Lymph node FNA cytology: Diagnostic performance and clinical implications of proposed diagnostic categories

2021 ◽  
Author(s):  
Vladislav V. Makarenko ◽  
Michelle E. DeLelys ◽  
Robert P. Hasserjian ◽  
Amy Ly
2014 ◽  
Vol 53 (03) ◽  
pp. 89-94 ◽  
Author(s):  
D. H. Lee ◽  
J.-K Yoon ◽  
S. J. Lee ◽  
T. H. Kim ◽  
D. K. Kang ◽  
...  

SummaryThe aim of this study was to evaluate the diagnostic abilities of 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) compared with those of ultrasonography and magnetic resonance imaging (MRI) for axillary lymph node staging in breast cancer patients. Patients, methods: Pre- operative 18F-FDG PET/non-contrast CT, ultrasonography and MRI were performed in 215 women with breast cancer. Axillary lymph node dissection was performed in all patients and the diagnostic performance of each modality was evaluated using histopathologic assessments as the reference standard. ROC curves were compared to evaluate the diagnostic ability of several imaging modalities (i. e., ultrasonography, MRI and 18F-FDG PET/CT). Results: In total, 132 patients (61.4%) had axillary lymph node metastasis. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for the detection of axillary lymph node metastasis were 72.3%, 77.3%, 66.7%, 81.6%, 75.3% for ultrasonography, 67.5%, 78.0%, 65.9%, 79.2%, 74.0% for MRI, and 62.7%, 88.6%, 77.6%, 79.1%, 78.6% for 18F-FDG PET/CT, respectively. There was no significant difference in diagnostic ability among the imaging modalities (i.e., ultrasonography, MRI and 18F-FDG PET/CT). The diagnostic ability of 18F-FDG PET/CT was significantly improved by combination with MRI (p = 0.0002) or ultrasonography (p < 0.0001). The combination of 18F-FDG PET/CT with ultrasonography had a similar diagnostic ability to that of all three modalities combined (18F-FDG PET/CT+ultraso- nography+MRI, p = 0.05). Conclusion: The diagnostic performance of 18F-FDG PET/CT for detection of axillary node metastasis was not significantly different from that of ultrasonography or MRI in breast cancer patients. Combining 18F-FDG PET/CT with ultrasonography or MRI could improve the diagnostic performance compared to 18F-FDG PET/CT alone.


2021 ◽  
Author(s):  
Naresh Kumar Regula ◽  
Vasileios Kostaras ◽  
Silvia Johansson ◽  
Carlos Trampal ◽  
Elin Lindström ◽  
...  

Abstract 18F-NaF positron emission tomography/computed tomography (fluoride PET/CT) is considered the most sensitive technique to detect bone metastasis in prostate cancer (PCa). 68Ga-PSMA-11 (PSMA) PET/CT is increasingly used for staging of PCa. This study primarily aimed to compare the diagnostic performance of fluoride PET/CT and Gallium based PSMA PET/CT in identifying bone metastasis followed by a comparison of PSMA PET/CT with contrast-enhanced CT (CE-CT) in identifying soft tissue lesions as a secondary objective. Methods: Twenty-eight PCa patients with high suspicion of disseminated disease following curative treatment were prospectively evaluated. PET/CT examinations using fluoride and PSMA were performed. All suspicious bone lesions were counted, and the tracer uptake was measured as standardized uptake values (SUV) for both tracers. In patients with multiple findings, ten bone lesions with highest SUVmax were selected from which identical lesions from both scans were considered for direct comparison of SUVmax. Soft tissue findings of local and lymph node lesions from CE-CT were compared with PSMA PET/CT. Results: Both scans were negative for bone lesions in 7 patients (25%). Of 699 lesions consistent with skeletal metastasis in 21 patients on fluoride PET/CT, PSMA PET/CT identified 579 lesions (83%). In 69 identical bone lesions fluoride PET/CT showed significantly higher uptake (mean SUVmax: 73.1±36.8) compared to PSMA PET/CT (34.5±31.4; p<0.001). Compared to CE-CT, PSMA PET/CT showed better diagnostic performance in locating local (96% vs 61%, p=0.004) and lymph node (94% vs 46%, p<0.001) metastasis. Conclusion: In this prospective comparative study PSMA PET/CT detected the majority of bone lesions that were positive on fluoride PET/CT. Further, this study indicates better diagnostic performance of PSMA PET/CT to locate soft tissue lesions compared to CE-CT.


2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e12583-e12583
Author(s):  
Jian Li ◽  
Cai Nian ◽  
Xie Ze-Ming ◽  
Zhou Jingwen ◽  
Huang Kemin

e12583 Background: To improve the performance of ultrasound (US) for diagnosing metastatic axillary lymph node (ALN), machine learning was used to reveal the inherently medical hints from ultrasonic images and assist pre-treatment evaluation of ALN for patients with early breast cancer. Methods: A total of 214 eligible patients with 220 breast lesions, from whom 220 target ALNs of ipsilateral axillae underwent ultrasound elastography (UE), were prospectively recruited. Based on feature extraction and fusion of B-mode and shear wave elastography (SWE) images of 140 target ALNs using radiomics and deep learning, with reference to the axillary pathological evaluation from training cohort, a proposed deep learning-based heterogeneous model (DLHM) was established and then validated by a collection of B-mode and SWE images of 80 target ALNs from testing cohort. Performance was compared between UE based on radiological criteria and DLHM in terms of areas under the receiver operating characteristics curve (AUC), sensitivity, specificity, accuracy, negative predictive value, and positive predictive value for diagnosing ALN metastasis. Results: DLHM achieved an excellent performance for both training and validation cohorts. In the prospectively testing cohort, DLHM demonstrated the best diagnostic performance with AUC of 0.911(95% confidence interval [CI]: 0.826, 0.963) in identifying metastatic ALN, which significantly outperformed UE in terms of AUC (0.707, 95% CI: 0.595, 0.804, P<0.001). Conclusions: DLHM provides an effective, accurate and non-invasive preoperative method for assisting the diagnosis of ALN metastasis in patients with early breast cancer.[Table: see text]


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