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Background: Attainment of a complete histopathological response following neoadjuvant therapy has been associated with favorable long-term survival outcomes in esophageal cancer patients. We investigated the ability of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET/CT) radiomic features to predict the pathological response to neoadjuvant treatment in patients with esophageal cancer. Materials and methods: A retrospective review of medical records of patients with locally advanced resectable esophageal or esophagogastric junctional cancers. Included patients had a baseline FDG PET/CT scan and underwent Chemoradiotherapy for Oesophageal Cancer Followed by Surgery Study (CROSS) protocol followed by surgery. Four demographic variables and 107 PET radiomic features were extracted and analyzed using univariate and multivariate analyses to predict response to neoadjuvant therapy. Results: Overall, 53 FDG-avid primary esophageal cancer lesions were segmented and radiomic features were extracted. Seventeen radiomic features and 2 non-radiomics variables were found to exhibit significant differences between neoadjuvant therapy responders and non-responders. An unsupervised hierarchical clustering analysis using these 19 variables classified patients in a manner significantly associated with response to neoadjuvant treatment (p < 0.01). Conclusion: Our findings highlight the potential of FDG PET/CT radiomic features as a predictor for the response to neoadjuvant therapy in esophageal cancer patients. The combination of these radiomic features with select non-radiomic variables provides a model for stratifying patients based on their likelihood to respond to neoadjuvant treatment.
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BACKGROUND: Retroperitoneal sarcomas (RPSs) present a surgical challenge, with complex anatomic relationships to organs and vascular structures. This pilot study investigated the role of three-dimensional (3D) augmented reality (3DAR) compared with standard imaging in preoperative planning and resection strategies. METHODS: For the study, 13 patients who underwent surgical resection of their RPS were selected based on the location of their tumor (right, left, pelvis). From the patients' preoperative computed tomography (CT) scans, 3DAR models were created using a D2P program and projected by an augmented-reality (AR) glass (Hololens). The 3DAR models were evaluated by three experienced sarcoma surgeons and compared with the baseline two-dimensional (2D) contrast-enhanced CT scans. RESULTS: Three members of the surgical team evaluated 13 models of retroperitoneal sarcomas, resulting in a total of 26 responses. When the surgical team was asked to evaluate whether the 3DAR better prepared the surgeon for planned surgical resection, 10 responses favored the 3DAR, 5 favored the 2D CT scans and 11 showed no difference (p = 0.074). According to 15 (57.6 %) of the 26 responses, the 3DAR offered additional value over standard imaging in the preoperative planning (median score of 4; range, 1-5). The median stated likelihood that the surgeons would consult the 3DAR was 5 (range, 2-5) for the preoperative setting and 3 (range, 1-5) for the intraoperative setting. CONCLUSIONS: This pilot study suggests that the use of 3DAR may provide additional value over current standard imaging in the preoperative planning for surgical resection of RPS, and the technology merits further study.
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ABSTRACT: A 67-year-old woman underwent staging 18 F-FDG PET/CT scan for recently diagnosed breast cancer. Her scan showed a highly hypermetabolic right breast mass, with ipsilateral hypermetabolic axillary lymph nodes. The contralateral axillary lymph nodes were also enlarged with avid FDG uptake, alongside focal increased uptake in the left deltoid muscle. Upon investigation, the patient reported receiving the new zoster recombinant adjuvanted varicella zoster vaccine (Shingrix, GlaxoSmithKline) 4 days before the scan. The lymph node uptake could be potential pitfall for cancer staging.
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Neoplasias da Mama , Linfadenopatia , Feminino , Humanos , Idoso , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Fluordesoxiglucose F18 , Herpesvirus Humano 3 , Linfonodos/diagnóstico por imagem , Linfonodos/patologia , Neoplasias da Mama/patologia , Vacinação , Linfadenopatia/diagnóstico por imagem , Linfadenopatia/etiologiaRESUMO
PURPOSE: 68 Ga-fibroblast activation protein inhibitor (FAPI), a new PET/CT radiotracer targeting cancer-associated fibroblasts in tumor microenvironment, can detect many types of cancer. We aimed to assess whether it can also be used for response assessment and follow-up. METHODS: We followed up patients with FAPI-avid invasive lobular breast cancer (ILC) before and after treatment changes and correlated qualitative maximal intensity projection images and quantitative tumor volume with CT results and blood tumor biomarkers. RESULTS: Six consenting ILC breast cancer patients (53 ± 8 years old) underwent a total of 24 scans (baseline for each patient and 2-4 follow-up scans). We found a strong correlation between 68 Ga-FAPI tumor volume and blood biomarkers ( r = 0.7, P < 0.01), but weak correlation between CT and 68 Ga-FAPI maximal intensity projection-based qualitative response assessment. CONCLUSIONS: We found a strong correlation between ILC progression and regression (as assessed by blood biomarkers) and 68 Ga-FAPI tumor volume. 68 Ga-FAPI PET/CT could possibly be used for disease response assessment and follow-up.
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Neoplasias da Mama , Humanos , Feminino , Neoplasias da Mama/diagnóstico por imagem , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Seguimentos , Biomarcadores Tumorais/sangue , Pessoa de Meia-Idade , Estudos ProspectivosRESUMO
PURPOSE: Invasive lobular breast cancer (ILC) may be hard to detect using conventional imaging modalities and usually shows less avidity to 18 F-FDG PET/CT. 68 Ga-fibroblast activation protein inhibitor (FAPI) PET/CT has shown promising results in detecting non- 18 F-FDG-avid cancers. We aimed to assess the feasibility of detecting metastatic disease in patients with non- 18 F-FDG-avid ILC. METHODS: This prospective study included patients with metastatic ILC, infiltrative to soft tissues, which was not 18 F-FDG avid. The patients underwent 68 Ga-FAPI PET/CT for evaluation, which was correlated with the fully diagnostic CT performed at the same time. RESULTS: Seven women (aged 57 ± 10 years) were included. Among the 30 organs and structures found to be involved by tumor, the number of findings observed by FAPI PET/CT was significantly higher than that observed by CT alone ( P = 0.022), especially in infiltrative soft tissue and serosal locations. CONCLUSIONS: This small pilot trial suggests a role for 68 Ga-FAPI PET/CT in ILC, which needs to be confirmed by subsequent trials.
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Neoplasias da Mama , Carcinoma Lobular , Humanos , Feminino , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Neoplasias da Mama/diagnóstico por imagem , Fluordesoxiglucose F18 , Estudos Prospectivos , Carcinoma Lobular/diagnóstico por imagem , Radioisótopos de GálioRESUMO
OBJECTIVES: To evaluate if radiomics with machine learning can differentiate between F-18-fluorodeoxyglucose (FDG)-avid breast cancer metastatic lymphadenopathy and FDG-avid COVID-19 mRNA vaccine-related axillary lymphadenopathy. MATERIALS AND METHODS: We retrospectively analyzed FDG-positive, pathology-proven, metastatic axillary lymph nodes in 53 breast cancer patients who had PET/CT for follow-up or staging, and FDG-positive axillary lymph nodes in 46 patients who were vaccinated with the COVID-19 mRNA vaccine. Radiomics features (110 features classified into 7 groups) were extracted from all segmented lymph nodes. Analysis was performed on PET, CT, and combined PET/CT inputs. Lymph nodes were randomly assigned to a training (n = 132) and validation cohort (n = 33) by 5-fold cross-validation. K-nearest neighbors (KNN) and random forest (RF) machine learning models were used. Performance was evaluated using an area under the receiver-operator characteristic curve (AUC-ROC) score. RESULTS: Axillary lymph nodes from breast cancer patients (n = 85) and COVID-19-vaccinated individuals (n = 80) were analyzed. Analysis of first-order features showed statistically significant differences (p < 0.05) in all combined PET/CT features, most PET features, and half of the CT features. The KNN model showed the best performance score for combined PET/CT and PET input with 0.98 (± 0.03) and 0.88 (± 0.07) validation AUC, and 96% (± 4%) and 85% (± 9%) validation accuracy, respectively. The RF model showed the best result for CT input with 0.96 (± 0.04) validation AUC and 90% (± 6%) validation accuracy. CONCLUSION: Radiomics features can differentiate between FDG-avid breast cancer metastatic and FDG-avid COVID-19 vaccine-related axillary lymphadenopathy. Such a model may have a role in differentiating benign nodes from malignant ones. KEY POINTS: ⢠Patients who were vaccinated with the COVID-19 mRNA vaccine have shown FDG-avid reactive axillary lymph nodes in PET-CT scans. ⢠We evaluated if radiomics and machine learning can distinguish between FDG-avid metastatic axillary lymphadenopathy in breast cancer patients and FDG-avid reactive axillary lymph nodes. ⢠Combined PET and CT radiomics data showed good test AUC (0.98) for distinguishing between metastatic axillary lymphadenopathy and post-COVID-19 vaccine-associated axillary lymphadenopathy. Therefore, the use of radiomics may have a role in differentiating between benign from malignant FDG-avid nodes.
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Neoplasias da Mama , COVID-19 , Linfadenopatia , Neoplasias da Mama/patologia , Vacinas contra COVID-19/efeitos adversos , Feminino , Fluordesoxiglucose F18 , Humanos , Linfonodos/diagnóstico por imagem , Linfonodos/patologia , Linfadenopatia/diagnóstico por imagem , Linfadenopatia/etiologia , Linfadenopatia/patologia , Metástase Linfática/patologia , Projetos Piloto , Tomografia por Emissão de Pósitrons combinada à Tomografia Computadorizada , Estudos Retrospectivos , Vacinação , Vacinas Sintéticas , Vacinas de mRNARESUMO
BACKGROUND: Medical imaging and the resultant ionizing radiation exposure is a public concern due to the possible risk of cancer induction. OBJECTIVES: To assess the accuracy of ultra-low-dose (ULD) chest computed tomography (CT) with denoising versus normal dose (ND) chest CT using the Lung CT Screening Reporting and Data System (Lung-RADS). METHODS: This prospective single-arm study comprised 52 patients who underwent both ND and ULD scans. Subsequently AI-based denoising methods were applied to produce a denoised ULD scan. Two chest radiologists independently and blindly assessed all scans. Each scan was assigned a Lung-RADS score and grouped as 1 + 2 and 3 + 4. RESULTS: The study included 30 men (58%) and 22 women (42%); mean age 69.9 ± 9 years (range 54-88). ULD scan radiation exposure was comparable on average to 3.6-4.8% of the radiation depending on patient BMI. Denoising increased signal-to-noise ratio by 27.7%. We found substantial inter-observer agreement in all scans for Lung-RADS grouping. Denoised scans performed better than ULD scans when negative likelihood ratio (LR-) was calculated (0.04--0.08 vs. 0.08-0.12). Other than radiation changes, diameter measurement differences and part-solid nodules misclassification as a ground-glass nodule caused most Lung-RADS miscategorization. CONCLUSIONS: When assessing asymptomatic patients for pulmonary nodules, finding a negative screen using ULD CT with denoising makes it highly unlikely for a patient to have a pulmonary nodule that requires aggressive investigation. Future studies of this technique should include larger cohorts and be considered for lung cancer screening as radiation exposure is radically reduced.
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Neoplasias Pulmonares/diagnóstico por imagem , Doses de Radiação , Tomografia Computadorizada por Raios X/métodos , Idoso , Idoso de 80 Anos ou mais , Estudos de Coortes , Feminino , Humanos , Neoplasias Pulmonares/patologia , Masculino , Pessoa de Meia-Idade , Variações Dependentes do Observador , Estudos Prospectivos , Exposição à RadiaçãoRESUMO
OBJECTIVE: To investigate the patterns of breast cancer-related and lactation-related 18F-FDG uptake in breasts of lactating patients with pregnancy-associated breast cancer (PABC) and without breast cancer. METHODS: 18F-FDG-PET/CT datasets of 16 lactating patients with PABC and 16 non-breast cancer lactating patients (controls) were retrospectively evaluated. Uptake was assessed in the tumor and non-affected lactating tissue of the PABC group, and in healthy lactating breasts of the control group, using maximum and mean standardized uptake values (SUVmax and SUVmean, respectively), and breast-SUVmax/liver-SUVmean ratio. Statistical tests were used to evaluate differences and correlations between the groups. RESULTS: Physiological uptake in non-breast cancer lactating patients' breasts was characteristically high regardless of active malignancy status other than breast cancer (SUVmax = 5.0 ± 1.7, n = 32 breasts). Uptake correlated highly between the two breasts (r = 0.61, p = 0.01), but was not correlated with age or lactation duration (p = 0.24 and p = 0.61, respectively). Among PABC patients, the tumors demonstrated high 18F-FDG uptake (SUVmax = 7.8 ± 7.2, n = 16), which was 326-643% higher than the mostly low physiological FDG uptake observed in the non-affected lactating parenchyma of these patients (SUVmax = 2.1 ± 1.1). Overall, 18F-FDG uptake in lactating breasts of PABC patients was significantly decreased by 59% (p < 0.0001) compared with that of lactating controls without breast cancer. CONCLUSION: 18F-FDG uptake in lactating tissue of PABC patients is markedly lower compared with the characteristically high physiological uptake among lactating patients without breast cancer. Consequently, breast tumors visualized by 18F-FDG uptake in PET/CT were comfortably depicted on top of the background 18F-FDG uptake in lactating tissue of PABC patients. KEY POINTS: ⢠FDG uptake in the breast is characteristically high among lactating patients regardless of the presence of an active malignancy other than breast cancer. ⢠FDG uptake in non-affected lactating breast tissue is significantly lower among PABC patients compared with that in lactating women who do not have breast cancer. ⢠In pregnancy-associated breast cancer patients, 18F-FDG uptake is markedly increased in the breast tumor compared with uptake in the non-affected lactating tissue, enabling its prompt visualization on PET/CT.