Breast Imaging Reporting and Data System (BI-RADS®): a success history and particularities of its use in Brazil.

BI-RADS® is a standardization system for breast imaging reports and results created by the American College of Radiology to initially address the lack of uniformity in mammography reporting. The system consists of a lexicon of descriptors, a reporting structure with final categories and recommended management, and a structure for data collection and auditing. It is accepted worldwide by all specialties involved in the care of breast diseases. Its implementation is related to the Mammography Quality Standards Act initiative in the United States (1992) and breast cancer screening. After its initial creation in 1993, four additional editions were published in 1995, 1998, 2003 and 2013. It is adopted in several countries around the world and has been translated into 6 languages. Successful breast cancer screening programs in high-income countries can be attributed in part to the widespread use of BI-RADS®. This success led to the development of similar classification systems for other organs (e.g., lung, liver, thyroid, ovaries, colon). In 1998, the structured report model was adopted in Brazil. This article highlights the pioneering and successful role of BI-RADS®, created by ACR 30 years ago, on the eve of publishing its sixth edition, which has evolved into a comprehensive quality assurance tool for multiple imaging modalities. And, especially, it contextualizes the importance of recognizing how we are using BI-RADS® in Brazil, from its implementation to the present day, with a focus on breast cancer screening.

Impact of preoperative body composition in patients with renal cell carcinoma submitted to surgical treatment / Impacto da composição corporal pré-operatória em pacientes com carcinoma de células renais submetidos a tratamento cirúrgico

Abstract Objective: To evaluate the impact of preoperative body composition in patients with renal cell carcinoma (RCC) undergoing surgical treatment. Materials and Methods: This was a retrospective study of 52 patients with RCC undergoing total or partial nephrectomy. Body composition assessment was performed using the body mass index, together with computed tomography analysis at the level of the third lumbar vertebra to measure the area of visceral adipose tissue, as well as the area and density of skeletal muscle mass. Results: Malnutrition, obesity and inadequate skeletal muscle gauge (SMG) were associated with higher hospital length of stay (p = 0.028, p = 0.02 and p = 0.012, respectively). Although the rates of postoperative symptoms and readmissions were low, survival was better among the patients with an adequate SMG than among those with an inadequate SMG (p = 0.003). Conclusion: Among patients with RCC undergoing surgical treatment, preoperative body composition does not seem to be associated with the rates of perioperative complications, although an inadequate SMG seems to be associated with worse overall survival.

Resumo Objetivo Avaliar o impacto da composição corporal pré-operatória em pacientes portadores de carcinoma de células renais (CCR) submetidos a tratamento cirúrgico. Materiais e Métodos: Foi realizado estudo retrospectivo de 52 pacientes portadores de CCR submetidos a tratamento cirúrgico. A avaliação da composição corporal foi realizada por meio do índice de massa corporal e análise da L3 obtida pela tomografia computadorizada para mensurar a área do tecido adiposo visceral, área e densidade da massa muscular esquelética. Resultados: Os pacientes desnutridos, obesos e que apresentaram produto muscular esquelético (PME) inadequado permaneceram mais tempo internados (p = 0,028, p = 0,02 e p = 0,012, respectivamente). As taxas de sintomas e reinternações no pósoperatório foram baixas em toda a amostra, no entanto, observou-se que pacientes com PME inadequado apresentaram uma pior sobrevida em relação aos pacientes com PME adequado (p = 0,003). Conclusão: A análise da composição corporal pré-operatória não mostrou associação com as taxas de complicações periope-ratórias em pacientes portadores de CCR submetidos a nefrectomia total ou parcial, no entanto, a inadequação do PME está associada a uma pior sobrevida.

Are we ready to stratify BI-RADS 4 lesions observed on magnetic resonance imaging? A real-world noninferiority/equivalence analysis / Estamos prontos para estratificar lesões BI-RADS 4 na ressonância magnética? Uma análise de não inferioridade/equivalência do mundo real

Abstract Objective: To demonstrate that positive predictive values (PPVs) for suspicious (category 4) magnetic resonance imaging (MRI) findings that have been stratified are equivalent to those stipulated in the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) for mammography and ultrasound. Materials and Methods: This retrospective analysis of electronic medical records generated between January 4, 2016 and December 29, 2021 provided 365 patients in which 419 suspicious (BI-RADS category 4) findings were subcategorized as BI-RADS 4A, 4B or 4C. Malignant and nonmalignant outcomes were determined by pathologic analyses, follow-up, or both. For each subcategory, the level 2 PPV (PPV2) was calculated and tested for equivalence/noninferiority against the established benchmarks. Results: Of the 419 findings evaluated, 168 (40.1%) were categorized as malignant and 251 (59.9%) were categorized as nonmalignant. The PPV2 for subcategory 4A was 14.2% (95% CI: 9.3-20.4%), whereas it was 41.2% (95% CI: 32.8-49.9%) for subcategory 4B and 77.2% (95% CI: 68.4-84.5%) for subcategory 4C. Multivariate analysis showed a significantly different cancer yield for each subcategory (p < 0.001). Conclusion: We found that stratification of suspicious findings by MRI criteria is feasible, and malignancy probabilities for sub-categories 4B and 4C are equivalent to the values established for the other imaging methods in the BI-RADS. Nevertheless, low suspicion (4A) findings might show slightly higher malignancy rates.

Resumo Objetivo: Demonstrar que os valores preditivos positivos (VPPs) para lesões suspeitas (categoria 4) identificadas por ressonância magnética (RM) são equivalentes aos estipulados no ACR BI-RADS para mamografia e ultrassonografia. Materiais e Métodos: Análise retrospectiva de dados em prontuário eletrônico, entre 4 de janeiro de 2016 e 29 de dezembro de 2021, resultou em 365 pacientes elegíveis, com 419 lesões classificadas como BI-RADS 4A, 4B ou 4C. Desfechos malignos e não malignos foram determinados por estudo patológico e/ou acompanhamento. Realizamos o cálculo do VPP nível 2 (VPP2) para cada subcategoria e testamos para não inferioridade/equivalência em relação aos valores de referência. Resultados: Dos 419 achados, 168 (40,1%) foram malignos e 251 (59,9%), não malignos. O VPP2 para subcategoria 4A foi 14,2% (IC 95%: 9,3-20,4%), para 4B foi 41,2% (IC 95%:, 32,8-49,9%) e para 4C foi 77,2% (IC 95%: 68,4-84,5%). Análise multivariada demonstrou diferenças estatisticamente significantes entre as subcategorias (p < 0,001). Conclusão: A estratificação de achados suspeitos por RM é factível, sendo que a probabilidade de malignidade das subcategorias 4B e 4C é equivalente à estabelecida para outros métodos de imagem pelo BI-RADS. Contudo, lesões de baixa suspeição (4A) podem apresentar taxas mais altas de malignidade.

Application of artificial intelligence in predicting malignancy risk in breast masses on ultrasound / Aplicação de inteligência artificial na predição de risco de malignidade em nódulos mamários na ultrassonografia

Abstract Objective: To evaluate the results obtained with an artificial intelligence-based software for predicting the risk of malignancy in breast masses from ultrasound images. Materials and Methods: This was a retrospective, single-center study evaluating 555 breast masses submitted to percutaneous biopsy at a cancer referral center. Ultrasonographic findings were classified in accordance with the BI-RADS lexicon. The images were analyzed by using Koios DS Breast software and classified as benign, probably benign, low to intermediate suspicion, high suspicion, or probably malignant. The histological classification was considered the reference standard. Results: The mean age of the patients was 51 years, and the mean mass size was 16 mm. The radiologist evaluation had a sensitivity and specificity of 99.1% and 34.0%, respectively, compared with 98.2% and 39.0%, respectively, for the software evaluation. The positive predictive value for malignancy for the BI-RADS categories was similar between the radiologist and software evaluations. Two false-negative results were identified in the radiologist evaluation, the masses in question being classified as suspicious by the software, whereas four false-negative results were identified in the software evaluation, the masses in question being classified as suspicious by the radiologist. Conclusion: In our sample, the performance of artificial intelligence-based software was comparable to that of a radiologist.

Resumo Objetivo: O objetivo deste trabalho foi avaliar os resultados de um software baseado em algoritmo de inteligência artificial para predição do risco de malignidade em nódulos mamários. Materiais e Métodos: Estudo retrospectivo e unicêntrico que avaliou 555 nódulos mamários submetidos a biópsia percutânea em um centro de referência oncológico. Os achados ultrassonográficos foram classificados de acordo com o léxico do BI-RADS. As imagens foram analisadas pelo software Koios DS Breast e divididas em benigna ou provavelmente benigna, suspeita baixa ou intermediária, suspeita alta ou provavelmente maligna. O resultado histopatológico foi considerado como padrão ouro. Resultados: A média de idade das pacientes foi de 51 anos e o tamanho médio dos nódulos foi de 16 mm. A sensibilidade e a especificidade foram de 99,1% e 34,0% para o radiologista e 98,2% e 39,0% para o software, respectivamente. O valor preditivo positivo para malignidade para as categorias BIRADS foi semelhante para o radiologista e para o software. Foram identificados dois resultados falso-negativos na avaliação pelo radiologista que foram classificados como suspeitos pelo software, e quatro resultados falso-negativos na avaliação pelo software que foram classificados como suspeitos pelo radiologista. Conclusão: Na nossa amostra, o software de inteligência artificial demonstrou resultados comparáveis à avaliação pelo radiologista.

Analysis of muscle mass by computed tomography in patients with head and neck cancer: a prospective study / Análise da massa muscular por tomografia computadorizada em pacientes com câncer de cabeça e pescoço: um estudo prospectivo

Abstract Objective: To evaluate the preoperative muscle mass of patients with head and neck cancer (HNC) with computed tomography (CT), comparing the results obtained through analysis of cross-sectional areas at the level of the third lumbar vertebra (L3) with those obtained through analysis of cross-sectional areas at the levels of the third cervical and fourth thoracic vertebrae (C3 and T4, respectively). Materials and Methods: A total of 63 patients with HNC were evaluated preoperatively. Using CT, we assessed muscle mass at L3, as well as at C3 and T4. Results: Most (73.0%) of the patients had low muscle mass at L3, whereas 50.8% had a normal body mass index. The cross-sectional area at L3 correlated strongly with those at C3 and T4 (r = 0.831 and r = 0.763, respectively; p < 0.001 for both). In addition, the muscle mass index at L3 correlated strongly with those at C3 and T4 (r = 0.781 and r = 0.715, respectively; p < 0.001 for both). Conclusion: Low muscle mass appears to be highly prevalent in patients with HNC. Measurements at C3 and T4 could represent alternative means of assessing muscle mass in such patients.

Resumo Objetivo: Avaliar e comparar a massa muscular de pacientes com câncer de cabeça e pescoço (CCP) durante o período pré-operatório com tomografia computadorizada (TC), por meio da análise das áreas transversais no nível da terceira vértebra lombar (L3) em comparação com níveis cervical (C3) e torácico (T4). Materiais e Métodos: Sessenta e três pacientes com CCP foram avaliados no pré-operatório. A TC foi utilizada para avaliar a massa muscular de L3, assim como as secções transversais de C3 e T4. Resultados: A maioria dos pacientes (73,0%) tinha baixa massa muscular analisada pela TC de L3, mas índice de massa corpórea normal (50,8%). Também foi observada forte correlação entre as áreas e o índice de massa muscular (IMM) de L3 com C3 (área: r = 0,831, p < 0,001; IMM: r = 0,781, p < 0,001) e T4 (área: r = 0,763, p < 0,001; IMM: r = 0,715, p < 0,001). Conclusão: A baixa massa muscular é altamente prevalente em pacientes com CCP. As análises de TC em C3 e T4 podem representar opção para avaliar a massa muscular em pacientes com CCP.

Vacuum-assisted excision of breast lesions in surgical de-escalation: where are we?

Vacuum-assisted excision of breast lesions has come to be widely used in clinical practice. Increased acceptance and availability of the procedure, together with the use of larger needles, has allowed the removal of a greater amount of sample, substantially reducing the surgical upgrade rate and thus increasing the reliability of the results of the procedure. These characteristics result in the potential for surgical de-escalation in selected cases and gain strength in a scenario in which the aim is to reduce costs, as well as the rates of underestimation and overtreatment, without compromising the quality of patient care. The objective of this article is to review the technical parameters and current clinical indications for performing vacuum-assisted excision of breast lesions.

A excisão assistida a vácuo de lesões mamárias tem sido cada vez mais utilizada na prática clínica. A sua maior aceitação e disponibilidade, em associação ao uso de agulhas mais calibrosas, permitiu a retirada de quantidade maior de amostra, reduzindo substancialmente a taxa de subestimação diagnóstica e aumentando, assim, a confiabilidade final dos resultados do procedimento. Essas características resultam em potencial descalonamento cirúrgico, em casos selecionados, e ganham força em um cenário em que se visa a redução de custos, taxa de subestimação e tratamento excessivo, porém, sem comprometer a qualidade no cuidado com o paciente. O objetivo deste trabalho é revisar os parâmetros técnicos e as indicações clínicas atuais para realização de excisão assistida a vácuo em lesões mamárias.

Breast cancer after thoracic radiotherapy in young patients: what does the radiologist need to know?

Radiation-induced secondary tumors constitute a rare complication of radiation therapy and typically occur in or near the irradiated area. Women who undergo thoracic radiotherapy before 30 years of age have a significantly greater lifetime risk of developing breast cancer than do those in the general population. It is recommended that a patient who has previously received thoracic radiotherapy with a radiation dose ≥ 10 Gy subsequently undergo annual screening with mammography and magnetic resonance imaging, beginning eight years after the initial treatment or when the patient has reached 25 years of age (whichever comes later). The treatment of secondary breast cancer in this population should be individualized and should be discussed with a multidisciplinary team to avoid toxicity related to the treatment of the primary cancer.

Os cânceres secundários induzidos por radiação são complicações raras da radioterapia e geralmente ocorrem na área tratada ou próximo a ela. Mulheres com menos de 30 anos de idade tratadas com radioterapia torácica têm risco significativamente aumentado de desenvolver câncer de mama ao longo da vida, em comparação com a população em geral. Para as pacientes tratadas com irradiação torácica com dose igual ou superior a 10 Gy é recomendado rastreamento anual com mamografia e ressonância magnética iniciando oito anos após o tratamento, desde que este início seja após 25 anos de idade. O tratamento do câncer de mama secundário nessa população deve ser individualizado e discutido com equipe multidisciplinar, para evitar toxicidade relacionada ao tratamento do câncer primário.

Breast cancer after thoracic radiotherapy in young patients: what does the radiologist need to know? / Câncer de mama após radioterapia torácica em pacientes jovens: o que o radiologista precisa saber?

Abstract Radiation-induced secondary tumors constitute a rare complication of radiation therapy and typically occur in or near the irradiated area. Women who undergo thoracic radiotherapy before 30 years of age have a significantly greater lifetime risk of developing breast cancer than do those in the general population. It is recommended that a patient who has previously received thoracic radiotherapy with a radiation dose ≥ 10 Gy subsequently undergo annual screening with mammography and magnetic resonance imaging, beginning eight years after the initial treatment or when the patient has reached 25 years of age (whichever comes later). The treatment of secondary breast cancer in this population should be individualized and should be discussed with a multidisciplinary team to avoid toxicity related to the treatment of the primary cancer.

Resumo Os cânceres secundários induzidos por radiação são complicações raras da radioterapia e geralmente ocorrem na área tratada ou próximo a ela. Mulheres com menos de 30 anos de idade tratadas com radioterapia torácica têm risco significativamente aumentado de desenvolver câncer de mama ao longo da vida, em comparação com a população em geral. Para as pacientes tratadas com irradiação torácica com dose igual ou superior a 10 Gy é recomendado rastreamento anual com mamografia e ressonância magnética iniciando oito anos após o tratamento, desde que este início seja após 25 anos de idade. O tratamento do câncer de mama secundário nessa população deve ser individualizado e discutido com equipe multidisciplinar, para evitar toxicidade relacionada ao tratamento do câncer primário.

Vacuum-assisted excision of breast lesions in surgical de-escalation: where are we? / Excisão assistida a vácuo de lesões mamárias no descalonamento cirúrgico: onde estamos?

Abstract Vacuum-assisted excision of breast lesions has come to be widely used in clinical practice. Increased acceptance and availability of the procedure, together with the use of larger needles, has allowed the removal of a greater amount of sample, substantially reducing the surgical upgrade rate and thus increasing the reliability of the results of the procedure. These characteristics result in the potential for surgical de-escalation in selected cases and gain strength in a scenario in which the aim is to reduce costs, as well as the rates of underestimation and overtreatment, without compromising the quality of patient care. The objective of this article is to review the technical parameters and current clinical indications for performing vacuum-assisted excision of breast lesions.

Resumo A excisão assistida a vácuo de lesões mamárias tem sido cada vez mais utilizada na prática clínica. A sua maior aceitação e disponibilidade, em associação ao uso de agulhas mais calibrosas, permitiu a retirada de quantidade maior de amostra, reduzindo substancialmente a taxa de subestimação diagnóstica e aumentando, assim, a confiabilidade final dos resultados do procedimento. Essas características resultam em potencial descalonamento cirúrgico, em casos selecionados, e ganham força em um cenário em que se visa a redução de custos, taxa de subestimação e tratamento excessivo, porém, sem comprometer a qualidade no cuidado com o paciente. O objetivo deste trabalho é revisar os parâmetros técnicos e as indicações clínicas atuais para realização de excisão assistida a vácuo em lesões mamárias.

A Stochastic Grammar Approach to Mass Classification in Mammograms.

Breast cancer is responsible for approximately 15% of all cancer-related deaths among women worldwide, and early and accurate diagnosis increases the chances of survival. Over the last decades, several machine learning approaches have been used to improve the diagnosis of this disease, but most of them require a large set of samples for training. Syntactic approaches were barely used in this context, although it can present good results even if the training set has few samples. This article presents a syntactic approach to classify masses as benign or malignant. There were used features extracted from a polygonal representation of masses combined with a stochastic grammar approach to discriminate the masses found in mammograms. The results were compared with other machine learning techniques, and the grammar-based classifiers showed superior performance in the classification task. The best accuracies achieved were from 96% to 100%, indicating that grammatical approaches are robust and able to discriminate the masses even when trained with small samples of images. Syntactic approaches could be more frequently employed in the classification of masses, since they can learn the pattern of benign and malignant masses from a small sample of images achieving similar results when compared to the state of art.

Preoperative evaluation of sarcopenia in patients with colorectal cancer: a prospective study.

OBJECTIVE: Colorectal cancer is the third most diagnosed malignant neoplasm in the world and the fourth leading cause of cancer mortality. The loss of muscle mass in oncological patients is the main aspect of cancer-related malnutrition. Associations between sarcopenia and poor outcomes, such as high postoperative mortality, chemotherapy toxicity, and reduced survival, have been recently described. The aim of this study was to prospectively assess the prevalence of preoperative sarcopenia in patients with colorectal cancer using validated methods to evaluate muscle strength, muscle mass, and physical performance. METHODOLOGY: This study included patients with colorectal cancer undergoing oncological staging at a Cancer Center in Brazil from May 2019 to March 2020 who had images from abdominal computed tomography available for analysis of body composition. The muscle strength test, physical performance, referred fatigue, and clinical and nutritional data were evaluated. RESULTS: A total of 31 patients were included, and most were diagnosed with colon cancer (77.4%) and clinical stage II in 41.9% of cases. The prevalence of probable sarcopenia was 22.6%; of these patients, sarcopenia was confirmed in 19.4%, and ultimately, 9.7% of the sample was classified as severe sarcopenia. We did not find a significant association between the presence of sarcopenia in our sample and age, sex, tumor staging, nutritional characteristics, referred patient fatigue, or postoperative complications. CONCLUSION: Considering the criteria established by the EWGSOP, the prevalence of preoperative sarcopenia in colorectal cancer patients was 19.4%.

Preoperative evaluation of sarcopenia in patients with colorectal cancer: a prospective study

SUMMARY OBJECTIVE: Colorectal cancer is the third most diagnosed malignant neoplasm in the world and the fourth leading cause of cancer mortality. The loss of muscle mass in oncological patients is the main aspect of cancer-related malnutrition. Associations between sarcopenia and poor outcomes, such as high postoperative mortality, chemotherapy toxicity, and reduced survival, have been recently described. The aim of this study was to prospectively assess the prevalence of preoperative sarcopenia in patients with colorectal cancer using validated methods to evaluate muscle strength, muscle mass, and physical performance. METHODOLOGY: This study included patients with colorectal cancer undergoing oncological staging at a Cancer Center in Brazil from May 2019 to March 2020 who had images from abdominal computed tomography available for analysis of body composition. The muscle strength test, physical performance, referred fatigue, and clinical and nutritional data were evaluated. RESULTS: A total of 31 patients were included, and most were diagnosed with colon cancer (77.4%) and clinical stage II in 41.9% of cases. The prevalence of probable sarcopenia was 22.6%; of these patients, sarcopenia was confirmed in 19.4%, and ultimately, 9.7% of the sample was classified as severe sarcopenia. We did not find a significant association between the presence of sarcopenia in our sample and age, sex, tumor staging, nutritional characteristics, referred patient fatigue, or postoperative complications. CONCLUSION: Considering the criteria established by the EWGSOP, the prevalence of preoperative sarcopenia in colorectal cancer patients was 19.4%.

Impact of preoperative body composition in patients with renal cell carcinoma submitted to surgical treatment.

Objective: To evaluate the impact of preoperative body composition in patients with renal cell carcinoma (RCC) undergoing surgical treatment. Materials and Methods: This was a retrospective study of 52 patients with RCC undergoing total or partial nephrectomy. Body composition assessment was performed using the body mass index, together with computed tomography analysis at the level of the third lumbar vertebra to measure the area of visceral adipose tissue, as well as the area and density of skeletal muscle mass. Results: Malnutrition, obesity and inadequate skeletal muscle gauge (SMG) were associated with higher hospital length of stay (p = 0.028, p = 0.02 and p = 0.012, respectively). Although the rates of postoperative symptoms and readmissions were low, survival was better among the patients with an adequate SMG than among those with an inadequate SMG (p = 0.003). Conclusion: Among patients with RCC undergoing surgical treatment, preoperative body composition does not seem to be associated with the rates of perioperative complications, although an inadequate SMG seems to be associated with worse overall survival.

Objetivo: Avaliar o impacto da composição corporal pré-operatória em pacientes portadores de carcinoma de células renais (CCR) submetidos a tratamento cirúrgico. Materiais e Métodos: Foi realizado estudo retrospectivo de 52 pacientes portadores de CCR submetidos a tratamento cirúrgico. A avaliação da composição corporal foi realizada por meio do índice de massa corporal e análise da L3 obtida pela tomografia computadorizada para mensurar a área do tecido adiposo visceral, área e densidade da massa muscular esquelética. Resultados: Os pacientes desnutridos, obesos e que apresentaram produto muscular esquelético (PME) inadequado permaneceram mais tempo internados (p = 0,028, p = 0,02 e p = 0,012, respectivamente). As taxas de sintomas e reinternações no pósoperatório foram baixas em toda a amostra, no entanto, observou-se que pacientes com PME inadequado apresentaram uma pior sobrevida em relação aos pacientes com PME adequado (p = 0,003). Conclusão: A análise da composição corporal pré-operatória não mostrou associação com as taxas de complicações periope-ratórias em pacientes portadores de CCR submetidos a nefrectomia total ou parcial, no entanto, a inadequação do PME está associada a uma pior sobrevida.

Are we ready to stratify BI-RADS 4 lesions observed on magnetic resonance imaging? A real-world noninferiority/equivalence analysis.

Objective: To demonstrate that positive predictive values (PPVs) for suspicious (category 4) magnetic resonance imaging (MRI) findings that have been stratified are equivalent to those stipulated in the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) for mammography and ultrasound. Materials and Methods: This retrospective analysis of electronic medical records generated between January 4, 2016 and December 29, 2021 provided 365 patients in which 419 suspicious (BI-RADS category 4) findings were subcategorized as BI-RADS 4A, 4B or 4C. Malignant and nonmalignant outcomes were determined by pathologic analyses, follow-up, or both. For each subcategory, the level 2 PPV (PPV2) was calculated and tested for equivalence/noninferiority against the established benchmarks. Results: Of the 419 findings evaluated, 168 (40.1%) were categorized as malignant and 251 (59.9%) were categorized as nonmalignant. The PPV2 for subcategory 4A was 14.2% (95% CI: 9.3-20.4%), whereas it was 41.2% (95% CI: 32.8-49.9%) for subcategory 4B and 77.2% (95% CI: 68.4-84.5%) for subcategory 4C. Multivariate analysis showed a significantly different cancer yield for each subcategory (p < 0.001). Conclusion: We found that stratification of suspicious findings by MRI criteria is feasible, and malignancy probabilities for sub-categories 4B and 4C are equivalent to the values established for the other imaging methods in the BI-RADS. Nevertheless, low suspicion (4A) findings might show slightly higher malignancy rates.

Objetivo: Demonstrar que os valores preditivos positivos (VPPs) para lesões suspeitas (categoria 4) identificadas por ressonância magnética (RM) são equivalentes aos estipulados no ACR BI-RADS para mamografia e ultrassonografia. Materiais e Métodos: Análise retrospectiva de dados em prontuário eletrônico, entre 4 de janeiro de 2016 e 29 de dezembro de 2021, resultou em 365 pacientes elegíveis, com 419 lesões classificadas como BI-RADS 4A, 4B ou 4C. Desfechos malignos e não malignos foram determinados por estudo patológico e/ou acompanhamento. Realizamos o cálculo do VPP nível 2 (VPP2) para cada subcategoria e testamos para não inferioridade/equivalência em relação aos valores de referência. Resultados: Dos 419 achados, 168 (40,1%) foram malignos e 251 (59,9%), não malignos. O VPP2 para subcategoria 4A foi 14,2% (IC 95%: 9,3­20,4%), para 4B foi 41,2% (IC 95%:, 32,8­49,9%) e para 4C foi 77,2% (IC 95%: 68,4­84,5%). Análise multivariada demonstrou diferenças estatisticamente significantes entre as subcategorias (p < 0,001). Conclusão: A estratificação de achados suspeitos por RM é factível, sendo que a probabilidade de malignidade das subcategorias 4B e 4C é equivalente à estabelecida para outros métodos de imagem pelo BI-RADS. Contudo, lesões de baixa suspeição (4A) podem apresentar taxas mais altas de malignidade.

Application of artificial intelligence in predicting malignancy risk in breast masses on ultrasound.

Objective: To evaluate the results obtained with an artificial intelligence-based software for predicting the risk of malignancy in breast masses from ultrasound images. Materials and Methods: This was a retrospective, single-center study evaluating 555 breast masses submitted to percutaneous biopsy at a cancer referral center. Ultrasonographic findings were classified in accordance with the BI-RADS lexicon. The images were analyzed by using Koios DS Breast software and classified as benign, probably benign, low to intermediate suspicion, high suspicion, or probably malignant. The histological classification was considered the reference standard. Results: The mean age of the patients was 51 years, and the mean mass size was 16 mm. The radiologist evaluation had a sensitivity and specificity of 99.1% and 34.0%, respectively, compared with 98.2% and 39.0%, respectively, for the software evaluation. The positive predictive value for malignancy for the BI-RADS categories was similar between the radiologist and software evaluations. Two false-negative results were identified in the radiologist evaluation, the masses in question being classified as suspicious by the software, whereas four false-negative results were identified in the software evaluation, the masses in question being classified as suspicious by the radiologist. Conclusion: In our sample, the performance of artificial intelligence-based software was comparable to that of a radiologist.

Objetivo: O objetivo deste trabalho foi avaliar os resultados de um software baseado em algoritmo de inteligência artificial para predição do risco de malignidade em nódulos mamários. Materiais e Métodos: Estudo retrospectivo e unicêntrico que avaliou 555 nódulos mamários submetidos a biópsia percutânea em um centro de referência oncológico. Os achados ultrassonográficos foram classificados de acordo com o léxico do BI-RADS. As imagens foram analisadas pelo software Koios DS Breast e divididas em benigna ou provavelmente benigna, suspeita baixa ou intermediária, suspeita alta ou provavelmente maligna. O resultado histopatológico foi considerado como padrão ouro. Resultados: A média de idade das pacientes foi de 51 anos e o tamanho médio dos nódulos foi de 16 mm. A sensibilidade e a especificidade foram de 99,1% e 34,0% para o radiologista e 98,2% e 39,0% para o software, respectivamente. O valor preditivo positivo para malignidade para as categorias BIRADS foi semelhante para o radiologista e para o software. Foram identificados dois resultados falso-negativos na avaliação pelo radiologista que foram classificados como suspeitos pelo software, e quatro resultados falso-negativos na avaliação pelo software que foram classificados como suspeitos pelo radiologista. Conclusão: Na nossa amostra, o software de inteligência artificial demonstrou resultados comparáveis à avaliação pelo radiologista.

Analysis of muscle mass by computed tomography in patients with head and neck cancer: a prospective study.

Objective: To evaluate the preoperative muscle mass of patients with head and neck cancer (HNC) with computed tomography (CT), comparing the results obtained through analysis of cross-sectional areas at the level of the third lumbar vertebra (L3) with those obtained through analysis of cross-sectional areas at the levels of the third cervical and fourth thoracic vertebrae (C3 and T4, respectively). Materials and Methods: A total of 63 patients with HNC were evaluated preoperatively. Using CT, we assessed muscle mass at L3, as well as at C3 and T4. Results: Most (73.0%) of the patients had low muscle mass at L3, whereas 50.8% had a normal body mass index. The cross-sectional area at L3 correlated strongly with those at C3 and T4 (r = 0.831 and r = 0.763, respectively; p < 0.001 for both). In addition, the muscle mass index at L3 correlated strongly with those at C3 and T4 (r = 0.781 and r = 0.715, respectively; p < 0.001 for both). Conclusion: Low muscle mass appears to be highly prevalent in patients with HNC. Measurements at C3 and T4 could represent alternative means of assessing muscle mass in such patients.

Objetivo: Avaliar e comparar a massa muscular de pacientes com câncer de cabeça e pescoço (CCP) durante o período pré-operatório com tomografia computadorizada (TC), por meio da análise das áreas transversais no nível da terceira vértebra lombar (L3) em comparação com níveis cervical (C3) e torácico (T4). Materiais e Métodos: Sessenta e três pacientes com CCP foram avaliados no pré-operatório. A TC foi utilizada para avaliar a massa muscular de L3, assim como as secções transversais de C3 e T4. Resultados: A maioria dos pacientes (73,0%) tinha baixa massa muscular analisada pela TC de L3, mas índice de massa corpórea normal (50,8%). Também foi observada forte correlação entre as áreas e o índice de massa muscular (IMM) de L3 com C3 (área: r = 0,831, p < 0,001; IMM: r = 0,781, p < 0,001) e T4 (área: r = 0,763, p < 0,001; IMM: r = 0,715, p < 0,001). Conclusão: A baixa massa muscular é altamente prevalente em pacientes com CCP. As análises de TC em C3 e T4 podem representar opção para avaliar a massa muscular em pacientes com CCP.

Computed tomography assessment of body composition in patients with nonmetastatic breast cancer: what are the best prognostic markers?

Objective: To correlate body composition measures, based on computed tomography (CT) analysis of muscle mass and adipose tissue, with disease-free survival in breast cancer patients. Materials and Methods: This single-center retrospective study included 262 female patients with nonmetastatic breast cancer. Body composition was assessed on a pretreatment CT scan (at the L3 level). The analysis included quantification of the areas of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle mass, as well as of the mean skeletal muscle density. The VAT/SAT ratio, skeletal mass index (SMI), and skeletal muscle gauge (SMG) were calculated. Results: Of the 262 patients evaluated, 175 (66.8%) were classified as overweight or obese on the basis of their body mass index. We observed low SMI in 35 patients (13.4%) and elevated VAT in 123 (46.9%). Disease-free survival was significantly shorter in the patients who underwent neoadjuvant chemotherapy (p = 0.044), in those with a low SMI (p = 0.006), in those with low SMG (p = 0.013), and in those with a low VAT/SAT ratio (p = 0.050). In a multivariate analysis, only SMG, the VAT/SAT ratio, and having undergone neoadjuvant chemotherapy retained their statistical significance. Conclusion: Our results confirm that low SMG and the VAT/SAT ratio can be used as imaging biomarkers to assess prognosis in patients with nonmetastatic breast cancer.

Objetivo: Correlacionar medidas de composição corporal baseadas na análise por tomografia computadorizada (TC) da massa muscular e tecido adiposo com a sobrevida livre de doença em pacientes com câncer de mama. Materiais e Métodos: Estudo retrospectivo unicêntrico que incluiu 262 mulheres com câncer de mama não metastático. Avaliação da composição corporal foi realizada na TC pré-tratamento (nível de L3), incluindo tecido adiposo subcutâneo (SAT) e tecido adiposo visceral (VAT), massa muscular esquelética e densidade do músculo esquelético. A relação VAT/SAT, o índice de massa esquelética (SMI) e o produto do músculo esquelético (SMG) foram calculados. Resultados: De acordo com o índice de massa corporal, 175 (66,8%) pacientes foram classificadas com sobrepeso ou obesidade. Baixo SMI foi observado em 35 (13,4%) pacientes e VAT elevado, em 123 (46,9%). Houve uma redução significativa na sobrevida livre de doença nas pacientes que realizaram quimioterapia neoadjuvante (p = 0,044), nas com baixo SMI (p = 0,006), baixo SMG (p = 0,013) e baixa relação VAT/SAT (p = 0,050). Na análise multivariada, apenas SMG, relação VAT/SAT e quimioterapia neoadjuvante confirmaram significância estatística. Conclusão: Nossos resultados confirmaram que SMG e relação VAT/SAT baixos podem ser usados como importantes biomarcadores de imagem para avaliar o prognóstico em pacientes com câncer de mama não metastático.

Assessment of body composition by whole-body densitometry: what radiologists should know.

The analysis of body composition is a fundamental part of a nutritional status assessment, and the use of diagnostic imaging methods has been increasingly required for an adequate characterization of the lean body mass and fat mass. Body composition measurements are useful in evaluating the effectiveness of nutritional interventions and monitoring changes associated with aging and chronic diseases. Whole-body densitometry using dual-energy X-ray absorptiometry (DEXA) is one of the most widely used methods in clinical practice, allowing highly accurate assessment of the bone mineral content, lean body mass, and fat mass. Although a DEXA examination provides a lot of information, there is still no universal standardization of the parameters to be included in radiology reports. The aim of this study was to review the most relevant information for assessing body composition by whole-body densitometry.

A análise da composição corporal é parte fundamental de uma avaliação nutricional, em que a utilização de métodos diagnósticos por imagem tem sido cada vez mais requisitada para uma adequada caracterização da massa magra e massa gorda corporal. Medidas de composição corporal são úteis em avaliar a eficácia das intervenções nutricionais e monitorar as mudanças associadas ao envelhecimento e condições de doenças crônicas. A densitometria de corpo inteiro utilizando a técnica de absorciometria de dupla energia (DEXA) é um dos métodos mais utilizados na prática clínica, que permite avaliação com elevada acurácia do conteúdo mineral ósseo, da gordura corporal e da massa magra. Este exame fornece grande quantidade de informações, no entanto, ainda não existe uma padronização universal de quais parâmetros devem ser incluídos nos relatórios radiológicos. O objetivo deste trabalho é revisar as informações mais relevantes para avaliação da composição corporal fornecidas pela densitometria de corpo inteiro.

Computed tomography assessment of body composition in patients with nonmetastatic breast cancer: what are the best prognostic markers? / Avaliação da composição corporal por tomografia computadorizada em pacientes com câncer de mama não metastático: quais os melhores marcadores de prognóstico?

Abstract Objective: To correlate body composition measures, based on computed tomography (CT) analysis of muscle mass and adipose tissue, with disease-free survival in breast cancer patients. Materials and Methods: This single-center retrospective study included 262 female patients with nonmetastatic breast cancer. Body composition was assessed on a pretreatment CT scan (at the L3 level). The analysis included quantification of the areas of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and skeletal muscle mass, as well as of the mean skeletal muscle density. The VAT/SAT ratio, skeletal mass index (SMI), and skeletal muscle gauge (SMG) were calculated. Results: Of the 262 patients evaluated, 175 (66.8%) were classified as overweight or obese on the basis of their body mass index. We observed low SMI in 35 patients (13.4%) and elevated VAT in 123 (46.9%). Disease-free survival was significantly shorter in the patients who underwent neoadjuvant chemotherapy (p = 0.044), in those with a low SMI (p = 0.006), in those with low SMG (p = 0.013), and in those with a low VAT/SAT ratio (p = 0.050). In a multivariate analysis, only SMG, the VAT/SAT ratio, and having undergone neoadjuvant chemotherapy retained their statistical significance. Conclusion: Our results confirm that low SMG and the VAT/SAT ratio can be used as imaging biomarkers to assess prognosis in patients with nonmetastatic breast cancer.

Resumo Objetivo: Correlacionar medidas de composição corporal baseadas na análise por tomografia computadorizada (TC) da massa muscular e tecido adiposo com a sobrevida livre de doença em pacientes com câncer de mama. Materiais e Métodos: Estudo retrospectivo unicêntrico que incluiu 262 mulheres com câncer de mama não metastático. Avaliação da composição corporal foi realizada na TC pré-tratamento (nível de L3), incluindo tecido adiposo subcutâneo (SAT) e tecido adiposo visceral (VAT), massa muscular esquelética e densidade do músculo esquelético. A relação VAT/SAT, o índice de massa esquelética (SMI) e o produto do músculo esquelético (SMG) foram calculados. Resultados: De acordo com o índice de massa corporal, 175 (66,8%) pacientes foram classificadas com sobrepeso ou obesidade. Baixo SMI foi observado em 35 (13,4%) pacientes e VAT elevado, em 123 (46,9%). Houve uma redução significativa na sobrevida livre de doença nas pacientes que realizaram quimioterapia neoadjuvante (p = 0,044), nas com baixo SMI (p = 0,006), baixo SMG (p = 0,013) e baixa relação VAT/SAT (p = 0,050). Na análise multivariada, apenas SMG, relação VAT/SAT e quimioterapia neoadjuvante confirmaram significância estatística. Conclusão: Nossos resultados confirmaram que SMG e relação VAT/SAT baixos podem ser usados como importantes biomarcadores de imagem para avaliar o prognóstico em pacientes com câncer de mama não metastático.

Relationship between anxiety and internet searches before percutaneous ultrasound-guided diagnostic procedures: A prospective cohort study.

Invasive procedures guided by ultrasound (US) are part of routine medical diagnostic investigation. The lack of knowledge surrounding the technical aspects of such procedures can lead patients to seek complementary information on the Internet, which may in turn trigger anxiety. However, the intersection between the fields of Radiology and Psychology is poorly studied. Here, we identify the profile of an anxious patient before an US-guided intervention. We prospectively studied 133 patients undergoing image-guided procedures. The State-Trait Anxiety Inventory (STAI) was applied for psychometry. Significantly higher anxiety scores were observed in female patients (p = .001), those who believed they had received inadequate information from their referring physician (p = .006), and in patients who considered online information unreliable or difficult to access (p = .007 and p = .001, respectively). Participants who defined themselves as proactive online reported lower anxiety levels (p = .003).