ABSTRACT
A pulmonary arteriovenous malformation (PAVM) is a fistulous connection between a pulmonary artery and a pulmonary vein that bypasses the normal pulmonary capillary bed resulting in a right-to-left shunt. Because of the potential for paradoxical emboli, PAVMs are treated when their feeding arteries exceed 3 mm or patients are symptomatic. PAVMs are often encountered in patients with suspected hereditary hemorrhagic telangiectasia (HHT). Sporadic cases are uncommon. The radiologist may be called on to diagnose a PAVM after positive transthoracic contrast-enhanced echocardiography in a patient with suspected HHT to direct patient management and avoid potential complications. The radiologist may also be required to evaluate a potential PAVM detected at CT performed for other reasons. Through the authors' experiences at an HHT Center of Excellence in an area endemic with histoplasmosis, the authors have gained a unique perspective on the diagnosis of PAVMs and differentiation of PAVMs from their mimics. Understanding the CT appearance of PAVMs limits misdiagnosis, directs appropriate treatment, and allows subsequent family screening for HHT (and avoidance of unnecessary screening when a PAVM mimic is encountered). Both vascular and nonvascular pulmonary lesions can mimic PAVMs. Vascular mimics include fibrosing mediastinitis, venovenous collaterals, arterial collaterals, pulmonary artery pseudoaneurysms, hepatopulmonary vessels, Sheehan vessels, meandering pulmonary veins, and pulmonary vein varices. Nonvascular mimics include granulomas, nodules, mucoceles, bronchoceles, ground-glass opacities, and atelectasis. The authors review the CT technique for evaluating PAVMs and the appearance of PAVMs and their mimics. ©RSNA, 2022.
Subject(s)
Arteriovenous Malformations , Embolization, Therapeutic , Pulmonary Veins , Telangiectasia, Hereditary Hemorrhagic , Arteriovenous Malformations/diagnostic imaging , Humans , Pulmonary Artery/diagnostic imaging , Pulmonary Veins/abnormalities , Pulmonary Veins/diagnostic imaging , Telangiectasia, Hereditary Hemorrhagic/complications , Telangiectasia, Hereditary Hemorrhagic/diagnosis , Telangiectasia, Hereditary Hemorrhagic/therapy , Tomography, X-Ray ComputedABSTRACT
OBJECTIVE. Coronavirus disease (COVID-19) is a global pandemic. Studies in the radiology literature have suggested that CT might be sufficiently sensitive and specific in diagnosing COVID-19 when used in lieu of a reverse transcription-polymerase chain reaction test; however, this suggestion runs counter to current society guidelines. The purpose of this article is to critically review some of the most frequently cited studies on the use of CT for detecting COVID-19. CONCLUSION. To date, the radiology literature on COVID-19 has consisted of limited retrospective studies that do not substantiate the use of CT as a diagnostic test for COVID-19.
Subject(s)
Coronavirus Infections/diagnostic imaging , Pneumonia, Viral/diagnostic imaging , Radiography, Thoracic/methods , Tomography, X-Ray Computed/methods , Betacoronavirus , COVID-19 , Humans , Pandemics , SARS-CoV-2ABSTRACT
Background Risk stratification systems for thyroid nodules are often complicated and affected by low specificity. Continual improvement of these systems is necessary to reduce the number of unnecessary thyroid biopsies. Purpose To use artificial intelligence (AI) to optimize the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS). Materials and Methods A total of 1425 biopsy-proven thyroid nodules from 1264 consecutive patients (1026 women; mean age, 52.9 years [range, 18-93 years]) were evaluated retrospectively. Expert readers assigned points based on five ACR TI-RADS categories (composition, echogenicity, shape, margin, echogenic foci), and a genetic AI algorithm was applied to a training set (1325 nodules). Point and pathologic data were used to create an optimized scoring system (hereafter, AI TI-RADS). Performance of the systems was compared by using a test set of the final 100 nodules with interpretations from the expert reader, eight nonexpert readers, and an expert panel. Initial performance of AI TI-RADS was calculated by using a test for differences between binomial proportions. Additional comparisons across readers were conducted by using bootstrapping; diagnostic performance was assessed by using area under the receiver operating curve. Results AI TI-RADS assigned new point values for eight ACR TI-RADS features. Six features were assigned zero points, which simplified categorization. By using expert reader data, the diagnostic performance of ACR TI-RADS and AI TI-RADS was area under the receiver operating curve of 0.91 and 0.93, respectively. For the same expert, specificity of AI TI-RADS (65%, 55 of 85) was higher (P < .001) than that of ACR TI-RADS (47%, 40 of 85). For the eight nonexpert radiologists, mean specificity for AI TI-RADS (55%) was also higher (P < .001) than that of ACR TI-RADS (48%). An interactive AI TI-RADS calculator can be viewed at http://deckard.duhs.duke.edu/â¼ai-ti-rads . Conclusion An artificial intelligence-optimized Thyroid Imaging Reporting and Data System (TI-RADS) validates the American College of Radiology TI-RADS while slightly improving specificity and maintaining sensitivity. Additionally, it simplifies feature assignments, which may improve ease of use. © RSNA, 2019 Online supplemental material is available for this article.
Subject(s)
Artificial Intelligence , Diagnostic Imaging/methods , Image Interpretation, Computer-Assisted/methods , Radiology Information Systems , Thyroid Nodule/diagnostic imaging , Adolescent , Adult , Aged , Aged, 80 and over , Female , Humans , Male , Middle Aged , Reproducibility of Results , Retrospective Studies , Risk Assessment , Sensitivity and Specificity , Societies, Medical , Thyroid Gland/diagnostic imaging , United States , Young AdultABSTRACT
Radiology reports contain a large amount of potentially valuable unstructured data. Recently, neural networks have been employed to perform classification of radiology reports over a few classes at the document level. The success of neural networks in sequence-labeling problems such as named entity recognition and part of speech tagging suggests that they could be used to classify radiology report text with greater granularity. We employed a neural network architecture to comprehensively classify mammography report text at the word level using a sequence labeling approach. Two radiologists devised a comprehensive classification system for screening mammography reports. Each word in each report was manually categorized by a radiologist into one of 33 categories according to the classification system. Tagged words referencing the same finding were grouped into unique sets. We pre-labeled reports with a rule-based algorithm and then manually edited these annotations for 6705 screening mammography reports (25.1%, 66.8%, and 8.1% BI-RADS 0, 1, and 2, respectively). A combined convolutional and recurrent neural network model was used to label words in each sentence of the individual reports. A siamese recurrent neural network was then used to group findings into sets. Performance of the neural network-based method was compared to a rule-based algorithm and a conditional random field (CRF) model. Global accuracy (percentage of documents where all word tags were predicted correctly) and keyword accuracy (percentage of all words that were labeled correctly, excluding words tagged as unimportant) were calculated on an unseen 519 report test set. Two-tailed t tests were used to assess differences between algorithm performance, and p < 0.05 was used to determine statistical significance. The neural network-based approach showed significantly higher global accuracy compared to both the rule-based algorithm (88.3 vs 57.0%, p < 0.001) and the CRF model (88.3% vs. 75.8%, p < 0.001). The neural network also showed significantly higher keyword level accuracy compared to the rule-based algorithm (95.5% vs. 80.9% p < 0.001) and CRF model (95.5% vs. 76.9%, p < 0.001). We demonstrate the potential of neural networks to accurately perform word-level multilabel classification of free text radiology reports across 33 classes, thus showing the utility of a sequence labeling approach to NLP of radiology reports. We found that a neural network classifier outperforms a rule-based algorithm and a CRF classifier for comprehensive multilabel classification of free text screening mammography reports at the word level. By approaching radiology report classification as a sequence-labeling problem, we demonstrate the ability of neural networks to extract data from free text radiology reports at a level of granularity not previously reported.
Subject(s)
Breast Neoplasms/diagnostic imaging , Electronic Health Records/classification , Image Interpretation, Computer-Assisted/methods , Mammography/methods , Neural Networks, Computer , Databases, Factual , Female , Humans , Reproducibility of Results , Research ReportABSTRACT
History A 31-year-old woman with a history of bilateral orthotopic lung transplantation performed 10 months earlier for cystic fibrosis presented for a routine follow-up appointment, with her chief symptom being a cough. The cough started approximately 1 month prior to this appointment and was minimally productive of clear to yellow phlegm. In addition to her cough, she reported increased sinus congestion and a sensation of "something in her upper chest." She denied shortness of breath, wheezing, hemoptysis, or cigarette smoking. Review of systems was negative for fever, chills, or night sweats. At physical examination, the patient was afebrile, borderline tachycardic (heart rate, 99 beats per minute), and mildly hypertensive (blood pressure, 138/99 mm Hg). Oxygen saturation was 96% on room air. Laboratory evaluation revealed a white blood cell count of 3.5 × 109/L (normal range, 3.2-9.8 × 109/L). Pulmonary function testing was notable for a newly decreased ratio of forced expiratory volume in 1 second (FEV1) to forced vital capacity (FVC) of 64% (2.0 and 3.4 L, respectively) (normal FEV1-to-FVC ratio, 80%), suggesting an obstructive lung process. One month prior to presentation, the patient's sputum cultures grew Pseudomonas and methicillin-resistant Staphylococcus aureus. The patient showed no evidence of active infection at the time of bronchoscopy. Thus, the bacteria were favored to reflect colonization, and antibiotic therapy was not administered at that time. The patient was taking an immunosuppression regimen of mycophenalate mofetil (CellCept; Genentech, San Francisco, Calif) (1 g twice daily), prednisone (10 mg daily), and tacrolimus (Prograf; Astellas Pharma US, Northbrook, Ill) (goal therapeutic range, 12-14 ng/mL). The patient was sent for posteroanterior and lateral chest radiography followed by chest CT ( Figs 1 - 3 ) and fluorine 18 fluorodeoxyglucose PET/CT ( Fig 4 ). [Figure: see text][Figure: see text][Figure: see text][Figure: see text].
ABSTRACT
History A 31-year-old woman with a history of bilateral orthotopic lung transplantation performed 10 months earlier for cystic fibrosis presented for a routine follow-up appointment, with her chief symptom being a cough. The cough started approximately 1 month prior to this appointment and was minimally productive of clear to yellow phlegm. In addition to her cough, she reported increased sinus congestion and a sensation of "something in her upper chest." She denied shortness of breath, wheezing, hemoptysis, or cigarette smoking. Review of systems was negative for fever, chills, or night sweats. At physical examination, the patient was afebrile, borderline tachycardic (heart rate, 99 beats per minute), and mildly hypertensive (blood pressure, 138/99 mm Hg). Oxygen saturation was 96% on room air. Laboratory evaluation revealed a white blood cell count of 3.5 × 109/L (normal range, [3.2-9.8] × 109/L). Pulmonary function testing was notable for a newly decreased ratio of forced expiratory volume in 1 second (FEV1) to forced vital capacity (FVC) of 64% (2.0 and 3.4 L, respectively) (normal FEV1-to-FVC ratio, 80%), suggesting an obstructive lung process. One month prior to presentation, the patient's sputum cultures grew Pseudomonas and methicillin-resistant Staphylococcus aureus. The patient showed no evidence of active infection at the time of bronchoscopy. Thus, the bacteria were favored to reflect colonization, and antibiotic therapy was not administered at that time. The patient was taking an immunosuppression regimen of mycophenolate mofetil (CellCept; Genentech, San Francisco, Calif) (1 g twice daily), prednisone (10 mg daily), and tacrolimus (Prograf; Astellas Pharma US, Northbrook, Ill) (goal therapeutic range, 12-14 ng/mL). The patient was sent for posteroanterior and lateral chest radiography followed by chest CT ( Figs 1 - 3 ) and fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT ( Fig 4 ).
Subject(s)
Lung Transplantation , Lymphoproliferative Disorders/diagnostic imaging , Postoperative Complications/diagnostic imaging , Tomography, X-Ray Computed/methods , Adult , Bronchi/diagnostic imaging , Bronchoscopy/methods , Female , Fluorodeoxyglucose F18 , Humans , Lung/diagnostic imaging , Positron Emission Tomography Computed Tomography , RadiopharmaceuticalsABSTRACT
Factors governing the steady-state IOP have been extensively studied; however, the dynamic aspects of IOP are less understood. Clinical studies have suggested that intraocular pressure (IOP) fluctuation may be associated with glaucoma risk. This study aims to investigate how stiffening of corneoscleral biomechanical properties affects IOP spikes induced by rapid microvolumetric change. Porcine eyes (n = 25 in total) were subjected to volumetric infusions before and after external treatment of a circular area (11 mm diameter) in either the central cornea or posterior sclera. The treated area in the control group was immersed in phosphate-buffered saline (PBS) for 40 min, while the treated area of the chemical crosslinking group was immersed in 4% glutaraldehyde/PBS for 40 min. A subset of the sham-treated eyes was also subjected to volumetric infusions at a raised steady-state IOP. The magnitude of IOP spikes increased after localized chemical crosslinking of either the cornea (27.5% increase, p < 0.001) or the sclera (14.3% increase, p < 0.001) with corneal crosslinking having a stronger effect than scleral crosslinking (p = 0.018). We also observed that raising the steady-state IOP from 15 to 25 mmHg resulted in marked increase in IOP spike magnitudes by 63.9% (p < 0.001). These results suggested that an increased corneoscleral stiffness could significantly increase IOP spike magnitudes at the same volumetric change. Corneal stiffness appeared to have a strong impact on the IOP spike magnitude and may play a major role in regulating rapid volume-pressure dynamics. An increase in steady-state IOP also resulted in larger IOP fluctuations due to the increased "apparent" stiffness of the ocular shell, suggesting a potential interaction between the magnitude of IOP and its fluctuations. Corneoscleral properties may represent additional pathways for understanding and managing glaucoma risk and warrant future investigation.
Subject(s)
Cornea/physiology , Elasticity/physiology , Intraocular Pressure/physiology , Sclera/physiology , Animals , Biomechanical Phenomena , Models, Animal , Ocular Hypertension/physiopathology , Swine , Tonometry, OcularABSTRACT
Lung transplantation is the only curative treatment for end-stage lung disease, which is caused by a wide variety of pathologies and encountered in a diverse range of patients. Potential recipients, as well as donors are carefully evaluated by imaging prior to transplant for contraindications to the transplant. After transplantation, recipients are imaged in the immediate, early, intermediate, and late periods for complications that may arise and require intervention. Radiography and computed tomography are the 2 most commonly used imaging modalities used to evaluate the chest after lung transplantation.
Subject(s)
Lung Transplantation , Tomography, X-Ray Computed , Humans , Lung Diseases/diagnostic imaging , Lung Diseases/surgery , Lung Diseases/diagnosis , Postoperative Complications/diagnostic imaging , Postoperative Complications/etiology , Lung/diagnostic imagingABSTRACT
OBJECTIVE: The purpose of this study was to develop a natural language processing (NLP) pipeline to identify incidental thyroid nodules (ITNs) meeting criteria for sonographic follow-up and to assess both adherence rates to white paper recommendations and downstream outcomes related to these incidental findings. METHODS: 21583 non-contrast chest CT reports from 2017 and 2018 were retrospectively evaluated to identify reports which included either an explicit recommendation for thyroid ultrasound, a description of a nodule ≥ 1.5 cm, or description of a nodule with suspicious features. Reports from 2018 were used to train an NLP algorithm called fastText for automated identification of such reports. Algorithm performance was then evaluated on the 2017 reports. Next, any patient from 2017 with a report meeting criteria for ultrasound follow-up was further evaluated with manual chart review to determine follow-up adherence rates and nodule-related outcomes. RESULTS: NLP identified reports with ITNs meeting criteria for sonographic follow-up with an accuracy of 96.5% (95% CI 96.2-96.7) and sensitivity of 92.1% (95% CI 89.8-94.3). In 10006 chest CTs from 2017, ITN follow-up ultrasound was indicated according to white paper criteria in 81 patients (0.8%), explicitly recommended in 46.9% (38/81) of patients, and obtained in less than half of patients in which it was appropriately recommended (17/35, 48.6%). DISCUSSION: NLP accurately identified chest CT reports meeting criteria for ITN ultrasound follow-up. Radiologist adherence to white paper guidelines and subsequent referrer adherence to radiologist recommendations showed room for improvement.
Subject(s)
Thyroid Nodule , Humans , Incidental Findings , Natural Language Processing , Retrospective Studies , Thyroid Nodule/diagnostic imaging , Tomography, X-Ray ComputedABSTRACT
OBJECTIVE: To evaluate patient use and experience with patient-centered radiology reports provided via a radiology-specific patient portal in an outpatient setting. METHODS: Patient-centered interactive radiology reports were made available to all patients who had imaging examinations performed at any of seven outpatient imaging centers via a radiology-specific patient portal, using commercially available software. We recorded portal usage statistics including report access rate, report view time, and use of interactive diagrams and plain language explanations. We assessed patients' subjective report comprehension and experience via survey questions. Results were stratified by age. RESULTS: The majority of patients accessed their online radiology report (59%). For patients who used the interactive plain language definitions and diagrams, the average report viewing time was 5.8 ± 6.6 min compared with 1.8 ± 1.9 min for patients viewing only the raw text report (P < .005). The majority (84.7%) of patients reported that the definitions and diagrams helped them understand their report, and 86.7% of patients endorsed an overall positive experience viewing their report online. CONCLUSIONS: Our results suggest that patient-centered radiology reporting is feasible in the outpatient private practice setting and that dedicated patient-centered content has the potential to increase engagement across all age groups. Our experience suggests that patient-centered radiology reports may improve subjective patient comprehension and positively impact the patient experience.
Subject(s)
Patient Portals , Radiology Information Systems , Radiology , Humans , Language , RadiographyABSTRACT
RATIONALE AND OBJECTIVES: To assess whether abdominopelvic computed tomography (CT) radiology reports directly address a cause for pain when pain is included in the scan indication. MATERIALS AND METHODS: Four hundred and ninety-five random abdominopelvic CT reports containing "pain" in the indication were retrospectively reviewed. The position of pain descriptors within the indication, the presence of an oncology-related indication in addition to pain and whether a cause for pain was addressed in the impression were recorded. Linguistic analysis of indication and impression sections was performed. Comparisons between reports that addressed pain and those that did not were conducted using Chi-square, Fisher exact, and two-tailed t-tests. RESULTS: A cause for pain was addressed in 454 of 495 (91.7%) report impressions. Indications with both oncology-related and pain-related descriptors were less likely to have pain directly addressed (χ2 (1, Nâ¯=â¯495)â¯=â¯16.4, p < .001). There was no significant association between where pain appeared within the indication and whether pain was addressed (χ2 (1, Nâ¯=â¯495)â¯=â¯3.2, pâ¯=â¯.07). Whether an impression conveyed a normal result did not influence if pain was addressed (pâ¯=â¯.49). Impression word count and complexity were higher in the addressed group compared to the not addressed group (word count 66.6 vs. 51.9, p= .02, Composite grade level 30.1 vs. 25.3, p= .02). CONCLUSION: Radiologists at our institution consistently addressed a cause for pain on abdominopelvic CTs when pain was in the indication. However, oncology patients who also had an indication of pain were less likely to have a cause for pain addressed. Impression complexity was high for all reports, though higher in those where pain was addressed.
Subject(s)
Radiography, Abdominal , Radiology , Abdominal Pain/diagnostic imaging , Humans , Retrospective Studies , Tomography, X-Ray ComputedABSTRACT
We report two cases of myocarditis, in two young and previously healthy individuals, temporally related to the second dose of the mRNA-COVID-19 vaccine. Both patients developed acute chest pain, changes on electrocardiogram (ECG), and elevated serum troponin within two days of receiving their second dose. Cardiac magnetic resonance (CMR) findings were consistent with acute myocarditis.
Subject(s)
COVID-19 , Myocarditis , COVID-19 Vaccines , Humans , Myocarditis/diagnostic imaging , RNA, Messenger , SARS-CoV-2ABSTRACT
BACKGROUND: Nivolumab is a novel immunotherapy that was recently approved for treatment of advanced non-small-cell lung cancer (NSCLC). Patients treated with checkpoint inhibitors may show variable computed tomography (CT) features on follow-up imaging, and it is unclear how reliable conventional response criteria are to determine patient management and outcomes. We report the spectrum of sequential CT findings in patients with advanced stage lung cancer who received nivolumab in an effort to better inform appropriate imaging strategies. MATERIALS AND METHODS: We identified all patients at our institution with advanced NSCLC who received nivolumab. Pre- and posttreatment CT scans were reviewed and categorized based on radiographic response to therapy. Demographic data as well as survival data were recorded. RESULTS: There were 34 patients with advanced NSCLC who received nivolumab with sufficient follow-up data. Nineteen patients were classified as responders to treatment; 6 (32%) of 19 showed improvement on their initial follow-up CT and had an average survival of 11.2 months, whereas 13 (68%) of 19 responders initially had stable or progressive disease on CT with an average survival of 11.6 months. Fifteen patients were classified as nonresponders to treatment with an average survival of 3.4 months. CONCLUSION: Novel immunotherapies such as nivolumab mechanistically differ from conventional chemotherapy. Some patients have improved survival despite initial radiographic progression of disease. Our findings underscore the heterogeneous radiographic appearance at follow-up CT in patients with lung cancer who ultimately respond to nivolumab.
Subject(s)
Carcinoma, Non-Small-Cell Lung/diagnosis , Immunotherapy/methods , Lung Neoplasms/diagnosis , Lung/diagnostic imaging , Tomography, X-Ray Computed/methods , Adult , Aged , Aged, 80 and over , Antineoplastic Agents/therapeutic use , Carcinoma, Non-Small-Cell Lung/drug therapy , Carcinoma, Non-Small-Cell Lung/mortality , Female , Follow-Up Studies , Humans , Lung/pathology , Lung Neoplasms/drug therapy , Lung Neoplasms/mortality , Male , Middle Aged , Neoplasm Staging , Nivolumab/therapeutic use , Survival Analysis , Treatment OutcomeABSTRACT
PURPOSE: To determine the variability and readability of language used in chest CT reports to describe a "normal" thyroid gland. METHODS: Using a semi-automated process, we identified unique sentences or phrases describing a "normal" thyroid gland in 11,357 noncontrast chest CT reports. Readability metrics were computed for each descriptor, including sentence length and grade-level indices quantifying the education necessary for text comprehension. Grade-level indices included the Flesch-Kincaid (FK) grade level, Gunning Fog index (GF), Coleman-Liau (CL) index, automated readability index (ARI), and a computed composite grade level (CGL) calculated as (FK + GF + CL + ARI)/4. RESULTS: There were 342 unique "normal" thyroid descriptors identified among 6,957 noncontrast chest CT reports characterizing a normal thyroid gland. For these 342 unique descriptors, sentence length varied 23-fold, with a mean sentence length of 8.3 ± 5.1 words. CGL varied 4-fold, with a mean of 16.4 ± 4.5, suggesting that descriptors for a normal thyroid gland, on average, require an advanced college-level education for comprehension. CONCLUSIONS: The language used by radiologists to describe a normal thyroid gland in chest CT reports is variable and complex. The linguistic characteristics observed herein may be a surrogate for the broader readability of radiology reports. With the growing role of the radiology report in patient communication, further linguistic analysis of reporting language may provide valuable insight for optimizing radiology communication.
Subject(s)
Linguistics , Radiography, Thoracic , Thyroid Gland/diagnostic imaging , Tomography, X-Ray Computed , Comprehension , Humans , Quality Assurance, Health CareABSTRACT
PURPOSE: The aim of this study was to evaluate the effectiveness of a patient-centered web-based interactive mammography report. METHODS: A survey was distributed on Amazon Mechanical Turk, an online crowdsourcing platform. One hundred ninety-three US women ≥18 years of age were surveyed and then randomized to one of three simulated BI-RADS® 0 report formats: standard report, Mammography Quality Standards Act-modeled patient letter, or web-based interactive report. Survey questions assessed participants' report comprehension, satisfaction with and perception of the interpreting radiologist, and experience with the presented report. Two-tailed t tests and χ2 tests were used to evaluate differences among groups. RESULTS: Participants in the interactive web-based group spent more than double the time viewing the report than the standard report group (160.0 versus 64.2 seconds, P < .001). Report comprehension scores were significantly higher for the interactive web-based and patient letter groups than the standard report group (P < .05). Scores of satisfaction with the interpreting radiologist were significantly higher for the web-based interactive report and patient letter groups than the standard report group (P < .01). There were no significant differences between the patient letter and web-based interactive report groups. CONCLUSIONS: Radiology report format likely influences communication effectiveness. For result communication to a non-medical patient audience, patient-centric report formats, such as a Mammography Quality Standards Act-modeled patient letter or web-based interactive report, may offer advantages over the standard radiology report. Future work is needed to determine if these findings are reproducible in patient care settings and to determine how best to optimize radiology result communication to patients.