Incidental Findings and Low-Value Care

Beyond pulmonary embolism: Alternative diagnosis and incidental findings on CT pulmonary angiography in sickle cell disease

BACKGROUND

Sickle cell disease (SCD) is a genetic hematological disorder associated with severe complications, such as vaso-occlusive crises, acute chest syndrome (ACS), and an increased risk of thromboembolic events, including pulmonary embolism (PE). The diagnosis of PE in SCD patients presents challenges due to the overlapping symptoms with other pulmonary conditions. Our previous study revealed that nearly 96% of computed tomography pulmonary angiography (CTPA) scans in SCD patients were negative for PE, highlighting a gap in understanding the significance of CTPA findings when PE is absent.

METHODS

In this retrospective follow-up study conducted at the Salmaniya Medical Complex in Bahrain, we examined SCD patients with HbSS genotypes who underwent CTPA from January 1, 2018, to December 31, 2021, for suspected PE, but the results were negative. The aim of this study was to identify alternative diagnoses and incidental findings from CTPA scans. Experienced radiologists reviewed the CTPA images and reports to assess potential alternative diagnoses and incidental findings, incorporating an additional analysis of chest X-rays to evaluate the diagnostic value of CTPA. Incidental findings were classified based on their location and clinical significance.

RESULTS

Among the 230 evaluated SCD patients (average age 39.7 years; 53% male) who were CTPA negative for PE, 142 (61.7%) had identifiable alternative diagnoses, primarily pneumonia (49.1%). Notably, 88.0% of these alternative diagnoses had been previously suggested by chest radiographs. Furthermore, incidental findings were noted in 164 (71.3%) patients, with 11.0% deemed clinically significant, necessitating immediate action, and 87.8% considered potentially significant, requiring further assessment. Notable incidental findings included thoracic abnormalities such as cardiomegaly (12.2%) and an enlarged pulmonary artery (11.3%), as well as upper abdominal pathologies such as hepatomegaly (19.6%), splenomegaly (20.9%), and gallstones (10.4%).

CONCLUSION

This study underscores the limited additional diagnostic yield of CTPA for identifying alternative diagnoses to PE in SCD patients, with the majority of diagnoses, such as pneumonia, already suggested by chest radiographs. The frequent incidental findings, most of which necessitate further evaluation, highlight the need for a cautious and tailored approach to using CTPA in the SCD population.

Planetary Health and Radiology: Why We Should Care and What We Can Do

Climate change adversely affects the well-being of humans and the entire planet. A planetary health framework recognizes that sustaining a healthy planet is essential to achieving individual, community, and global health. Radiology contributes to the climate crisis by generating greenhouse gas (GHG) emissions during the production and use of medical imaging equipment and supplies. To promote planetary health, strategies that mitigate and adapt to climate change in radiology are needed. Mitigation strategies to reduce GHG emissions include switching to renewable energy sources, refurbishing rather than replacing imaging scanners, and powering down unused scanners. Radiology departments must also build resiliency to the now unavoidable impacts of the climate crisis. Adaptation strategies include education, upgrading building infrastructure, and developing departmental sustainability dashboards to track progress in achieving sustainability goals. Shifting practices to catalyze these necessary changes in radiology requires a coordinated approach. This includes partnering with key stakeholders, providing effective communication, and prioritizing high-impact interventions. This article reviews the intersection of planetary health and radiology. Its goals are to emphasize why we should care about sustainability, showcase actions we can take to mitigate our impact, and prepare us to adapt to the effects of climate change. © RSNA, 2024 Supplemental material is available for this article. See also the article by Ibrahim et al in this issue. See also the article by Lenkinski and Rofsky in this issue.

Algorithms in medical decision-making and in everyday life: what's the difference?

Algorithms are a ubiquitous part of modern life. Despite being a component of medicine since early efforts to deploy computers in medicine, clinicians' resistance to using decision support and use algorithms to address cognitive biases has been limited. This resistance is not just limited to the use of algorithmic clinical decision support, but also evidence and stochastic reasoning and the implications of the forcing function of the electronic medical record. Physician resistance to algorithmic support in clinical decision making is in stark contrast to their general acceptance of algorithmic support in other aspects of life.

Opportunistic Screening for Coronary Artery Disease: An Untapped Population Health Resource

BACKGROUND

Coronary artery disease is the leading cause of death in the United States. At-risk asymptomatic adults are eligible for screening with electrocardiogram-gated coronary artery calcium (CAC) CT, which aids in risk stratification and management decision-making. Incidental CAC (iCAC) is easily quantified on chest CT in patients imaged for noncardiac indications; however, radiologists do not routinely report the finding.

OBJECTIVE

To determine the clinical significance of CAC identified incidentally on routine chest CT performed for noncardiac indications.

DESIGN

An informationist developed search strategies in MEDLINE, Embase, and SCOPUS, and two reviewers independently screened results at both the abstract and full text levels. Data extracted from eligible articles included age, rate of iCAC identification, radiologist reporting frequency, impact on downstream medical management, and association of iCAC with patient outcomes.

RESULTS

From 359 unique citations, 83 research publications met inclusion criteria. The percentage of patients with iCAC ranged from 9% to 100%. Thirty-one investigations measured association(s) between iCAC and cardiovascular morbidity and mortality, and 29 identified significant correlations, including nonfatal myocardial infarction, fatal myocardial infarction, major adverse cardiovascular event, cardiovascular death, and all-cause death. iCAC was present in 20% to 100% of the patients in these cohorts, but when present, iCAC was reported by radiologists in only 31% to 44% of cases. Between 18% and 77% of patients with iCAC were not on preventive medications in studies that reported these data. Seven studies measured the effect of reporting on guideline directed medical therapy, and 5 (71%) reported an increase in medication prescriptions after diagnosis of iCAC, with one confirming reductions in low-density lipoprotein levels. Twelve investigations reported good concordance between CAC grade on noncardiac CT and Agatston score on electrocardiogram-gated cardiac CT, and 10 demonstrated that artificial intelligence tools can reliably calculate an Agatston score on noncardiac CT.

CONCLUSION

A body of evidence demonstrates that patients with iCAC on routine chest CT are at risk for cardiovascular disease events and death, but they are often undiagnosed. Uniform reporting of iCAC in the chest CT impression represents an opportunity for radiology to contribute to early identification of high-risk individuals and potentially reduce morbidity and mortality. AI tools have been validated to calculate Agatston score on routine chest CT and hold the best potential for facilitating broad adoption.

Applying ONCO-RADS to whole-body MRI cancer screening in a retrospective cohort of asymptomatic individuals

BACKGROUND

Whole-body magnetic resonance imaging (WB-MRI) has emerged as a valuable tool for cancer detection. This study evaluated the prevalence rates of cancer in asymptomatic individuals undergoing WB-MRI according to the Oncologically Relevant Findings Reporting and Data System (ONCO-RADS) classifications in order to assess the reliability of the classification method.

METHODS

We retrospectively enrolled 2064 asymptomatic individuals who participated in a WB-MRI cancer screening program between 2017 and 2022. WB-MRI was acquired on a 3-T system with a standard protocol, including regional multisequence and gadolinium-based contrast agent-enhanced oncologic MRI. Results of further examinations, including additional imaging and histopathology examinations, performed at our institute were used to validate the WB-MRI findings. Two radiologists blinded to the clinical outcome classified the WB-MRI findings according to the ONCO-RADS categories as follows: 1 (normal), 2 (benign finding highly likely), 3 (benign finding likely), 4 (malignant finding likely), and 5 (malignant finding highly likely). Firth logistic regression analysis was performed to determine the associations between participant characteristics and findings of ONCO-RADS category ≥ 4.

RESULTS

Of the 2064 participants with median age of 55 years, 1120 (54.3%) were men, 43 (2.1%) had findings of ONCO-RADS category ≥ 4, and 24 (1.2%) had confirmed cancer. The cancer prevalence rates were 0.1%, 5.4%, 42.9%, and 75% for ONCO-RADS categories 2, 3, 4, and 5, respectively. In the multivariable model, older age (OR: 1.035, p = 0.029) and history of hypertension (OR: 2.051, p = 0.026), hepatitis B carrier (OR: 2.584, p = 0.013), or prior surgery (OR: 3.787, p < 0.001) were independently associated with the findings for ONCO-RADS category ≥ 4.

CONCLUSIONS

The ONCO-RADS categories for cancer risk stratification were validated and found to be positively correlated with cancer risk. The application of ONCO-RADS facilitates risk-based management after WB-MRI for cancer screening.

Incidental Thalamic Lesions Identified on Brain MRI in Pediatric and Young Adult Patients: Imaging Features and Natural History

BACKGROUND AND PURPOSE

Nonspecific, localized thalamic signal abnormalities of uncertain significance are occasionally found on pediatric brain MR imaging. The goal of this study is to describe the MR imaging appearance and natural history of these lesions in children and young adults.

MATERIALS AND METHODS

This retrospective study evaluated clinically acquired brain MR imaging examinations obtained from February 1995 to March 2022 at a large, tertiary care pediatric hospital. Examinations with non-mass-like and nonenhancing thalamic lesions were identified based on term search of MR imaging reports. A total of 221 patients formed the initial group for imaging assessment. Additional exclusions during imaging review resulted in 171 patients. Imaging appearance and size changes were assessed at baseline and at follow-up examinations.

RESULTS

A total of 171 patients (102 male) at a median age of 11 years (range: 1-23 years), 568 MR imaging examinations, and 180 thalamic lesions were included. Median time from baseline to the last follow-up MR imaging was 542 days (range: 46-5730 days). No lesion enhanced at any time point. On imaging follow-up, 11% of lesions (18/161) became smaller, 10% (16/161) resolved, 73% (118/161) remained stable, and 6% (9/161) increased in size at some point during evaluation. Median time interval from baseline to enlargement was 430 days (range: 136-1074 days).

CONCLUSIONS

Most incidental, non-mass-like thalamic signal abnormalities were stable, decreased in size, or resolved on follow-up imaging and are likely of no clinical significance. Surveillance strategies with longer follow-up intervals may be adequate in the management of such findings.

Patient experiences of rotator cuff-related shoulder pain and their views on diagnostic shoulder imaging: a qualitative study

PURPOSE

To explore patient experiences of rotator cuff-related shoulder pain, and their views on the role and value of diagnostic shoulder imaging.

MATERIALS AND METHODS

Semi-structured interviews were conducted with 20 patients with shoulder pain exploring the impact and management of their shoulder condition, reasons for and experiences of diagnostic imaging, and feelings about and responses to diagnostic imaging findings. Framework analysis was used to analyse the dataset.

RESULTS

Five themes were identified [1]: Lived experience and beliefs about pain and movement [2]; Contextualisation of imaging findings by health professionals is more important than the imaging report [3]; Factors influencing whether and when to have imaging [4]; Imaging can identify the actual problem and guide treatment; and [5] Treatment responses and treatment decision making.

CONCLUSION

Patients commonly believe imaging is needed to formulate a diagnosis. There was minimal concern about potential indirect harms that could arise (e.g., inappropriate diagnosis leading to unnecessary treatments). The context of the diagnostic imaging reports (i.e., what needed to be done) was perceived as more important than the exact meaning of the imaging findings. Patients felt that the diagnostic imaging confirmed their existing biomedical beliefs, and these beliefs were not challenged by their healthcare professionals.IMPLICATIONS FOR REHABILITATIONPatients with shoulder pain may believe imaging is necessary for diagnosis and defining treatment yet do not consider potential indirect harms (e.g., unnecessary treatment for findings that are not relevant).Health professionals should ensure patients are aware of imaging limitations and harms and facilitate shared decision-making about whether to have imaging.Health professionals also have an important role in the appropriate contextualisation of imaging findings (i.e., they do not necessarily relate to pain nor guide treatment).

Can we revolutionize diagnostic imaging by keeping Pandora's box closed?

Incidental imaging findings are a considerable health problem, because they generally result in low-value and potentially harmful care. Healthcare professionals struggle how to deal with them, because once detected they can usually not be ignored. In this opinion article, we first reflect on current practice, and then propose and discuss a new potential strategy to pre-emptively tackle incidental findings. The core principle of this concept is to keep the proverbial Pandora's box closed, i.e. to not visualize incidental findings, which can be achieved using deep learning algorithms. This concept may have profound implications for diagnostic imaging.

Turning radiology reports into epidemiological data to track seasonal pulmonary infections and the COVID-19 pandemic

OBJECTIVES

To automatically label chest radiographs and chest CTs regarding the detection of pulmonary infection in the report text, to calculate the number needed to image (NNI) and to investigate if these labels correlate with regional epidemiological infection data.

MATERIALS AND METHODS

All chest imaging reports performed in the emergency room between 01/2012 and 06/2022 were included (64,046 radiographs; 27,705 CTs). Using a regular expression-based text search algorithm, reports were labeled positive/negative for pulmonary infection if described. Data for regional weekly influenza-like illness (ILI) consultations (10/2013-3/2022), COVID-19 cases, and hospitalization (2/2020-6/2022) were matched with report labels based on calendar date. Positive rate for pulmonary infection detection, NNI, and the correlation with influenza/COVID-19 data were calculated.

RESULTS

Between 1/2012 and 2/2020, a 10.8-16.8% per year positive rate for detecting pulmonary infections on chest radiographs was found (NNI 6.0-9.3). A clear and significant seasonal change in mean monthly detection counts (102.3 winter; 61.5 summer; p < .001) correlated moderately with regional ILI consultations (weekly data r = 0.45; p < .001). For 2020-2021, monthly pulmonary infection counts detected by chest CT increased to 64-234 (23.0-26.7% per year positive rate, NNI 3.7-4.3) compared with 14-94 (22.4-26.7% positive rate, NNI 3.7-4.4) for 2012-2019. Regional COVID-19 epidemic waves correlated moderately with the positive pulmonary infection CT curve for 2020-2022 (weekly new cases: r = 0.53; hospitalizations: r = 0.65; p < .001).

CONCLUSION

Text mining of radiology reports allows to automatically extract diagnoses. It provides a metric to calculate the number needed to image and to track the trend of diagnoses in real time, i.e., seasonality and epidemic course of pulmonary infections.

CLINICAL RELEVANCE

Digitally labeling radiology reports represent previously neglected data and may assist in automated disease tracking, in the assessment of physicians' clinical reasoning for ordering radiology examinations and serve as actionable data for hospital workflow optimization.

KEY POINTS

• Radiology reports, commonly not machine readable, can be automatically labeled with the contained diagnoses using a regular-expression based text search algorithm. • Chest radiograph reports positive for pulmonary infection moderately correlated with regional influenza-like illness consultations (weekly data; r = 0.45; p < .001) and chest CT reports with the course of the regional COVID-19 pandemic (new cases: r = 0.53; hospitalizations: r = 0.65; p < 0.001). • Rendering radiology reports into data labels provides a metric for automated disease tracking, the assessment of ordering physicians clinical reasoning and can serve as actionable data for workflow optimization.

Functional roles of magnetic nanoparticles for the identification of metastatic lymph nodes in cancer patients

Staging lymph nodes (LN) is crucial in diagnosing and treating cancer metastasis. Biotechnologies for the specific localization of metastatic lymph nodes (MLNs) have attracted significant attention to efficiently define tumor metastases. Bioimaging modalities, particularly magnetic nanoparticles (MNPs) such as iron oxide nanoparticles, have emerged as promising tools in cancer bioimaging, with great potential for use in the preoperative and intraoperative tracking of MLNs. As radiation-free magnetic resonance imaging (MRI) probes, MNPs can serve as alternative MRI contrast agents, offering improved accuracy and biological safety for nodal staging in cancer patients. Although MNPs' application is still in its initial stages, exploring their underlying mechanisms can enhance the sensitivity and multifunctionality of lymph node mapping. This review focuses on the feasibility and current application status of MNPs for imaging metastatic nodules in preclinical and clinical development. Furthermore, exploring novel and promising MNP-based strategies with controllable characteristics could lead to a more precise treatment of metastatic cancer patients.