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Objective: To test the performance of ChatGPT on radiology questions formulated by the Colégio Brasileiro de Radiologia (CBR, Brazilian College of Radiology), evaluating its failures and successes. Materials and Methods: 165 questions from the CBR annual resident assessment (2018, 2019, and 2022) were presented to ChatGPT. For statistical analysis, the questions were divided by the type of cognitive skills assessed (lower or higher order), by topic (physics or clinical), by subspecialty, by style (description of a clinical finding or sign, clinical management of a case, application of a concept, calculation/classification of findings, correlations between diseases, or anatomy), and by target academic year (all, second/third year, or third year only). Results: ChatGPT answered 88 (53.3%) of the questions correctly. It performed significantly better on the questions assessing lower-order cognitive skills than on those assessing higher-order cognitive skills, providing the correct answer on 38 (64.4%) of 59 questions and on only 50 (47.2%) of 106 questions, respectively (p = 0.01). The accuracy rate was significantly higher for physics questions than for clinical questions, correct answers being provided for 18 (90.0%) of 20 physics questions and for 70 (48.3%) of 145 clinical questions (p = 0.02). There was no significant difference in performance among the subspecialties or among the academic years (p > 0.05). Conclusion: Even without dedicated training in this field, ChatGPT demonstrates reasonable performance, albeit still insufficient for approval, on radiology questions formulated by the CBR.

Objetivo: Testar o desempenho do ChatGPT em questões de radiologia formuladas pelo Colégio Brasileiro de Radiologia (CBR), avaliando seus erros e acertos. Materiais e Métodos: 165 questões da avaliação anual dos residentes do CBR (2018, 2019 e 2022) foram apresentadas ao ChatGPT. Elas foram divididas, para análise estatística, em questões que avaliavam habilidades cognitivas de ordem superior ou inferior e de acordo com a subespecialidade, o tipo da questão (descrição de um achado clínico ou sinal, manejo clínico de um doente, aplicação de um conceito, cálculo ou classificação dos achados descritos, associação entre doenças ou anatomia) e o ano da residência (R1, R2 ou R3). Resultados: O ChatGPT acertou 53,3% das questões (88/165). Houve diferença estatística entre o desempenho em questões de ordem cognitiva inferior (64,4%; 38/59) e superior (47,2%; 50/106) (p = 0,01). Houve maior índice de acertos em física (90,0%; 18/20) do que em questões clínicas (48,3%; 70/145) (p = 0,02). Não houve diferença significativa de desempenho entre subespecialidades ou ano de residência (p > 0,05). Conclusão: Mesmo sem treinamento dedicado a essa área, o ChatGPT apresenta desempenho razoável, mas ainda insuficiente para aprovação, em questões de radiologia formuladas pelo CBR.

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Abstract Objective: To test the performance of ChatGPT on radiology questions formulated by the Colégio Brasileiro de Radiologia (CBR, Brazilian College of Radiology), evaluating its failures and successes. Materials and Methods: 165 questions from the CBR annual resident assessment (2018, 2019, and 2022) were presented to ChatGPT. For statistical analysis, the questions were divided by the type of cognitive skills assessed (lower or higher order), by topic (physics or clinical), by subspecialty, by style (description of a clinical finding or sign, clinical management of a case, application of a concept, calculation/classification of findings, correlations between diseases, or anatomy), and by target academic year (all, second/third year, or third year only). Results: ChatGPT answered 88 (53.3%) of the questions correctly. It performed significantly better on the questions assessing lower-order cognitive skills than on those assessing higher-order cognitive skills, providing the correct answer on 38 (64.4%) of 59 questions and on only 50 (47.2%) of 106 questions, respectively (p = 0.01). The accuracy rate was significantly higher for physics questions than for clinical questions, correct answers being provided for 18 (90.0%) of 20 physics questions and for 70 (48.3%) of 145 clinical questions (p = 0.02). There was no significant difference in performance among the subspecialties or among the academic years (p > 0.05). Conclusion: Even without dedicated training in this field, ChatGPT demonstrates reasonable performance, albeit still insufficient for approval, on radiology questions formulated by the CBR.

Resumo Objetivo: Testar o desempenho do ChatGPT em questões de radiologia formuladas pelo Colégio Brasileiro de Radiologia (CBR), avaliando seus erros e acertos. Materiais e Métodos: 165 questões da avaliação anual dos residentes do CBR (2018, 2019 e 2022) foram apresentadas ao ChatGPT. Elas foram divididas, para análise estatística, em questões que avaliavam habilidades cognitivas de ordem superior ou inferior e de acordo com a subespecialidade, o tipo da questão (descrição de um achado clínico ou sinal, manejo clínico de um doente, aplicação de um conceito, cálculo ou classificação dos achados descritos, associação entre doenças ou anatomia) e o ano da residência (R1, R2 ou R3). Resultados: O ChatGPT acertou 53,3% das questões (88/165). Houve diferença estatística entre o desempenho em questões de ordem cognitiva inferior (64,4%; 38/59) e superior (47,2%; 50/106) (p = 0,01). Houve maior índice de acertos em física (90,0%; 18/20) do que em questões clínicas (48,3%; 70/145) (p = 0,02). Não houve diferença significativa de desempenho entre subespecialidades ou ano de residência (p > 0,05). Conclusão: Mesmo sem treinamento dedicado a essa área, o ChatGPT apresenta desempenho razoável, mas ainda insuficiente para aprovação, em questões de radiologia formuladas pelo CBR.

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Cutaneous myiasis is an endemic infestation in Latin America and Africa. Many unusual sites of larval infection can cause diagnostic confusion, especially if the patient is not from an endemic area. In the breast, the furuncular aspect suggests some differential diagnosis. We report a case of an 84-year-old patient with an ulcerated lesion on the right breast, who was referred to the reference service to exclude malignancy. Considering the clinical aspects and after further evaluation with imaging methods, she was diagnosed with myiasis. This study reinforces the importance of differential diagnosis of myiasis in patients that come from endemic areas.

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BACKGROUND: The effects of dose reduction in lung nodule detection need better understanding. PURPOSE: To compare the detection rate of simulated lung nodules in a chest phantom using different computed tomography protocols, low dose (LD), ultralow dose (ULD), and conventional (CCT), and to quantify their respective amount of radiation. MATERIALS AND METHODS: A chest phantom containing 93 simulated lung nodules was scanned using five different protocols: ULD (80 kVp/30 mA), LD A (120 kVp/20 mA), LD B (100 kVp/30 mA), LD C (120 kVp/30 mA), and CCT (120 kVp/automatic mA). Four chest radiologists analyzed a selected image from each protocol and registered in diagrams the nodules they detected. Kruskal-Wallis and McNemar's tests were performed to determine the difference in nodule detection. Equivalent doses were estimated by placing thermoluminescent dosimeters on the surface and inside the phantom. RESULTS: There was no significant difference in lung nodules' detection when comparing ULD and LD protocols (p=0.208 to p=1.000), but there was a significant difference when comparing each one of those against CCT (p < 0.001). The detection rate of nodules with CT attenuation values lower than -600 HU was also different when comparing all protocols against CCT (p < 0.001 to p=0.007). There was at least moderate agreement between observers in all protocols (κ-value >0.41). Equivalent dose values ranged from 0.5 to 9 mSv. CONCLUSION: There is no significant difference in simulated lung nodules' detection when comparing ULD and LD protocols, but both differ from CCT, especially when considering lower-attenuating nodules.

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BACKGROUND: Olfactory dysfunction is frequent in COVID-19 and it might occur along with pulmonary involvement. These manifestations do not seem to share pathophysiological mechanisms, but clinical data on the subject is lacking. Aims/Objectives: This study aims to correlate the olfactory function (OF) and the radiological pulmonary involvement among in-hospital patients with COVID-19. MATERIALS AND METHODS: Patients hospitalized with severe COVID-19 were consecutively recruited. They had their objective OF evaluated by the Alcohol Sniff Test and underwent a chest computed tomography (cCT). Qualitative and quantitative analyses of the cCT scans were performed by a blinded radiologist. The quantitative assessment included both the grade of involved parenchyma and the CT severity score (CT-SS). Data obtained were then compared. RESULTS: 57 patients were included. There was no correlation between the OF and the grade of lung involvement (p-value: .884) or the CT-SS (Pearson's coefficient: -.111). Yet, patients with radiological findings on the cCT typical for COVID-19 did not present significantly different OF from the remaining (p-value: .193). Conclusions: Olfactory dysfunction does not correlate with the radiological lung involvement in patients hospitalized with COVID-19. SIGNIFICANCE: There is also clinical evidence that the olfactory disorder and the pulmonary disease in COVID-19 have distinct mechanisms.Supplemental data for this article is available online at here.

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BACKGROUND: Appropriate mammary positioning is an important factor in optimizing image quality in mammography (MMG). PURPOSE: To study the correlation of quality criteria and breast density classification proposed by the American College of Radiology (ACR) and European Guidelines and its influence to achieve a proper positioning, therefore an adequate MMG. MATERIAL AND METHODS: A total of 128 routine MMG examinations were reviewed for the definition of breast composition parenchyma and assessment of several quality criteria proposed by the ACR and European Guidelines to achieve an adequate MMG. Adequate MMG was defined as a difference between the posterior nipple line (PNL), difference of the mediolateral oblique (MLO) and craniocaudal (CC) incidences > 1 cm. The quality criteria were analyzed as a function of correlation coefficient in order to evaluate the individual impact of each factor and analysis of variance (ANOVA) for all criteria. Receiver operating characteristic (ROC) curves were plotted to evaluate the performance of the criteria on each type of parenchyma. RESULTS: Negative correlation of fatty breasts and visibility of the mammary angle, a greater number of skin folds and PNL > 1 cm (r < 0). Dense MMG presented less visibility of the lateral tissue compared with other categories. Area under the curve of ROC analysis revealed values of 53.1% and 54.7% for the right and left breasts, respectively. CONCLUSION: Several factors influenced in the MMG process, but we find that breast parenchyma has a substantial role in affecting these criteria and therefore a correct position for diagnosis, which could compromise MMG diagnostic performance.

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BACKGROUND: Image-guided charcoal injection in suspicious breast lesions for preoperative localization is a procedure that has been increasing over the years because it is safer, faster, and more affordable when compared to needle-wire preoperative localization. To date, no complications have been associated with the method. However, in recent years there have been some reports about charcoal granulomas mimicking malignant lesions in some postoperative patients or in a conservative follow-up. PURPOSE: To report a series of 11 cases which had suspicious imaging findings for malignancy and resulted in charcoal granulomas on histopathological analysis. MATERIAL AND METHODS: A database of 1650 patients that attended our center from January 2007 to June 2018 was reviewed and detected 495 patients who had been previously submitted to ultrasound-guided charcoal marking in a breast lesion. Then, patients whose imaging studies were compatible with new suspicious lesions on mammography, breast ultrasound, and/or magnetic resonance imaging and biopsy of this new lesion indicating charcoal granuloma were selected. RESULTS: From 495 patients who had undergone charcoal localization injections in previous biopsies, we selected 11 who had new lesions with malignant characteristics on imaging studies but histopathological analysis resulted in charcoal granuloma. CONCLUSION: Charcoal granuloma should be considered in patients with previous preoperative injection localization, since the residual charcoal in the breast tissue may form granulomas and mimic malignant lesions on follow-up imaging studies.