Satisfaction of search from detection of pulmonary nodules in computed tomography of the chest

Inattentional blindness in medicine

People often fail to notice unexpected stimuli when their attention is directed elsewhere. Most studies of this "inattentional blindness" have been conducted using laboratory tasks with little connection to real-world performance. Medical case reports document examples of missed findings in radiographs and CT images, unintentionally retained guidewires following surgery, and additional conditions being overlooked after making initial diagnoses. These cases suggest that inattentional blindness might contribute to medical errors, but relatively few studies have directly examined inattentional blindness in realistic medical contexts. We review the existing literature, much of which focuses on the use of augmented reality aids or inspection of medical images. Although these studies suggest a role for inattentional blindness in errors, most of the studies do not provide clear evidence that these errors result from inattentional blindness as opposed to other mechanisms. We discuss the design, analysis, and reporting practices that can make the contributions of inattentional blindness unclear, and we describe guidelines for future research in medicine and similar contexts that could provide clearer evidence for the role of inattentional blindness.

Investigating the impact of cognitive biases in radiologists' image interpretation: A scoping review

RATIONALE AND OBJECTIVE

Image interpretation is a fundamental aspect of radiology. The treatment and management of patients relies on accurate and timely imaging diagnosis. However, errors in radiological reports can negatively impact on patient health outcomes. These misdiagnoses can be caused by several different errors, but cognitive biases account for 74 % of all image interpretation errors. There are many biases that can impact on a radiologist's perception and cognitive processes. Several recent narrative reviews have discussed these cognitive biases and have offered possible strategies to mitigate their effects. However, these strategies remain untested. Therefore, the purpose of this scoping review is to evaluate the current knowledge on the extent that cognitive biases impact on medical image interpretation.

MATERIAL AND METHODS

Scopus and Medline Databases were searched using relevant keywords to identify papers published between 2012 and 2022. A subsequent hand search of the narrative reviews was also performed. All studies collected were screened and assessed against the inclusion and exclusion criteria.

RESULTS

Twenty-four publications were included and categorised into five main themes: satisfaction of search, availability bias, hindsight bias, framing bias and other biases. From these studies, there were mixed results regarding the impact of cognitive biases, highlighting the need for further investigation in this area. Moreover, the limited and untested debiasing methods offered by a minority of the publications and narrative reviews also suggests the need for further research. The potential of role of artificial intelligence is also highlighted to further assist radiologists in identifying and mitigating these cognitive biases.

CONCLUSION

Cognitive biases can impact radiologists' image interpretation, however the effectiveness of debiasing strategies remain largely untested.

Incidentally Diagnosed With Pulmonary Embolism in Lung Cancer Patients: Comparison of Clinical Characteristics and Mortality With Symptomatic Pulmonary Embolism

The purpose of this work was to compare the clinical characteristics, rate of recurrent venous thromboembolism (VTE), bleeding complications and mortality of incidental and symptomatic pulmonary embolism (PE) detected on computed tomography in patients with lung cancer. Clinical data of lung cancer patients with PE were obtained from the Department of Respiratory and Critical Care Medicine of Ningbo First affiliated hospital of Ningbo University during January 2016 and June 2021 and were reviewed retrospectively. We compared clinical and radiological characteristics in lung cancer patients with incidental PE (IPE) and symptomatic PE (SPE) and identified variables associated with the 1-year survival on multivariate Cox analysis. All patients were followed up for 1 year to compare the risks of recurrent VTE, bleeding complications, and mortality. Survival analysis was performed by use of Kaplan-Meier. A total of 223 lung cancer patients with PE were enrolled over the period. Of these, 117 (52%) patients had symptomatic whereas 106 (48%) patients had incidental PE. Those with IPE were more likely to have adenocarcinoma, VTE history, chronic respiratory disease and chemotherapy within 30 days prior to PE, while SPE was more frequently observed in patients with squamous cancer, concomitant VTE, performance status 0-1, chronic heart disease and major surgery within 30 days prior to PE. During 1 year of follow-up, recurrent VTE was diagnosed in 10 patients (9.3%) in lung cancer patients with IPE and 13 patients (11.2%) with SPE. The 12-month cumulative recurrent VTE incidence was 9.6% for patients with incidental and 11.4% for patients with symptomatic PE (P = .61). The 12-month cumulative incidences of major bleeding complications were also comparable in the 2 groups (8.1% for incidental patients and 9.8% for symptomatic patients; P = .62). However, the respective 12-month mortality risks were 34.6% and 30.2% in lung cancer patients with IPE and SPE respectively (P = .03). On multivariate Cox analysis, we found that IPE occurrence was an independent risk factor associated with 1-year mortality in lung cancer patients complicated with PE after adjusting for age and sex (HR 1.517; 95% CI: 1.366-1.684; P = .027). Our findings suggest that lung cancer patients diagnosed with and treated for incidental PE had a similar rate of recurrent VTE, and incidence of hemorrhagic complications, but a significantly higher 1-year cumulative mortality rate after PE compared to those with symptomatic PE. IPE may be a marker of poor prognosis.

Clinical impact of a deep learning system for automated detection of missed pulmonary nodules on routine body computed tomography including the chest region

OBJECTIVES

To evaluate the clinical impact of a deep learning system (DLS) for automated detection of pulmonary nodules on computed tomography (CT) images as a second reader.

METHODS

This single-centre retrospective study screened 21,150 consecutive body CT studies from September 2018 to February 2019. Pulmonary nodules detected by the DLS on axial CT images but not mentioned in initial radiology reports were flagged. Flagged images were scored by four board-certificated radiologists each with at least 5 years of experience. Nodules with scores of 2 (understandable miss) or 3 (should not be missed) were then categorised as unlikely to be clinically significant (2a or 3a) or likely to be clinically significant (2b or 3b) according to the 2017 Fleischner guidelines for pulmonary nodules. The miss rate was defined as the total number of studies receiving scores of 2 or 3 divided by total screened studies.

RESULTS

Among 172 nodules flagged by the DLS, 60 (35%) missed nodules were confirmed by the radiologists. The nodules were further categorised as 2a, 2b, 3a, and 3b in 24, 14, 10, and 12 studies, respectively, with an overall positive predictive value of 35%. Missed pulmonary nodules were identified in 0.3% of all CT images, and one-third of these lesions were considered clinically significant.

CONCLUSIONS

Use of DLS-assisted automated detection as a second reader can identify missed pulmonary nodules, some of which may be clinically significant.

CLINICAL RELEVANCE/APPLICATION

Use of DLS to help radiologists detect pulmonary lesions may improve patient care.

KEY POINTS

• DLS-assisted automated detection as a second reader is feasible in a large consecutive cohort. • Performance of combined radiologists and DLS was better than DLS or radiologists alone. • Pulmonary nodules were missed more frequently in abdomino-pelvis CT than the thoracic CT.

Diagnostic reasoning in cardiovascular medicine

Research in cognitive psychology shows that expert clinicians make a medical diagnosis through a two step process of hypothesis generation and hypothesis testing. Experts generate a list of possible diagnoses quickly and intuitively, drawing on previous experience. Experts remember specific examples of various disease categories as exemplars, which enables rapid access to diagnostic possibilities and gives them an intuitive sense of the base rates of various diagnoses. After generating diagnostic hypotheses, clinicians then test the hypotheses and subjectively estimate the probability of each diagnostic possibility by using a heuristic called anchoring and adjusting. Although both novices and experts use this two step diagnostic process, experts distinguish themselves as better diagnosticians through their ability to mobilize experiential knowledge in a manner that is content specific. Experience is clearly the best teacher, but some educational strategies have been shown to modestly improve diagnostic accuracy. Increased knowledge about the cognitive psychology of the diagnostic process and the pitfalls inherent in the process may inform clinical teachers and help learners and clinicians to improve the accuracy of diagnostic reasoning. This article reviews the literature on the cognitive psychology of diagnostic reasoning in the context of cardiovascular disease.

Pitfalls in diagnosis of infiltrative lung disease by CT

The diagnosis of interstitial lung disease may be challenging, especially in atypical disease. Various factors must be considered when performing and reading a chest CT examination for interstitial lung disease, because each of them may represent a source of misinterpretation. Firstly, technical aspects must be mastered, including acquisition and reconstruction parameters as well as post-processing. Secondly, mistakes in interpretation related to the inaccurate description of predominant features, potentially leading to false-positive findings, as well as satisfaction of search must be avoided. In all cases, clinical context, coexisting chest abnormalities and previous examinations must be integrated into the analysis to suggest the most appropriate differential diagnosis.

[Quality of findings, interpretation, and self-assessment of readers of chest x-rays acquired in one plane depending on the use of an anatomical viewing scheme and reader expertise]

PURPOSE

To objectify effects of an anatomical viewing scheme on the respective correctness of (a) findings, (b) interpretations, and (c) self-assessments of readers in chest radiographs acquired in one plane and the assessment of other influencing factors.

MATERIALS AND METHODS

In all, 20 radiologists with 3-60 months of full-time radiography experience evaluated 12 chest radiographs of varying difficulty: once with and once without using an anatomical viewing scheme with at least 1 month in between (n = 480). In consensus of 3 radiological experts (a) and (b) were determined by means of a current computed tomography. The self-assessment (c) of readers was queried.

RESULTS

(a) Findings were either missed or not described in 21%. Another 20% were recognized, but incorrectly described, (b) 62% of interpretations and 31% of derived clinical consequences were wrong and (c) in 39% of items the readers overestimated themselves. Experts were faster and better than novices, but for the scheme usage no further significant differences were detected (p > 0.5, respectively). The most pronounced effect was found in comparison with the routine report produced by the joint evaluation of novices and experts being clearly superior even to the expert study results (a), (b) and (c) alone (p < 0.001, respectively).

CONCLUSION

Reporting of chest X‑rays acquired in one plane was often incomplete or even wrong, and the evaluators overestimated themselves, which was not influenced by the use of the anatomical viewing scheme. Since errors between the evaluators sometimes differed greatly, duplicate evaluation of the radiographs by two different radiologists, which is already the case in many training facilities, may possibly be advisable in general.

Clinical value of a new generation adaptive statistical iterative reconstruction (ASIR-V) in the diagnosis of pulmonary nodule in low-dose chest CT

OBJECTIVE

To evaluate the clinical value of low-dose chest CT combined with the new generation adaptive statistical iterative reconstruction (ASIR-V) algorithm in the diagnosis of pulmonary nodule.

METHODS

30 patients with pulmonary nodules underwent chest CT using Revolution CT. The patients were first scanned with standard-dose at a noise index (NI) of 14, and the images were reconstructed with filtered back projection (FBP) algorithm. If pulmonary nodules were found, a low-dose targeted scan, with NI of 24, was performed localized on the nodules, and the images were reconstructed with 60% ASIR-V. The detection rate of pulmonary nodules in the two scanning modes was recorded. The size of nodules, CT value and standard deviation of nodules were measured. The signal-to-noise ratio and contrast-to-noise ratio were also calculated. Two experienced radiologists used a 5-point method to score the image quality. The volumetric CT dose index, and dose-length product were recorded and the effective dose (ED) was calculated of the two scanning modes.

RESULTS

Volumetric CT dose index (ED) of the standard-dose scan covering the entire lungs was 7.29 ± 2.38 mGy (3.52 ± 1.09 mSv), and that of low-dose targeted scan was 2.56 ± 1.87 mGy (0.51 ± 0.32 mSv). However, the ED of the virtual low-dose scan for the entire lungs was 1.44 ± 0.15 mSv, which would mean a dose reduction of 59.1% compared with the standard-dose scan. 85 of the 87 pulmonary nodules were detected in the low-dose targeted scan, with 2 of the ground-glass density nodules with size less than 1 cm missed, resulting in 97.7% overall detection rate. There was no difference between the low-dose ASIR-V images and standard-dose FBP images for the size (1.49 ± 0.74 cm vs 1.48 ± 0.75 cm), CT value [33.02 ± 1.95 Hounsfield unit (HU) vs 34.6 ± 3.07 HU], standard deviation (27.64 ± 14.42 HU vs 30.38 ± 20.04 HU), signal-to-noise ratio (1.44 ± 0.88 vs 1.43 ± 1.31) and contrast-to-noise ratio (38.95 ± 18.43 vs 38.23 ± 14.99) of nodules (all p > 0.05). There was no difference in the subjective scores between the two scanning modes.

CONCLUSION

The low-dose CT scan combined with ASIR-V algorithm is of comparable value in the detection and the display of pulmonary nodules when compared with the FBP images obtained by standard-dose scan.

ADVANCES IN KNOWLEDGE

This is a clinical study to evaluate the clinical value of pulmonary nodules using ASIR-V algorithm in the same patients in the low-dose chest CT scans. It suggests that ASIR-V provides similar image quality and detection rate for pulmonary nodules at much reduced radiation dose.

Integration of fully automated computer-aided pulmonary nodule detection into CT pulmonary angiography studies in the emergency department: effect on workflow and diagnostic accuracy

PURPOSE

To assess the feasibility of implementing fully automated computer-aided diagnosis (CAD) for detection of pulmonary nodules on CT pulmonary angiography (CTPA) studies in emergency setting.

MATERIALS AND METHODS

CTPA of 48 emergency patients was retrospectively reviewed. Fully automated CAD nodule detection was performed at the scanner and results were automatically submitted to PACS. A third-year radiology resident (RAD1) and a cardiothoracic radiologist with 6 years' experience (RAD2) reviewed the scans independently to detect pulmonary nodules in two different sessions 8 weeks apart: session 1, CAD was reviewed first and then all images were reviewed; session 2, CAD was reviewed last after all images were reviewed. Time spent by RAD to evaluate image sets was measured for each case. Fisher's exact test and t test were used.

RESULTS

There were 17 male and 31 female patients with mean ± SD age of 48.7 ± 16.4 years. Using CAD at the beginning was associated with lower average reading time for both readers. However, difference in reading time did not reach statistical significance for RAD1 (RAD1 94.6 s vs. 102.7 s, P > 0.05; RAD2 61.1 s vs. 76.5 s, P < 0.05). Using CAD at the end significantly increased rate of RAD1 and RAD2 nodule detection by 34% (2.52 vs. 2.12 nodule/scan, P < 0.05) and 27% (2.23 vs. 1.81 nodule/scan, P < 0.05), respectively.

CONCLUSION

Routine utilization of CAD in emergency setting is feasible and can improve detection rate of pulmonary nodules significantly. Different methods of incorporating CAD in detecting pulmonary nodules can improve both the rate of detection and interpretation speed.

Using Eye Movements to Understand how Security Screeners Search for Threats in X-Ray Baggage

There has been an increasing drive to understand failures in searches for weapons and explosives in X-ray baggage screening. Tracking eye movements during the search has produced new insights into the guidance of attention during the search, and the identification of targets once they are fixated. Here, we review the eye-movement literature that has emerged on this front over the last fifteen years, including a discussion of the problems that real-world searchers face when trying to detect targets that could do serious harm to people and infrastructure.

256 Shades of gray: uncertainty and diagnostic error in radiology

Radiologists practice in an environment of extraordinarily high uncertainty, which results partly from the high variability of the physical and technical aspects of imaging, partly from the inherent limitations in the diagnostic power of the various imaging modalities, and partly from the complex visual-perceptual and cognitive processes involved in image interpretation. This paper reviews the high level of uncertainty inherent to the process of radiological imaging and image interpretation vis-à-vis the issue of radiological interpretive error, in order to highlight the considerable degree of overlap that exists between these. The scope of radiological error, its many potential causes and various error-reduction strategies in radiology are also reviewed.

Added Value of Dedicated Spine CT to Detect Fracture in Patients with CT Chest, Abdomen, and Pelvis in the Trauma Setting

PURPOSE

Fractures of the thoracolumbar spine account for up to 90% of spinal fractures, and are associated with significant disability. The advantage of acquiring dedicated spine CT imaging in addition to visceral CT studies of the chest, abdomen and pelvis for detection of spinal fractures has not been definitively established. This retrospective study seeks to determine the contribution of dedicated spine CT in the acute clinical setting.

METHODS

Patients who were diagnosed with fractures of the thoracic or lumbar spine at our institution between January 1, 2010 and June 30, 2014 were identified. Additional inclusion criteria included having a CT of the chest and/or abdomen and pelvis followed by a dedicated thoracic or lumbar spine CT within 30 days. Reports were reviewed for accuracy of fracture detection, and missed fractures were retrospectively analyzed on images for detectability.

RESULTS

A total of 102 patients met our inclusion criteria for a total of 312 fractures. Of the 312 fractures, 31 (10%) were missed on the initial visceral CT in 18 of the 102 patients. In all but two cases, at least one fracture was identified on the visceral spine CT. There were no cases in which the newly identified fractures changed patient management.

CONCLUSION

All fractures requiring surgical intervention were identified on the visceral CT. A dedicated spine CT does detect additional spine fractures but does not clearly alter patient management.

Lung cancer screening: nodule identification and characterization

The accurate identification and characterization of small pulmonary nodules at low-dose CT is an essential requirement for the implementation of effective lung cancer screening. Individual reader detection performance is influenced by nodule characteristics and technical CT parameters but can be improved by training, the application of CT techniques, and by computer-aided techniques. However, the evaluation of nodule detection in lung cancer screening trials differs from the assessment of individual readers as it incorporates multiple readers, their inter-observer variability, reporting thresholds, and reflects the program accuracy in identifying lung cancer. Understanding detection and interpretation errors in screening trials aids in the implementation of lung cancer screening in clinical practice. Indeed, as CT screening moves to ever lower radiation doses, radiologists must be cognisant of new technical challenges in nodule assessment. Screen detected lung cancers demonstrate distinct morphological features from incidentally or symptomatically detected lung cancers. Hence characterization of screen detected nodules requires an awareness of emerging concepts in early lung cancer appearances and their impact on radiological assessment and malignancy prediction models. Ultimately many nodules remain indeterminate, but further imaging evaluation can be appropriate with judicious utilization of contrast enhanced CT or MRI techniques or functional evaluation by PET-CT.

Screening for early stage lung cancer and its correlation with lung nodule detection

Currently, the most effective way of reducing lung cancer mortality is early diagnosis of lung cancer. The National Lung Screening Trial has proved the efficacy of lung cancer screening using low-dose computed tomography to reduce lung cancer mortality. However, many questions remain surrounding lung cancer screening implementation, among which include how to select the optimal risk population, the personalized screening interval based different levels of risk, methods to improve diagnostic discrimination between malignant and benign disease in detected lung nodules, and the roles of biomolecular markers in stratifying risk and in guiding the management of indeterminate nodules. This review concentrates on the latest developments of lung cancer screening and provides an overview of the main unanswered questions on lung nodule detection.

The impact of reconstruction techniques on observer performance for the detection and characterization of small pulmonary nodules in chest CT of children under 13 years

OBJECTIVE

To compare three different reconstruction techniques of CT data for the detection of pulmonary nodules in children under 13 years. Secondly to assess the prevalence of perifissural nodular opacities.

MATERIALS AND METHODS

The study consisted of chest CTs of 31 children (median age 6.9 years, range 2.1-12.7), of whom 17 had known extra-thoracic malignancies. Four observers assessed three techniques for the presence of nodules: axial 5 mm maximum intensity projections (MIPs) used in conjunction with 1 mm slices (mode A), 1 mm slices alone (mode B) and 3 mm slices (mode C). All modes were available in 3D. Per mode sensitivities were determined above a certain threshold of reader agreement. Confidence level and reader agreement for identification of an opacity as nodule served as surrogate for quality of nodule characterization.

RESULTS

103 nodules (median size 2.0 mm) were detected. Mode A yielded the highest interreader agreement (κ 0.336) and a superior sensitivity (71%, p = 0.003) compared to mode B and C (κ 0.218, sensitivity 57% and κ 0.247, sensitivity 56%, respectively). Mode B provided the highest confidence level and interreader agreement with respect to nodule identification (mean 4.3/5, κw 0.508). Double reading improved and evened interreader agreement for all modes (κ 0.450), mode A maintained the highest sensitivity (89.1%, p = 0.05-0.08). A median of 1 intrapulmonary lymph node/patient was seen in children with and without malignancy.

CONCLUSION

MIP improves the detection of pulmonary nodules in chest CTs of children, but overall interreader agreement is only fair. Double reading represents a powerful tool to increase diagnostic reliability in chest CTs of children with a malignancy. Nodule characterization is best with 1 mm slices. Intrapulmonary lymph nodes occur in children with and without malignancy.

Effect of fatigue on reading computed tomography examination of the multiply injured patient

Our goal was to ascertain how fatigue affects performance in reading computed tomography (CT) examinations of patients with multiple injuries. CT images with multiple fractures from a previous study of satisfaction of search (SOS) were read by radiologists after a day of clinical work. Performance in this study with fatigued readers was compared to a previous study in which readers were not fatigued. Detection accuracy for obvious injuries was not affected by fatigue, but accuracy for subtle fractures was reduced ([Formula: see text]). An SOS effect on decision thresholds was evident mirroring recent studies. Without fatigue, readers spent more time interpreting and reporting findings as the number of the injuries increased. When fatigued, readers did not increase reading time as fracture number increased. Without fractures, reading time for not-fatigued and fatigued readers was the same ([Formula: see text]) but was significant ([Formula: see text]) with an added subtle fracture. The difference increased with a major injury ([Formula: see text]) and increased further with both a major injury and subtle fracture ([Formula: see text]). Fatigue and multiple abnormalities have independent effects on detection performance but do interact in determining search time.

Perceptual errors in pediatric radiology

Perceptual errors are common contributors to missed diagnoses in the clinical practice of radiology. While the physical attributes of an image such as image resolution, signal-to-noise characteristics, and anatomic complexity are major causes of poor conspicuity of pathologic lesions, there are major interrelated cognitive contributors to visual errors. The first is satisfaction of search (SOS), where the detection of an abnormality results in premature termination of further search. Another form of incomplete search pattern is visual isolation, where a radiologist's search pattern is truncated to the main areas of an image, while little or no attention is given to peripheral areas. A second cognitive error is inattentional blindness, defined as the failure to notice a fully visible, but unexpected object because attention was otherwise engaged. Strategies for error mitigation have centered around the use of check lists, self prompting routines, and structured reporting within an institutional culture of safety and vigilance.

Missed lung cancer: when, where, and why?

Missed lung cancer is a source of concern among radiologists and an important medicolegal challenge. In 90% of the cases, errors in diagnosis of lung cancer occur on chest radiographs. It may be challenging for radiologists to distinguish a lung lesion from bones, pulmonary vessels, mediastinal structures, and other complex anatomical structures on chest radiographs. Nevertheless, lung cancer can also be overlooked on computed tomography (CT) scans, regardless of the context, either if a clinical or radiologic suspect exists or for other reasons. Awareness of the possible causes of overlooking a pulmonary lesion can give radiologists a chance to reduce the occurrence of this eventuality. Various factors contribute to a misdiagnosis of lung cancer on chest radiographs and on CT, often very similar in nature to each other. Observer error is the most significant one and comprises scanning error, recognition error, decision-making error, and satisfaction of search. Tumor characteristics such as lesion size, conspicuity, and location are also crucial in this context. Even technical aspects can contribute to the probability of skipping lung cancer, including image quality and patient positioning and movement. Albeit it is hard to remove missed lung cancer completely, strategies to reduce observer error and methods to improve technique and automated detection may be valuable in reducing its likelihood.

The Gold Standard Paradox in Digital Image Analysis: Manual Versus Automated Scoring as Ground Truth

CONTEXT

- Novel therapeutics often target complex cellular mechanisms. Increasingly, quantitative methods like digital tissue image analysis (tIA) are required to evaluate correspondingly complex biomarkers to elucidate subtle phenotypes that can inform treatment decisions with these targeted therapies. These tIA systems need a gold standard, or reference method, to establish analytical validity. Conventional, subjective histopathologic scores assigned by an experienced pathologist are the gold standard in anatomic pathology and are an attractive reference method. The pathologist's score can establish the ground truth to assess a tIA solution's analytical performance. The paradox of this validation strategy, however, is that tIA is often used to assist pathologists to score complex biomarkers because it is more objective and reproducible than manual evaluation alone by overcoming known biases in a human's visual evaluation of tissue, and because it can generate endpoints that cannot be generated by a human observer.

OBJECTIVE

- To discuss common visual and cognitive traps known in traditional pathology-based scoring paradigms that may impact characterization of tIA-assisted scoring accuracy, sensitivity, and specificity.

DATA SOURCES

- This manuscript reviews the current literature from the past decades available for traditional subjective pathology scoring paradigms and known cognitive and visual traps relevant to these scoring paradigms.

CONCLUSIONS

- Awareness of the gold standard paradox is necessary when using traditional pathologist scores to analytically validate a tIA tool because image analysis is used specifically to overcome known sources of bias in visual assessment of tissue sections.

The Causes of Errors in Clinical Reasoning: Cognitive Biases, Knowledge Deficits, and Dual Process Thinking

Contemporary theories of clinical reasoning espouse a dual processing model, which consists of a rapid, intuitive component (Type 1) and a slower, logical and analytical component (Type 2). Although the general consensus is that this dual processing model is a valid representation of clinical reasoning, the causes of diagnostic errors remain unclear. Cognitive theories about human memory propose that such errors may arise from both Type 1 and Type 2 reasoning. Errors in Type 1 reasoning may be a consequence of the associative nature of memory, which can lead to cognitive biases. However, the literature indicates that, with increasing expertise (and knowledge), the likelihood of errors decreases. Errors in Type 2 reasoning may result from the limited capacity of working memory, which constrains computational processes. In this article, the authors review the medical literature to answer two substantial questions that arise from this work: (1) To what extent do diagnostic errors originate in Type 1 (intuitive) processes versus in Type 2 (analytical) processes? (2) To what extent are errors a consequence of cognitive biases versus a consequence of knowledge deficits?The literature suggests that both Type 1 and Type 2 processes contribute to errors. Although it is possible to experimentally induce cognitive biases, particularly availability bias, the extent to which these biases actually contribute to diagnostic errors is not well established. Educational strategies directed at the recognition of biases are ineffective in reducing errors; conversely, strategies focused on the reorganization of knowledge to reduce errors have small but consistent benefits.

"First, know thyself": cognition and error in medicine

Although error is an integral part of the world of medicine, physicians have always been little inclined to take into account their own mistakes and the extraordinary technological progress observed in the last decades does not seem to have resulted in a significant reduction in the percentage of diagnostic errors. The failure in the reduction in diagnostic errors, notwithstanding the considerable investment in human and economic resources, has paved the way to new strategies which were made available by the development of cognitive psychology, the branch of psychology that aims at understanding the mechanisms of human reasoning. This new approach led us to realize that we are not fully rational agents able to take decisions on the basis of logical and probabilistically appropriate evaluations. In us, two different and mostly independent modes of reasoning coexist: a fast or non-analytical reasoning, which tends to be largely automatic and fast-reactive, and a slow or analytical reasoning, which permits to give rationally founded answers. One of the features of the fast mode of reasoning is the employment of standardized rules, termed "heuristics." Heuristics lead physicians to correct choices in a large percentage of cases. Unfortunately, cases exist wherein the heuristic triggered fails to fit the target problem, so that the fast mode of reasoning can lead us to unreflectively perform actions exposing us and others to variable degrees of risk. Cognitive errors arise as a result of these cases. Our review illustrates how cognitive errors can cause diagnostic problems in clinical practice.

Satisfaction of Search in Chest Radiography 2015

RATIONALE AND OBJECTIVES

Two decades have passed since the publication of laboratory studies of satisfaction of search (SOS) in chest radiography. Those studies were performed using film. The current investigation tests for SOS effects in computed radiography of the chest.

METHODS

Sixty-four chest computed radiographs half demonstrating various "test" abnormalities were read twice by 20 radiologists, once with and once without the addition of a simulated pulmonary nodule. Receiver-operating characteristic detection accuracy and decision thresholds were analyzed to study the effects of adding the nodule on detecting the test abnormalities. Results of previous studies were reanalyzed using similar modern techniques.

RESULTS

In the present study, adding nodules did not influence detection accuracy for the other abnormalities (P = .93), but did induce a reluctance to report them (P < .001). Adding nodules did not affect inspection time (P = .58) so the reluctance to report was not associated with reduced search. Reanalysis revealed a similar decision threshold shift that had not been recognized in the early studies of SOS in chest radiography (P < .01) in addition to reduced detection accuracy (P < .01).

CONCLUSIONS

The nature of SOS in chest radiography has changed, but it is not clear why.

ADVANCES IN KNOWLEDGE

SOS may be changing as a function of changes in radiology education and practice.

Multiple-Target Visual Search Errors

Visual search—the ability to locate visual targets among distractors—is a fundamental part of professional performance for many careers, including radiology, airport security screening, cytology, lifeguarding, and more. Successful execution of visual search in these settings is critically important because the consequences of a missed target can be horrific. Unfortunately, many of these professions place high demands on the people performing the searches, and either the task or the environment (or both) could lead to significant errors. One known source of error that exists across many fields is “multiple-target visual search” errors—a target is less likely to be detected if another target was already found in the same search than if the target was the only one present. These errors have proven to be stubborn and not easily eliminated. This article offers a brief overview of the existing research on multiple-target visual search errors and discusses possible policy implications of the errors for airport security screening. The policy suggestions are based on empirical research, with the hope of providing food for thought on using scientific data and theory to improve performance. Specifically, three policy suggestions are raised: shift screening to a remote location away from the checkpoint, reduce the number of prohibited items to lessen the searchers’ cognitive burden, and emphasize search consistency in the training process. Note that the focus here is on airport security screening, as this is a domain most readers can relate to, but the suggestions can equally apply to many search environments.

Cancer-associated unsuspected pulmonary embolism

Clinically unsuspected pulmonary embolism (UPE) is frequently diagnosed in cancer patients undergoing routine computed tomography scans for staging purposes or treatment response evaluation. The reported incidence of UPE ranges from 1% to 5% which probably represents an underestimation. A significant proportion of cancer patients with UPE actually do have pulmonary embolism (PE) related symptoms. However, these can erroneously be attributed to the cancer itself or to cancer therapy leading to a delayed or missed diagnosis. The incidence of UPE is likely to increase further with the improvements of imaging techniques. Radiologic features of UPE appear similar to symptomatic PE with nearly half of the UPE located in central pulmonary arteries and one third involving both lungs. UPE in cancer patients is not a benign condition with rates of recurrent venous thromboembolic events, bleeding and a mortality rate comparable to cancer patients with symptomatic PE. Current guidelines suggest that UPE should receive similar initial and long-term anticoagulant treatment as for symptomatic PE. However, direct evidence regarding the treatment of UPE is scarce and treatment indications are largely derived from studies performed in cancer patients with symptomatic venous thromboembolism. Selected subgroups of cancer patients with UPE such as those with sub-segmental UPE may be treated conservatively by withholding anticoagulation and avoiding the associated bleeding risk, although this requires further evaluation.