To explore relationships between reader performance and reader characteristics in mammography for specific radiologist groupings on the basis of annual number of readings. The institutional review board approved the study and waived the need for patient consent to use all images. Readers gave informed consent. One hundred sixteen radiologists independently reviewed 60 mammographic cases: 20 cases with cancer and 40 cases with normal findings. Readers located any visualized cancer, and levels of confidence were scored from 1 to 5. A jackknifing free response operating characteristic (JAFROC) method was used, and figures of merit along with sensitivity and specificity were correlated with reader characteristics by using Spearman techniques and standard multiple regressions. Reader performance was positively correlated with number of years since qualification as a radiologist (P ≤ .01), number of years reading mammograms (P ≤ .03), and number of readings per year (P ≤ .0001). The number of years since qualification as a radiologist (P ≤ .004) and number of years of reading mammograms (P ≤ .002) were negatively related to JAFROC values for radiologists with annual volumes of less than 1000 mammographic readings. For individuals with more than 5000 mammographic readings per year, JAFROC values were positively related to the number of years that the reader was qualified as a radiologist (P ≤ .01), number of years of reading mammograms (P ≤ .002), and number of hours per week of reading mammograms (P ≤ .003). Number of mammographic readings per year was positively related with JAFROC scores for readers with an annual volume between 1000 and 5000 readings (P ≤ .03). Differences in JAFROC scores appear to be more related to specificity than location sensitivity, with the former demonstrating significant relationships with four of the five characteristics analyzed, whereas no relationships were shown for the latter. Radiologists' determinants of performance are associated with annual reading volumes. Ability to recognize normal images is a discriminating factor in individuals with a high volume of mammographic readings.

Purpose: To measure the effect of abnormality-prevalence expectation on experienced radiologists' performance during pulmonary nodular lesion detection on a chest radiograph. Materials and Methods: A multiobserver receiver operating characteristic (ROC) and eye-position analysis study was performed to assess the effect of prevalence expectation on observer performance. Twenty-two experienced radiologists were divided into three groups and each was asked to interpret 30 (15 abnormal) identical posteroanterior chest images twice and decide if pulmonary lesions were present. Before each viewing, the radiologists were told that the images contained a specific number of abnormal images: group 1: 9 and 15; group 2: 15 and 22; and group 3: 15 and not told. Results: ROC analysis demonstrated that no significant effect could be measured as a function of prevalence expectation (P > .05). However, eye-position analysis showed significant increases in eye movements at higher prevalence expectation rates in terms of the number of fixations per image (group 1: P = .0001; group 2: P = .0001; group 3: P = .001) and the total scrutiny time of each image (group 1: P = .0001; group 2: P = .0283; group 3: P = .028). Conclusion: Overall, findings of this study showed no evidence that the accuracy of expert radiologists is altered due to changing prevalence expectation rates. However, the time spent interpreting each image and the number of fixations increased at higher prevalence rates. Maintenance of diagnostic efficacy has been shown even when circumstances challenge normal observer behavior.

A reasonable level of agreement (P < .01) between actual clinical reporting and test set conditions in screening mammography can be achieved when describing group performance if prior images are pr... PurposeTo establish the extent to which test set reading can represent actual clinical reporting in screening mammography.Materials and MethodsInstitutional ethics approval was granted, and informe...

Three‐dimensional (3D) printing technology has demonstrated a huge potential for the future of medicine. Since its introduction, it has been used in various areas, for example building anatomical models, personalising medical devices and implants, aiding in precision medical interventions and the latest development, 3D bioprinting. This commentary is provided to outline the current use of 3D printing in medical imaging and its future directions for advancing the healthcare services.

Introduction: An ideal organ‐specific insert phantom should be able to simulate the anatomical features with appropriate appearances in the resultant computed tomography (CT) images. This study investigated a 3D printing technology to develop a novel and cost‐effective cardiac insert phantom derived from volumetric CT image datasets of anthropomorphic chest phantom.Methods: Cardiac insert volumes were segmented from CT image datasets, derived from an anthropomorphic chest phantom of Lungman N‐01 (Kyoto Kagaku, Japan). These segmented datasets were converted to a virtual 3D‐isosurface of heart‐shaped shell, while two other removable inserts were included using computer‐aided design (CAD) software program. This newly designed cardiac insert phantom was later printed by using a fused deposition modelling (FDM) process via a Creatbot DM Plus 3D printer. Then, several selected filling materials, such as contrast media, oil, water and jelly, were loaded into designated spaces in the 3D‐printed phantom. The 3D‐printed cardiac insert phantom was positioned within the anthropomorphic chest phantom and 30 repeated CT acquisitions performed using a multi‐detector scanner at 120‐kVp tube potential. Attenuation (Hounsfield Unit, HU) values were measured and compared to the image datasets of real‐patient and Catphan^® 500 phantom.Results: The output of the 3D‐printed cardiac insert phantom was a solid acrylic plastic material, which was strong, light in weight and cost‐effective. HU values of the filling materials were comparable to the image datasets of real‐patient and Catphan^® 500 phantom.Conclusions: A novel and cost‐effective cardiac insert phantom for anthropomorphic chest phantom was developed using volumetric CT image datasets with a 3D printer. Hence, this suggested the printing methodology could be applied to generate other phantoms for CT imaging studies.