To evaluate the diagnostic performance of ultrasound, MRI and fluorine-18 fludeoxyglucose positron emission tomography (¹⁸F-FDG PET)/CT for the diagnosis of metastatic axillary lymph node (ALN) after neoadjuvant chemotherapy (NAC) and to find out histopathological factors affecting the diagnostic performance of these imaging modalities. From January 2012 to November 2014, 191 consecutive patients with breast cancer who underwent NAC before surgery were retrospectively reviewed. We included 139 patients with ALN metastasis that was confirmed on fine needle aspiration or core needle biopsy at initial diagnosis. After NAC, 39 (28%) patients showed negative conversion of ALN on surgical specimens of sentinel lymph node (LN) or ALN. The sensitivity of ultrasound, MRI and PET/CT was 50% (48/96), 72% (70/97) and 22% (16/73), respectively. The specificity of ultrasound, MRI and PET/CT was 77% (30/39), 54% (21/39) and 85% (22/26), respectively. The Az value of combination of ultrasound and PET/CT was the highest (0.634) followed by ultrasound (0.626) and combination of ultrasound, MRI and PET/CT (0.617). The size of tumour deposit in LN and oestrogen receptor was significantly associated with the diagnostic performance of ultrasound (p < 0.001 and p = 0.009, respectively) and MRI (p = 0.045 and p = 0.036, respectively). The percentage diameter decrease, size of tumour deposit in LN, progesterone receptor, HER2 and histological grade were significantly associated with the diagnostic performance of PET/CT (p = 0.023, p = 0.002, p = 0.036, p = 0.044 and p = 0.008, respectively). On multivariate logistic regression analysis, size of tumour deposit within LN was identified as being independently associated with diagnostic performance of ultrasound [odds ratio, 13.07; 95% confidence interval (CI), 2.95-57.96] and PET/CT (odds ratio, 6.47; 95% CI, 1.407-29.737). Combination of three imaging modalities showed the highest sensitivity, and PET/CT showed the highest specificity for the evaluation of ALN metastasis after NAC. Ultrasound alone or combination of ultrasound and PET/CT showed the highest positive-predictive value. The size of tumour deposit within ALN was significantly associated with diagnostic performance of ultrasound and PET/CT. This study is about the diagnostic performance of ultrasound, MRI, PET/CT and combination of each imaging modality for the evaluation of metastatic ALN after NAC. Of many histopathological factors, only the size of tumour deposit within ALN was an independent factor associated with the diagnostic performance of ultrasound and PET/CT.

Hwang HJ, et al. Korean J Radiol. 2023 Aug;24(8):807-820. https://doi.org/10.3348/kjr.2023.0088

This study aimed to assess the diagnostic accuracy and safety of CT-guided percutaneous core needle biopsy (PCNB) with a coaxial needle for the diagnosis of lung cancer in patients with an usual interstitial pneumonia (UIP) pattern of interstitial lung disease. This study included 70 patients with UIP and suspected to have lung cancer. CT-guided PCNB was performed using a 20-gauge coaxial cutting needle. The diagnostic accuracy, sensitivity, specificity, and percentage of nondiagnostic results for PCNB were determined in comparison with the final diagnosis. PCNB-related complications were evaluated. Additionally, the risk factors for nondiagnostic results and pneumothorax were analyzed. The overall diagnostic accuracy, sensitivity, and specificity were 85.7%, 85.5%, and 87.5%, respectively. The percentage of nondiagnostic results was 18.6% (13/70). Two or less biopsy sampling was a risk factor for nondiagnostic results (p = 0.003). The overall complication rate was 35.7% (25/70), and pneumothorax developed in 22 patients (31.4%). A long transpulmonary needle path was a risk factor for the development of pneumothorax (p = 0.007). CT-guided PCNB using a coaxial needle is an effective method with reasonable accuracy and an acceptable complication rate for the diagnosis of lung cancer, even in patients with UIP.

Background: The deep learning-based nodule detection (DLD) system improves nodule detection performance of observers on chest radiographs (CXRs). However, its performance in different pulmonary nodule (PN) locations remains unknown. Methods: We divided the CXR intrathoracic region into non-danger zone (NDZ) and danger zone (DZ). The DZ included the lung apices, paramediastinal areas, and retrodiaphragmatic areas, where nodules could be missed. We used a dataset of 300 CXRs (100 normal and 200 abnormal images with 216 PNs [107 NDZ and 109 DZ nodules]). Eight observers (two thoracic radiologists [TRs], two non-thoracic radiologists [NTRs], and four radiology residents [RRs]) interpreted each radiograph with and without the DLD system. The metric of lesion localization fraction (LLF; the number of correctly localized lesions divided by the total number of true lesions) was used to evaluate the diagnostic performance according to the nodule location. Results: The DLD system demonstrated a lower LLF for the detection of DZ nodules (64.2) than that of NDZ nodules (83.2, p = 0.008). For DZ nodule detection, the LLF of the DLD system (64.2) was lower than that of TRs (81.7, p < 0.001), which was comparable to that of NTRs (56.4, p = 0.531) and RRs (56.7, p = 0.459). Nonetheless, the LLF of RRs significantly improved from 56.7 to 65.6 using the DLD system (p = 0.021) for DZ nodule detection. Conclusion: The performance of the DLD system was lower in the detection of DZ nodules compared to that of NDZ nodules. Nonetheless, RR performance in detecting DZ nodules improved upon using the DLD system. Critical relevance statement: Despite the deep learning-based nodule detection system’s limitations in detecting danger zone nodules, it proves beneficial for less-experienced observers by providing valuable assistance in identifying these nodules, thereby advancing nodule detection in clinical practice. Key points: • The deep learning-based nodule detection (DLD) system can improve the diagnostic performance of observers in nodule detection. • The DLD system shows poor diagnostic performance in detecting danger zone nodules. • For less-experienced observers, the DLD system is helpful in detecting danger zone nodules. Graphical

Deciding whether to include or exclude the papillary muscles and trabeculae to blood pool is essential, because quantifications of left ventricular (LV) functional parameters and myocardial mass are significantly affected. As a result, such inclusion or exclusion might produce different indices for diagnosis and therapy. Using cardiac computed tomography (CT), we obtained standard values of the portion of papillary muscle and trabeculae in normal adults, and to find out how the inclusion or exclusion of papillary muscle and trabeculae affect LV functional parameters depending on the patient group. Excluding the papillary muscles from the LV mass results in easier automated contour detection using CT. The percentage portions of papillary muscle and trabeculae to LV end-diastolic volume (EDV) and LV mass (LVM) were 11.9 ± 5.6% and 20.2 ± 4.3%, respectively, significantly affecting disease diagnosis. Imaging should be consistent at follow-up and include or exclude the papillary muscles and trabeculae to avoid introducing significant differences between measurements.