of supraspinatus tears on MRI.

MATERIALS AND METHODS

A total of 200 shoulder MRI studies performed between 2015 and 2019 were retrospectively obtained from our institutional database using a balanced random sampling of studies containing a full-thickness tear, partial-thickness tear, or intact supraspinatus tendon. A 3-stage pipeline was developed comprised of a slice selection network based on a pre-trained residual neural network (ResNet); a segmentation network based on an encoder-decoder network (U-Net); and a custom multi-input convolutional neural network (CNN) classifier. Binary reference labels were created following review of radiologist reports and images by a radiology fellow and consensus validation by two musculoskeletal radiologists. Twenty percent of the data was reserved as a holdout test set with the remaining 80% used for training and optimization under a fivefold cross-validation strategy. Classification and segmentation accuracy were evaluated using area under the receiver operating characteristic curve (AUROC) and Dice similarity coefficient, respectively. Baseline characteristics in correctly versus incorrectly classified cases were compared using independent sample t-test and chi-squared.

RESULTS

Test sensitivity and specificity of the classifier at the optimal Youden's index were 85.0% (95% CI: 62.1-96.8%) and 85.0% (95% CI: 62.1-96.8%), respectively. AUROC was 0.943 (95% CI: 0.820-0.991). Dice segmentation accuracy was 0.814 (95% CI: 0.805-0.826). There was no significant difference in AUROC between 1.5 T and 3.0 T studies. Sub-analysis showed superior sensitivity on full-thickness (100%) versus partial-thickness (72.5%) subgroups.

DATA CONCLUSION

Deep learning is a feasible approach to detect supraspinatus tears on MRI.

Medical 3D Printing Dimensional Accuracy for Multi-pathological Anatomical Models 3D Printed Using Material Extrusion

Medical 3D printing of anatomical models is being increasingly applied in healthcare facilities. The accuracy of such 3D-printed anatomical models is an important aspect of their overall quality control. The purpose of this research was to test whether the accuracy of a variety of anatomical models 3D printed using Material Extrusion (MEX) lies within a reasonable tolerance level, defined as less than 1-mm dimensional error. Six medical models spanning across anatomical regions (musculoskeletal, neurological, abdominal, cardiovascular) and sizes (model volumes ranging from ~ 4 to 203 cc) were chosen for the primary study. Three measurement landing blocks were strategically designed within each of the six medical models to allow high-resolution caliper measurements. An 8-cc reference cube was printed as the 7th model in the primary study. In the secondary study, the effect of model rotation and scale was assessed using two of the models from the first study. All models were 3D printed using an Ultimaker 3 printer in triplicates. All absolute measurement errors were found to be less than 1 mm with a maximum error of 0.89 mm. The maximum relative error was 2.78%. The average absolute error was 0.26 mm, and the average relative error was 0.71% in the primary study, and the results were similar in the secondary study with an average absolute error of 0.30 mm and an average relative error of 0.60%. The relative errors demonstrated certain patterns in the data, which were explained based on the mechanics of MEX 3D printing. Results indicate that the MEX process, when carefully assessed on a case-by-case basis, could be suitable for the 3D printing of multi-pathological anatomical models for surgical planning if an accuracy level of 1 mm is deemed sufficient for the application.

A Metrics-Based Research Salary Award System and Its 9-Year Impact on Publication Productivity

RATIONALE AND OBJECTIVES

Although metrics-based systems may incentivize academic output, no prior studies have evaluated the impact on publication metrics in academic radiology. This study presents a metrics-based system of awarding research protected time, and retrospectively evaluates its 9-year impact on publication productivity and impact factor.

MATERIALS AND METHODS

Based on a metrics-based algorithm to award department funded Research Protected Time (RPT), metrics pre-RPT (2003-2009) and during the RPT period (2010-2018) from an academic radiology department were retrospectively analyzed to test the hypothesis that the RPT program resulted in higher publication productivity and journal impact factor at the departmental level and for faculty members receiving the award. Comparison was made between (1) pre-RPT and RPT periods and (2) during the RPT period, between RPT and non-RPT faculty members, for annual publication productivity normalized to faculty count (Student's t test) and median impact factor (Wilcoxon rank sum test).

RESULTS

For the evaluation period of 2003-2018, 724 unique publications were identified: 15% (107/724) pre-RPT period and 85% (617/724) RPT period. Normalized annual publication productivity was higher during the RPT period compared to the Pre-RPT period (1.2 vs. 0.3, p = 0.002), and within the RPT period, higher among faculty who received RPT vs. non-RPT faculty (3.5 vs. 0.4, p = 0.002). Median impact factor was higher during the RPT period compared to pre-RPT period (2.843 vs. 2.322, p = 0.044), and within the RPT period, higher in RPT vs. non-RPT faculty (3.016 vs. 2.346, p < 0.001).

CONCLUSION

The implementation of a metrics-based system of funded, research protected time, was associated with increased publication productivity and increased impact factor.

RadioGraphics Update: Medical 3D Printing for the Radiologist

Editor's Note.-Articles in the RadioGraphics Update section provide current knowledge to supplement or update information found in full-length articles previously published in RadioGraphics. Authors of the previously published article provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes. Articles in this section are published solely online and are linked to the original article.

Prognostic value of noninvasive combined anatomic/functional assessment by cardiac CT in patients with suspected coronary artery disease - Comparison with invasive coronary angiography and nuclear myocardial perfusion imaging for the five-year-follow up of the CORE320 multicenter study

BACKGROUND

Few data exist on long-term outcome in patients undergoing combined coronary CT angiography (CTA) and myocardial CT perfusion imaging (CTP) as well as invasive coronary angiography (ICA) and single photon emission tomography (SPECT).

METHODS

At 16 centers, 381 patients were followed for major adverse cardiac events (MACE) for the CORE320 study. All patients underwent coronary CTA, CTP, and SPECT before ICA within 60 days. Prognostic performance according binary results (normal/abnormal) was assessed by 5-year major cardiovascular events (MACE) free survival and area under the receiver-operating-characteristic curve (AUC).

RESULTS

Follow up beyond 2-years was available in 323 patients. MACE-free survival rate was greater among patients with normal combined CTA-CTP findings compared to ICA-SPECT: 85 vs. 80% (95% confidence interval [CI] for difference 0.1, 11.3) though event-free survival time was similar (4.54 vs. 4.37 years, 95% CI for difference: -0.03, 0.36). Abnormal results by combined CTA-CTP was associated with 3.83 years event-free survival vs. 3.66 years after abnormal combined ICA-SPECT (95% CI for difference: -0.05, 0.39). Predicting MACE by AUC also was similar: 65 vs. 65 (difference 0.1; 95% CI -4.6, 4.9). When MACE was restricted to cardiovascular death, myocardial infarction, or stroke, AUC for CTA-CTP was 71 vs. 60 by ICA-SPECT (difference 11.2; 95% CI -1.0, 19.7).

CONCLUSIONS

Combined CTA-CTP evaluation yields at least equal 5-year prognostic information as combined ICA-SPECT assessment in patients presenting with suspected coronary artery disease. Noninvasive cardiac CT assessment may eliminate the need for diagnostic cardiac catheterization in many patients.

CLINICAL TRIAL REGISTRATION

NCT00934037.

A systematic evaluation of medical 3D printing accuracy of multi-pathological anatomical models for surgical planning manufactured in elastic and rigid material using desktop inverted vat photopolymerization

PURPOSE

The dimensional accuracy of three-dimensional (3D) printed anatomical models is essential to correctly understand spatial relationships and enable safe presurgical planning. Most recent accuracy studies focused on 3D printing of a single pathology for surgical planning. This study evaluated the accuracy of medical models across multiple pathologies, using desktop inverted vat photopolymerization (VP) to 3D print anatomic models using both rigid and elastic materials.

METHODS

In the primary study, we 3D printed seven models (six anatomic models and one reference cube) with volumes ranging from ~2 to ~209 cc. The anatomic models spanned multiple pathologies (neurological, cardiovascular, abdominal, musculoskeletal). Two solid measurement landing blocks were strategically created around the pathology to allow high-resolution measurement using a digital micrometer and/or caliper. The physical measurements were compared to the designed dimensions, and further analysis was conducted regarding the observed patterns in accuracy. All of the models were printed in three resins: Elastic, Clear, and Grey Pro in the primary experiments. A full factorial block experimental design was employed and a total of 42 models were 3D printed in 21 print runs. In the secondary study, we 3D printed two of the anatomic models in triplicates selected from the previous six to evaluate the effect of 0.1 mm vs 0.05 mm layer height on the accuracy.

RESULTS

In the primary experiment, all dimensional errors were less than 1 mm. The average dimensional error across the 42 models was 0.238  ±  0.219 mm and the relative error was 1.10  ±  1.13%. Results from the secondary experiments were similar with an average dimensional error of 0.252  ±  0.213 mm and relative error of 1.52%  ±  1.28% across 18 models. There was a statistically significant difference in the relative errors between the Elastic resin and Clear resin groups. We explained this difference by evaluating inverted VP 3D printing peel forces. There was a significant difference between the Solid and Hollow group of models. There was a significant difference between measurement landing blocks oriented Horizontally and Vertically. In the secondary experiments, there was no difference in accuracy between the 0.10 and 0.05 mm layer heights.

CONCLUSIONS

The maximum measured error was less than 1 mm across all models, and the mean error was less than 0.26mm. Therefore, inverted VP 3D printing technology is suitable for medical 3D printing if 1 mm is considered the cutoff for clinical use cases. The 0.1 mm layer height is suitable for 3D printing accurate anatomical models for presurgical planning in a majority of cases. Elastic models, models oriented horizontally, and models that are hollow tend to have relatively higher deviation as seen from experimental results and mathematical model predictions. While clinically insignificant using a 1 mm cutoff, further research is needed to better understand the complex physical interactions in VP 3D printing which influence model accuracy.

Analysis of Gender Disparity in US and Canadian Radiology Residency Programs

BACKGROUND

Equity, diversity, and inclusion in academic radiology are a work in progress and although the gender gap has decreased, there remains a paucity of studies examining female representation among radiology trainees over the past decade.

OBJECTIVE

The aim of our undertaking was to evaluate gender parity in United States (US) and Canadian radiology residency programs and to suggest future directions to improve female representation MATERIALS AND METHODS: Retrospective analysis of publicly available data on radiology residents from the US and Canada was performed from 2007to 2019. Data on diagnostic radiology residents was collected from the Accreditation Council for Graduate Medical Education for the US and the Canadian Post M.D. Education Registry for Canada. Statistical tests including regression and ANOVA were used to study the gender proportions from 2007to 2019.

RESULTS

There has been little progress in bridging the gender gap in the last 12 years. The proportion of female residents pursuing radiology has remained at an average of 26.74% (n = 1,238of 4,629) in US programs and 31.78% (n = 28 of88) in Canadian programs. The average change in the percentage of female residents was 0.0% per year (P = 0.0) for US programs and -2.9% per year (P = 0.3) for Canadian programs.

DISCUSSION

Despite a higher proportion of females in North American medical schools, gender disparity persists among radiology residents. More research is needed to identify barriers limiting female representation and improve gender parity across North American radiology programs.

Recover Wisely From COVID-19: Responsible Resumption of Nonurgent Radiology Services

Rationale and Objectives

Following state and institutional guidelines, our Radiology department launched the “Recover Wisely” for all nonurgent radiology care on May 4, 2020. Our objective is to report our practice implementation and experience of COVID-19 recovery during the resumption of routine imaging at a tertiary academic medical center.

Materials and Methods

We used the SQUIRE 2.0 guidelines for this practice implementation. Recover Wisely focused on a data driven, strategic rescheduling and redesigning patient flow process. We used scheduling simulations and meticulous monitoring and control of outpatient medical imaging volumes to achieve a linear restoration to our pre-COVID imaging studies. We had a tiered plan to address the backlog of rescheduled patients with gradual opening of our imaging facilities, while maintaining broad communication with our patients and referring clinicians.

Results

Recover Wisely followed our anticipated linear modeling. Considering the last 10 weeks in the recovery, outpatient growth was linear with an increase of approximately 172 cases per week, (R² =0.97). We achieved an overall recovery of 102% in week 10, as compared to average weekly pre-COVID outpatient volumes. The modalities recovered as follows in outpatient volumes: CT (113%), MRI (101%), nuclear medicine including PET (138%), mammograms (97%), ultrasound (99%) and interventional radiology (106%). When compared to identical 2019 calendar weeks (May 4, 2020–July 10, 2020), the total 2020 radiology volume was 11% reduced from the 2019 volume. The reduction in total weighted relative value units was 8% in this time period, as compared to 2019.

Conclusion

Our department utilized a data-driven, team approach based on our guiding principles to “Recover Wisely.” We created and implemented a methodology that achieved a linear increase in outpatient studies over a 10-week recovery period.

Clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: adult cardiac conditions

BACKGROUND

Medical 3D printing as a component of care for adults with cardiovascular diseases has expanded dramatically. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (SIG) provides appropriateness criteria for adult cardiac 3D printing indications.

METHODS

A structured literature search was conducted to identify all relevant articles using 3D printing technology associated with a number of adult cardiac indications, physiologic, and pathologic processes. Each study was vetted by the authors and graded according to published guidelines.

RESULTS

Evidence-based appropriateness guidelines are provided for the following areas in adult cardiac care; cardiac fundamentals, perioperative and intraoperative care, coronary disease and ischemic heart disease, complications of myocardial infarction, valve disease, cardiac arrhythmias, cardiac neoplasm, cardiac transplant and mechanical circulatory support, heart failure, preventative cardiology, cardiac and pericardial disease and cardiac trauma.

CONCLUSIONS

Adoption of common clinical standards regarding appropriate use, information and material management, and quality control are needed to ensure the greatest possible clinical benefit from 3D printing. This consensus guideline document, created by the members of the RSNA 3D printing Special Interest Group, will provide a reference for clinical standards of 3D printing for adult cardiac indications.

Medical 3D Printing Cost-Savings in Orthopedic and Maxillofacial Surgery: Cost Analysis of Operating Room Time Saved with 3D Printed Anatomic Models and Surgical Guides

RATIONALE AND OBJECTIVE

Three-dimensional (3D) printed anatomic models and surgical guides have been shown to reduce operative time. The purpose of this study was to generate an economic analysis of the cost-saving potential of 3D printed anatomic models and surgical guides in orthopedic and maxillofacial surgical applications.

MATERIALS AND METHODS

A targeted literature search identified operating room cost-per-minute and studies that quantified time saved using 3D printed constructs. Studies that reported operative time differences due to 3D printed anatomic models or surgical guides were reviewed and cataloged. A mean of $62 per operating room minute (range of $22-$133 per minute) was used as the reference standard for operating room time cost. Different financial scenarios were modeled with the provided cost-per-minute of operating room time (using high, mean, and low values) and mean time saved using 3D printed constructs.

RESULTS

Seven studies using 3D printed anatomic models in surgical care demonstrated a mean 62 minutes ($3720/case saved from reduced time) of time saved, and 25 studies of 3D printed surgical guides demonstrated a mean 23 minutes time saved ($1488/case saved from reduced time). An estimated 63 models or guides per year (or 1.2/week) were predicted to be the minimum number to breakeven and account for annual fixed costs.

CONCLUSION

Based on the literature-based financial analyses, medical 3D printing appears to reduce operating room costs secondary to shortening procedure times. While resource-intensive, 3D printed constructs used in patients' operative care provides considerable downstream value to health systems.

RadioGraphics Update: Medical 3D Printing for the Radiologist

Editor's Note.-Articles in the RadioGraphics Update section provide current knowledge to supplement or update information found in full-length articles previously published in RadioGraphics. Authors of the previously published article provide a brief synopsis that emphasizes important new information such as technological advances, revised imaging protocols, new clinical guidelines involving imaging, or updated classification schemes. Articles in this section are published solely online and are linked to the original article.

Rescheduling Nonurgent Care in Radiology: Implementation During the Coronavirus Disease 2019 (COVID-19) Pandemic

OBJECTIVE

To meet hospital preparedness for the coronavirus disease 2019 pandemic, the Centers for Disease Control and Prevention and ACR recommended delay of all nonemergent tests and elective procedures. The purpose of this article is to report our experience for rescheduling nonemergent imaging and procedures during the pandemic at our tertiary academic institution.

METHODS

We rescheduled the nonemergent imaging and procedures in our hospitals and outpatient centers from March 16 to May 4, 2020. We created a tiered priority system to reschedule patients for whom imaging could be delayed with minimal clinical impact. The radiologists performed detailed chart reviews for decision making. We conducted daily virtual huddles with discussion of rescheduling strategies and issue tracking.

RESULTS

Using a snapshot during the rescheduling period, there was a 53.4% decrease in imaging volume during the period of March 16 to April 15, 2020, compared with the same time period in 2019. The total number of imaging studies decreased from 38,369 in 2019 to 17,891 in 2020 during this period. Although we saw the largest reduction in outpatient imaging (72.3%), there was also a significant decrease in inpatient (40.5%) and emergency department (48.9%) imaging volumes.

DISCUSSION

The use of multiple communication channels was critical in relaying the information to all our stakeholders, patients, referring physicians, and the radiology workforce. Teamwork, quick adoption, and adaptation of changing strategies was important given the fluidity of the situation.

Radiological Society of North America (RSNA) 3D Printing Special Interest Group (SIG) clinical situations for which 3D printing is considered an appropriate representation or extension of data contained in a medical imaging examination: abdominal, hepatobiliary, and gastrointestinal conditions

Background

Medical 3D printing has demonstrated value in anatomic models for abdominal, hepatobiliary, and gastrointestinal conditions. A writing group composed of the Radiological Society of North America (RSNA) Special Interest Group on 3D Printing (SIG) provides appropriateness criteria for abdominal, hepatobiliary, and gastrointestinal 3D printing indications.

Methods

A literature search was conducted to identify all relevant articles using 3D printing technology associated with a number of abdominal pathologic processes. Each included study was graded according to published guidelines.

Results

Evidence-based appropriateness guidelines are provided for the following areas: intra-hepatic masses, hilar cholangiocarcinoma, biliary stenosis, biliary stones, gallbladder pathology, pancreatic cancer, pancreatitis, splenic disease, gastric pathology, small bowel pathology, colorectal cancer, perianal fistula, visceral trauma, hernia, abdominal sarcoma, abdominal wall masses, and intra-abdominal fluid collections.

Conclusion

This document provides initial appropriate use criteria for medical 3D printing in abdominal, hepatobiliary, and gastrointestinal conditions.

Patient-specific 3D-printed coronary models based on coronary computed tomography angiography volumes to investigate flow conditions in coronary artery disease

BACKGROUND

3D printed patient-specific coronary models have the ability to enable repeatable benchtop experiments under controlled blood flow conditions. This approach can be applied to CT-derived patient geometries to emulate coronary flow and related parameters such as Fractional Flow Reserve (FFR).

METHODS

This study uses 3D printing to compare such benchtop FFR results with a non-invasive CT-FFR research software algorithm and catheter based invasive FFR (I-FFR) measurements. Fifty-two patients with a clinical indication for I-FFR underwent a research Coronary CT Angiography (CCTA) prior to catheterization. CT images were used to measure CT-FFR and to generate patient-specific 3D printed models of the aortic root and three main coronary arteries. Each patient-specific model was connected to a programmable pulsatile pump and benchtop FFR (B-FFR) was derived from pressures measured proximal and distal to coronary stenosis using pressure transducers. B-FFR was measured for two coronary outflow rates ('normal', 250 ml min^-1; and 'hyperemic', 500 ml min^-1) by adjusting the model's distal coronary resistance.

RESULTS

Pearson correlations and ROC AUC were calculated using invasive I-FFR as reference. The Pearson correlation factor of CT-FFR and B-FFR-500 was 0.75 and 0.71, respectively. Areas under the ROCs for CT-FFR and B-FFR-500 were 0.80 (95%CI: 0.70-0.87) and 0.81 (95%CI: 0.64-0.91) respectively.

CONCLUSION

Benchtop flow simulations with 3D printed models provide the capability to measure pressure changes at any location in the model, for ultimately emulating the FFR at several simulated physiological blood flow conditions.

CLINICAL TRIAL REGISTRATION

https://clinicaltrials.gov/show/NCT03149042.

Lack of Gender Disparity Among Administrative Leaders of Canadian Health Authorities

Background: Gender distribution within the managing bodies of the Canadian health authorities has not been studied despite their integral role in the health care system. The purpose of this study is to quantify gender differences and to craft a geographic gender analysis of such distribution. Methods: Retrospective data collection of all Canadian health authorities at the provincial, territorial, regional, and first nations levels was conducted. The dependent variable was gender, and other covariates, where applicable, included province/territory, region, leadership position, education (PhD or Master's), honorary degree, and primary occupation. Any member within the executive managing body or board of directors of a Canadian health authority was included, unless their gender could not be determined, in which case they were excluded. Results: Quantitative analysis of the 67 health authorities revealed 1346 individuals with identifiable gender (710 women; 636 men). Thematic distribution showed no significant difference in the gender distribution by provinces/territories (chi square = 14.248; p = 0.28), by leadership position (chi square = 1.88; p = 0.75), by education (chi square = 1.85; p = 0.17), or by primary occupation (chi square = 1.53; p = 0.46). Conclusion: The overall number of females exceeded that of males and there were no gender disparities. Critical analysis of probable causes was discussed. Further studies should be conducted to examine the policies and programs within the Canadian health authorities that successfully tackle the retention, recruitment, and promotion of females.

Left Ventricular Mid-Diastolic Wall Thickness: Normal Values for Coronary CT Angiography

Purpose

To generate normal reference values for left ventricular mid-diastolic wall thickness (LV-MDWT) measured by using CT angiography.

Materials and Methods

LV-MDWT was measured in 2383 consecutive patients, without structural heart disease, undergoing prospective electrocardiographically (ECG) triggered mid-diastolic coronary CT angiography. LV-MDWT was manually measured on automatically segmented short-axis images according to the American Heart Association's 17-segment model. Commercially available automatic software was used to calculate the left ventricular (LV) mass.

Results

Among the 2383 patients, average LV-MDWT was 7.24 mm ± 1.86 (standard deviation [SD]), with the basal anteroseptal segment being the thickest wall (8.71 mm ± 2.19) and the apical inferior segment being the thinnest wall (5.9 mm ± 1.58; P < .001). Over all LV segments, the maximum upper limit, as defined as 2 SD above the mean, was 13.6 mm for men (LV1) and 11.2 mm for women. For men, only the basal anterior segment was above 13 mm. There was a significant difference in average LV-MDWT between women and men with 6.47 mm ± 1.07 and 7.90 mm ± 1.24, respectively (P < .001). Significant differences in LV-MDWT were found in the subgroups aged less than 65 years and greater than or equal to 65 years (P < .001). There was a strong correlation between LV-MDWT and LV mass (P < .001).

Conclusion

Normal sex- and age-specific reference ranges for LV-MDWT in prospective ECG-triggered mid-diastolic coronary CT angiography have been provided. These benchmarks may expand the diagnostic and prognostic roles of CT angiography, beyond its role in the identification of coronary artery disease.© RSNA, 2019.

EXTraction of EMR numerical data: an efficient and generalizable tool to EXTEND clinical research

Background

Electronic medical records (EMR) contain numerical data important for clinical outcomes research, such as vital signs and cardiac ejection fractions (EF), which tend to be embedded in narrative clinical notes. In current practice, this data is often manually extracted for use in research studies. However, due to the large volume of notes in datasets, manually extracting numerical data often becomes infeasible. The objective of this study is to develop and validate a natural language processing (NLP) tool that can efficiently extract numerical clinical data from narrative notes.

Results

To validate the accuracy of the tool EXTraction of EMR Numerical Data (EXTEND), we developed a reference standard by manually extracting vital signs from 285 notes, EF values from 300 notes, glycated hemoglobin (HbA1C), and serum creatinine from 890 notes. For each parameter of interest, we calculated the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and F₁ score of EXTEND using two metrics.

(1) completion of data extraction, and (2) accuracy of data extraction compared to the actual values in the note verified by chart review. At the note level, extraction by EXTEND was considered correct only if it accurately detected and extracted all values of interest in a note.

Using manually-annotated labels as the gold standard, the note-level accuracy of EXTEND in capturing the numerical vital sign values, EF, HbA1C and creatinine ranged from 0.88 to 0.95 for sensitivity, 0.95 to 1.0 for specificity, 0.95 to 1.0 for PPV, 0.89 to 0.99 for NPV, and 0.92 to 0.96 in F₁ scores. Compared to the actual value level, the sensitivity, PPV, and F₁ score of EXTEND ranged from 0.91 to 0.95, 0.95 to 1.0 and 0.95 to 0.96.

Conclusions

EXTEND is an efficient, flexible tool that uses knowledge-based rules to extract clinical numerical parameters with high accuracy. By increasing dictionary terms and developing new rules, the usage of EXTEND can easily be expanded to extract additional numerical data important in clinical outcomes research.

Point of Care Clinical Risk Score to Improve the Negative Diagnostic Utility of an Agatston Score of Zero: Averting the Need for Coronary Computed Tomography Angiography

BACKGROUND

Coronary artery calcification is a marker of underlying atherosclerotic vascular disease. The absence of coronary artery calcification is associated with a low prevalence of obstructive coronary artery disease (CAD), but it cannot be ruled out completely. We sought to develop a clinical tool that can be added to Agatston score of zero to rule out obstructive CAD with high accuracy.

METHODS

We developed a clinical score retrospectively from a cohort of 4903 consecutive patients with an Agatston score of zero. Patients with prior diagnosis of CAD, coronary percutaneous coronary intervention, or surgical revascularization were excluded. Obstructive CAD was defined as any epicardial vessel diameter narrowing of ≥50%. The score was validated using an external cohort of 4290 patients with an Agatston score of zero from a multinational registry.

RESULTS

The score consisted of 7 variables: age, sex, typical chest pain, dyslipidemia, hypertension, family history, and diabetes mellitus. The model was robust with an area under the curve of 0.70 (95% CI, 0.65-0.76) in the derivation cohort and 0.69 (95% CI, 0.65-0.72) in the validation cohort. Patients were divided into 3 risk groups based on the score: low (≤6), intermediate (7-13), and high (≥14). Patients who score ≤6 have a negative likelihood ratio of 0.42 for obstructive CAD, whereas those who score ≥14 have a positive likelihood ratio of >5.5 for obstructive CAD. The outcome was ruled out in >98% of patients with a score ≤6 in the validation cohort.

CONCLUSIONS

We developed a score that may be used to identify the likelihood of obstructive CAD in patients with an Agatston score of zero, which may be used to direct the need for additional testing. However, the results of this retrospective analysis are hypothesis generating and before clinical implementation should be validated in a trial with a prospectively collected data.

Inter- and Intraoperator Variability in Measurement of On-Site CT-derived Fractional Flow Reserve Based on Structural and Fluid Analysis: A Comprehensive Analysis

Purpose

To measure the inter- and intraobserver variability among operators of varying expertise in conducting CT-derived fractional flow reserve (CT FFR) measurements on-site by using structural and fluid analysis and to evaluate differences in reproducibility between two different training methods for end users.

Materials and Methods

This retrospective analysis of the prospectively enrolled cohort included 22 symptomatic patients who underwent both 320-detector row coronary CT angiography and catheter-derived fractional flow reserve (FFR) within 90 days. Thirteen operators of varying expertise were assigned to one of two training arms: arm 1, on-site training by a specialist in CT FFR technology; arm 2, self-training through use of written materials. After the training, all 13 operators reviewed the CT data and measured CT FFR in 24 vessels in 22 patients. Inter- and intraoperator variability and agreements between CT FFR and catheter-derived FFR measurements were evaluated.

Results

The overall intraclass correlation coefficient (ICC) among operators was 0.71 (95% confidence interval: 0.58, 0.83) with a mean absolute difference (± standard deviation) of 0.027 ± 0.022. The operators in arm 2 showed greater interoperator differences than those in arm 1 (0.031 ± 0.024 vs 0.023 ± 0.018; P = .024). Among operators who recalculated CT FFR, the mean CT FFR value did not significantly differ between the first and second calculations (ICC, 0.66; 95% confidence interval: 0.46, 0.87), with the medical specialists producing the lowest intraoperator variability (0.053 ± 0.060). The overall correlation coefficient between CT FFR and catheter FFR was r = 0.61, with a mean absolute difference of 0.096 ± 0.089.

Conclusion

Good reproducibility of CT FFR values calculated on-site on the basis of structural and fluid analysis was observed among operators of varying expertise. Face-to-face training sessions may cause less variability.© RSNA, 2019Supplemental material is available for this article.

Diagnosis of obstructive coronary artery disease using computed tomography angiography in patients with stable chest pain depending on clinical probability and in clinically important subgroups: meta-analysis of individual patient data

OBJECTIVE

To determine whether coronary computed tomography angiography (CTA) should be performed in patients with any clinical probability of coronary artery disease (CAD), and whether the diagnostic performance differs between subgroups of patients.

DESIGN

Prospectively designed meta-analysis of individual patient data from prospective diagnostic accuracy studies.

DATA SOURCES

Medline, Embase, and Web of Science for published studies. Unpublished studies were identified via direct contact with participating investigators.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Prospective diagnostic accuracy studies that compared coronary CTA with coronary angiography as the reference standard, using at least a 50% diameter reduction as a cutoff value for obstructive CAD. All patients needed to have a clinical indication for coronary angiography due to suspected CAD, and both tests had to be performed in all patients. Results had to be provided using 2×2 or 3×2 cross tabulations for the comparison of CTA with coronary angiography. Primary outcomes were the positive and negative predictive values of CTA as a function of clinical pretest probability of obstructive CAD, analysed by a generalised linear mixed model; calculations were performed including and excluding non-diagnostic CTA results. The no-treat/treat threshold model was used to determine the range of appropriate pretest probabilities for CTA. The threshold model was based on obtained post-test probabilities of less than 15% in case of negative CTA and above 50% in case of positive CTA. Sex, angina pectoris type, age, and number of computed tomography detector rows were used as clinical variables to analyse the diagnostic performance in relevant subgroups.

RESULTS

Individual patient data from 5332 patients from 65 prospective diagnostic accuracy studies were retrieved. For a pretest probability range of 7-67%, the treat threshold of more than 50% and the no-treat threshold of less than 15% post-test probability were obtained using CTA. At a pretest probability of 7%, the positive predictive value of CTA was 50.9% (95% confidence interval 43.3% to 57.7%) and the negative predictive value of CTA was 97.8% (96.4% to 98.7%); corresponding values at a pretest probability of 67% were 82.7% (78.3% to 86.2%) and 85.0% (80.2% to 88.9%), respectively. The overall sensitivity of CTA was 95.2% (92.6% to 96.9%) and the specificity was 79.2% (74.9% to 82.9%). CTA using more than 64 detector rows was associated with a higher empirical sensitivity than CTA using up to 64 rows (93.4% v 86.5%, P=0.002) and specificity (84.4% v 72.6%, P<0.001). The area under the receiver-operating-characteristic curve for CTA was 0.897 (0.889 to 0.906), and the diagnostic performance of CTA was slightly lower in women than in with men (area under the curve 0.874 (0.858 to 0.890) v 0.907 (0.897 to 0.916), P<0.001). The diagnostic performance of CTA was slightly lower in patients older than 75 (0.864 (0.834 to 0.894), P=0.018 v all other age groups) and was not significantly influenced by angina pectoris type (typical angina 0.895 (0.873 to 0.917), atypical angina 0.898 (0.884 to 0.913), non-anginal chest pain 0.884 (0.870 to 0.899), other chest discomfort 0.915 (0.897 to 0.934)).

CONCLUSIONS

In a no-treat/treat threshold model, the diagnosis of obstructive CAD using coronary CTA in patients with stable chest pain was most accurate when the clinical pretest probability was between 7% and 67%. Performance of CTA was not influenced by the angina pectoris type and was slightly higher in men and lower in older patients.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO CRD42012002780.

Canadian Association of Radiologists White Paper on Ethical and Legal Issues Related to Artificial Intelligence in Radiology

Artificial intelligence (AI) software that analyzes medical images is becoming increasingly prevalent. Unlike earlier generations of AI software, which relied on expert knowledge to identify imaging features, machine learning approaches automatically learn to recognize these features. However, the promise of accurate personalized medicine can only be fulfilled with access to large quantities of medical data from patients. This data could be used for purposes such as predicting disease, diagnosis, treatment optimization, and prognostication. Radiology is positioned to lead development and implementation of AI algorithms and to manage the associated ethical and legal challenges. This white paper from the Canadian Association of Radiologists provides a framework for study of the legal and ethical issues related to AI in medical imaging, related to patient data (privacy, confidentiality, ownership, and sharing); algorithms (levels of autonomy, liability, and jurisprudence); practice (best practices and current legal framework); and finally, opportunities in AI from the perspective of a universal health care system.

Patient Preferences for Coronary CT Angiography with Stress Perfusion, SPECT, or Invasive Coronary Angiography

Background Patient preference is pivotal for widespread adoption of tests in clinical practice. Patient preferences for invasive versus other noninvasive tests for coronary artery disease are not known. Purpose To compare patient acceptance and preferences for noninvasive and invasive cardiac imaging in North and South America, Asia, and Europe. Materials and Methods This was a prospective 16-center trial in 381 study participants undergoing coronary CT angiography with stress perfusion, SPECT, and invasive coronary angiography (ICA). Patient preferences were collected by using a previously validated questionnaire translated into eight languages. Responses were converted to ordinal scales and were modeled with generalized linear mixed models. Results In patients in whom at least one test was associated with pain, CT and SPECT showed reduced median pain levels, reported on 0-100 visual analog scales, from 20 for ICA (interquartile range [IQR], 4-50) to 6 for CT (IQR, 0-27.5) and 5 for SPECT (IQR, 0-25) (P < .001). Patients from Asia reported significantly more pain than patients from other continents for ICA (median, 25; IQR, 10-50; P = .01), CT (median, 10; IQR, 0-30; P = .02), and SPECT (median, 7; IQR, 0-28; P = .03). Satisfaction with preparation differed by continent and test (P = .01), with patients from Asia reporting generally lower ratings. Patients from North America had greater percentages of "very high" or "high" satisfaction than patients from other continents for ICA (96% vs 82%, respectively; P < .001) and SPECT (95% vs 79%, respectively; P = .04) but not for CT (89% vs 86%, respectively; P = .70). Among all patients, CT was preferred by 54% of patients, compared with 18% for SPECT and 28% for ICA (P < .001). Conclusion For cardiac imaging, patients generally favored CT angiography with stress perfusion, while study participants from Asia generally reported lowest satisfaction. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Woodard and Nguyen in this issue.

Initial evaluation of three-dimensionally printed patient-specific coronary phantoms for CT-FFR software validation

We developed three-dimensionally (3D) printed patient-specific coronary phantoms that are capable of sustaining physiological flow and pressure conditions. We assessed the accuracy of these phantoms from coronary CT acquisition, benchtop experimentation, and CT-FFR software. Five patients with coronary artery disease underwent 320-detector row coronary CT angiography (CCTA) (Aquilion ONE, Canon Medical Systems) and a catheter lab procedure to measure fractional flow reserve (FFR). The aortic root and three main coronary arteries were segmented (Vitrea, Vital Images) and 3D printed (Eden 260V, Stratasys). Phantoms were connected into a pulsatile flow loop, which replicated physiological flow and pressure gradients. Contrast was introduced and the phantoms were scanned using the same CT scanner model and CCTA protocol as used for the patients. Image data from the phantoms were input to a CT-FFR research software (Canon Medical Systems) and compared to those derived from the clinical data, along with comparisons between image measurements and benchtop FFR results. Phantom diameter measurements were within 1 mm on average compared to patient measurements. Patient and phantom CT-FFR results had an absolute mean difference of 4.34% and Pearson correlation of 0.95. We have demonstrated the capabilities of 3D printed patient-specific phantoms in a diagnostic software.