To develop a risk stratification system that can predict axillary lymph node (LN) metastasis in invasive breast cancer based on the combination of shear wave elastography (SWE) and conventional ultrasound.A total of 619 participants pathologically diagnosed with invasive breast cancer underwent breast ultrasound examinations were recruited from a multicenter of 17 hospitals in China from August 2016 to August 2017. Conventional ultrasound and SWE features were compared between positive and negative LN metastasis groups. The regression equation, the weighting, and the counting methods were used to predict axillary LN metastasis. The sensitivity, specificity, and the areas under the receiver operating characteristic curve (AUC) were calculated.A significant difference was found in the Breast Imaging Reporting and Data System (BI-RADS) category, the "stiff rim" sign, minimum elastic modulus of the internal tumor and peritumor region of 3 mm between positive and negative LN groups (p < 0.05 for all). There was no significant difference in the diagnostic performance of the regression equation, the weighting, and the counting methods (p > 0.05 for all). Using the counting method, a 0-4 grade risk stratification system based on the four characteristics was established, which yielded an AUC of 0.656 (95% CI, 0.617-0.693, p < 0.001), a sensitivity of 54.60% (95% CI, 46.9%-62.1%), and a specificity of 68.99% (95% CI, 64.5%-73.3%) in predicting axillary LN metastasis.A 0-4 grade risk stratification system was developed based on SWE characteristics and BI-RADS categories, and this system has the potential to predict axillary LN metastases in invasive breast cancer.
Abstract Background: To determine the efficacy and safety of perineal nerve block (PNB) and modified perineal nerve block (PNB-1) in ultrasound-guided transperineal prostate biopsy(TPBx). Methods: 910 patients were enrolled from March 2019 to December 2021. They were divided into two groups based on their anesthesia methods: PNB group (375 patients) and PNB-1 group (535 patients). The pain scores were evaluated using visual analogue scale (VAS) at the start of anesthesia, during puncture biopsy, and one hour after operation.The chi-square test was used for comparison. Result :At the start of anesthesia, there was no significant difference in pain scores between the PNB and PNB-1 groups ( P >0.05), but there was a significant difference in pain scores between the two groups at the time of puncture ( P <0.05).Among them, the pain score for patients with a larger prostate volume in the PNB group was significantly higher than that for patients with a smaller prostate volume ( P <0.05), whereas the pain score for patients with a different prostate volume in the PNB-1 group was not significantly different ( P >0.05). Postoperative complications in the PNB-1 group were significantly less than those in the PNB group, and the postoperative urinary tract irritation sign was significantly less than that in the PNB group ( P <0.05). Conclusion :PNB-1 was a effective and safe anesthesia method, which could significantly reduce the pain during puncture biopsy, improve the anesthetic effect and provide the basis for puncture biopsy.
Giant phyllodes tumors are rare fibroepithelial neoplasms, usually defined as >10 cm. It is often difficult for pathologists to distinguish fibroadenomas from phyllodes tumors and determine the malignant potential level. The current treatment principle is to ensure the extended resection of tumors with a margin of 1 cm or more. For patients with multiple local recurrences or large tumors after surgery, simple mastectomy is recommended. Axillary management should be considered when breast cancer is diagnosed at the same time. We now present a rare case: a female patient found a right breast mass in 2014, and the mass had continued to grow for more than 7 months, and she was ultimately diagnosed with a giant phyllodes tumor with a diameter of 30 cm. Extensive resection is a suitable method to treat smaller phyllodes tumors, but giant phyllodes tumors require mastectomy, so the patient in this case underwent a total mastectomy. We removed the mass completely without destroying the normal tissue and structure. The treatment effect was obvious, and no related adverse events occurred during or after the operation, the postoperative recovery was good, and the patient was discharged once she was verified to be in a stable condition. This case is the first reported case of a patient who had a giant borderline phyllodes tumor with a diameter of 30 cm, underwent total mastectomy, and was followed up for 6 months without recurrence. The long-term effect of the treatment will be further evaluated after 5 years.
Abstract Background: Accurate prediction of axillary lymph node (ALN) involvement in early-stage breast cancer is important for determining appropriate axillary treatment and therefore avoiding unnecessary axillary surgery and complications. This study aimed to develop and validate an ultrasound radiomics nomogram for preoperative evaluation of the ALN burden. Methods: Data of 303 patients from Wuhan Tongji Hospital (training cohort) and 130 cases from Hunan Provincial Tumour Hospital (external validation cohort) between Jun 2016 and May 2019 were enrolled. Radiomic features were extracted from shear-wave elastography (SWE) and corresponding B-mode ultrasound (BMUS) images. Then, the minimum redundancy maximum relevance (MRMR) and least absolute shrinkage and selection operator (LASSO) algorithm were used to select ALN status-related features and construct the SWE and BMUS radiomic signatures. Proportional odds ordinal logistic regression was performed using the radiomic signature together with clinical data, and an ordinal nomogram was subsequently developed. We evaluated the performance of the nomogram using C-index, calibration, and compared it with clinical model. Results: Multivariate analysis indicated that SWE signature, US-reported LN status and molecular subtype were independent risk factors associated with ALN status. The radiomics nomogram based on these variables showed good calibration and discrimination in the training set (overall C-index: 0.842; 95%CI, 0.773–0.879) and the validation set (overall C-index: 0.822; 95%CI, 0.765–0.838). For discriminating between disease-free axilla (N0) and any axillary metastasis (N + (≥1)), it achieved C-index of 0.845 (95%CI, 0.777–0.914) for the training cohort and 0.817 (95%CI, 0.769–0.865) for the validation cohort. The tool could also discriminate between low (N + (1–2)) and heavy metastatic burden of ALN (N + (≥3)), with C-index of 0.827 (95%CI, 0.742–0.913) for the training cohort and 0.810 (95%CI, 0.755–0.864) for the validation cohort. Conclusions: The presented radiomics nomogram shows favourable predictive ability for ALN staging in patients with early-stage breast cancer, which could provide incremental information for preoperative decision-making.
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