ObjectiveTo explore the feasibility of homemade domestic breast palpation imaging (BPI) instead of clinical breast palpation examination (CBE) for screening breast masses. MethodsThe patients who received breast ultrasonography (BUS), BPI examinations and CBE in the Sichuan Cancer Hospital from March 2022 to September 2022 were retrospectively collected. The result of BUS examination was used as the criteria to compare the efficiency and difference between the BPI examination and CBE in detecting breast masses. The effects of the patients’ body mass index, breast volume, tumor location, benign and malignant tumor, and maximum tumor diameter on the accuracy of breast tumor detection by BPI system were further analyzed. ResultsA total of 102 patients were included in this study. Among the 90 patients with breast mass detected by BUS, 76 cases were detected by BPI and 51 cases were detected by CBE. In the 12 patients without tumor mass detected by BUS, only 11 cases patients without tumor mass were detected by BPI and CBE. The sensitivity and accuracy of breast tumor mass screening by the BPI were higher than those by the CBE (84.4% vs. 56.7%, 85.2% vs. 60.7%, respectively), and the specificity was similar (91.6%, both). The area under the receiver operating characteristic curve (95% confidence interval, 95%CI) of BPI and CBE for screening breast masses were 0.903 (0.791, 0.970) and 0.799 (0.747, 0.851), respectively. The former was higher than the latter (Z=2.494, P=0.013). The consistencies were moderate (Kappa=0.518, P<0.001), general (Kappa=0.204, P=0.002), moderate (Kappa=0.518, P<0.001) between the BPI and BUS, between CBE and BUS, and between BPI and CBE for screening breast masses, respectively. The results of multivariate analysis of binary logistics regression indicated that the benign tumor mass was not easily detected [OR (95%CI） was 9.600（1.328, 69.400), P=0.025] and the tumor mass with breast volume ＜350 mL was easily detected [OR (95%CI） was 0.157 (0.030, 0.818), P=0.028], the diameter of tumor mass had no obvious influence on breast tumor mass screening by the BPI. ConclusionAccording to the preliminary results of this study, BPI can improve the sensitivity of detecting breast masses and make up for the lack of objective records of CBE, but BPI cannot replace CBE at present.
Toexploretheinfluenceoflocalmassiveexcisionbeforeradicalsurgeryonprognosisofpatientswithbreastcancer,wecomparedtheprognosisbetweenthegroupunderwentlocalresectionpriortoradicalsurgery(106cases)andthegorupwithdirectradicalresection(143cases).Theresultsshowedthatthelocalrecurrencerate,distancemetastasisrateandthesurvivalrateat3,5yearsofthegroupunderwentlocalexcisionpriortoradicalsurgerywere16.0%,26.4%,79.2%,71.7%respectivelyandofthegroupunderwentdirectradicalresectionwere4.9%,16.1%,89.5%,82.5%respectively,thedeferencewassignificant(Plt;0.01,0.05,0.05,0.05respectively).Theresultsindicatethatthelocalexcisionbeforeradicalsurgerycanaffecttheprognosisofpatientswithbreastcancer.
目的:探讨麦默通装置在乳腺微创外科中的应用。方法:44例共113个乳腺多发肿块均采用麦默通装置8G穿刺针在彩超引导下进行肿块切除术,术后送常规病理检查。结果:所有肿块均为完全切除,大小为0.4--5.5cm,56个为临床不可扪及的肿块,占49.6%,存在两种以上的病理改变9例,占20.5%,手术平均耗时12.5min,平均出血18.6mL。术后8例局部青紫,3例切口下血肿,均保守治疗后痊愈,无切口感染与瘢痕发生。结论:彩超引导下麦默通乳腺微创旋切术是一种早期诊治乳腺肿瘤安全、合理、有效、符合美学观点的方法,尤其适用于多发和无法触及的肿块。
ObjectiveTo predict the risk factors affecting postoperative recurrence of granulomatous lobular mastitis (GLM) in the mass stage by machine learning algorithm, and to provide a reference for the early identification and prevention of postoperative recurrence of GLM in the mass stage. MethodsThe electronic medical records and follow-up data of patients with GLM in the Department of Breast Disease Unit, the First Affiliated Hospital of Henan University of Traditional Chinese Medicine from October 2020 to January 2023 were selected. A total of 340 patients with GLM in the mass stage who met the inclusion and exclusion criteria were selected as the research subjects. According to whether the patients relapsed after surgery, they were divided into recurrence group and non-recurrence group. The collected cases were randomly divided into training set and test set according to the ratio of 7:3. In the training set, the recurrence prediction model was constructed by using traditional logistic regression and three machine learning algorithms: artificial neural network, random forest and XGBoost (extrem gradient boosting). In the test set, the performance of the model was evaluated by sensitivity, specificity, accuracy,positive predictive value, negative predictive value, F1 value and area under the curve (AUC) value. The Shapley Additive exPlanation (SHAP) method was used to explore the important variables that affect the optimal model in identifying postoperative recurrence in the GLM mass phase. The optimal risk cutoff value of the prediction model was determined by the Youden index. Based on this, the postoperative patients in the GLM mass phase of the external test set were divided into high-risk and low-risk groups. ResultsA total of 392 patients who met the GLM mass stage were included, and 52 cases were excluded according to the exclusion criteria, and 340 cases were finally included, including 60 cases in the recurrence group and 280 cases in the non-recurrence group. Based on the results of univariate analysis, correlation analysis and clinically meaningful influencing factors, 12 non-zero coefficient characteristic variables were screened for the construction of the prediction model, and these 12 characteristic variables included other disease history, number of miscarriages, breastfeeding duration of the affected breast, history of milk stasis, lesion location, nipple indentation, fluctuation sensation, low-density lipoprotein, testosterone, previous antibiotic therapy, previous oral hormone medication, and perioperative traditional Chinese medicine treatment duration. The logistic regression prediction model, artificial neural network, random forest and XGBoost prediction models were constructed, and the results showed that the accuracy, positive predictive value and negative predictive value of the four prediction models were all >75%, among which the XGBoost model had the best performance, with accuracy, specificity, sensitivity, AUC, positive predictive value, negative predictive value and F1 values of 0.93, 0.99, 0.65, 0.87, 0.92, 0.93 and 0.76, respectively. SHAP method found that the duration of traditional Chinese medicine treatment during perioperative period, the duration of breast-feeding on the affected side, low density lipoprotein, testosterone and previous hormone drugs were the top five factors affecting XGBoost model to identify postoperative recurrence of GLM in mass stage. ConclusionsCompared with the traditional Logistic regression prediction model, the models based on machine learning for identifying postoperative recurrence in the GLM mass phase showed better performance, among which the XGBoost model performed best. Targeted preventive measures can be given based on the above risk factors to improve the postoperative prognosis of the GLM mass phase.
【摘要】目的探讨超声导向下Mammotome活检及旋切系统切除乳腺肿块的并发症及其处理。方法在超声导向下，利用Mammotome系统对乳腺肿块进行活检和切除，对出现的并发症进行及时的处理。结果46例患者的75个乳腺肿块被切除，病理证实68个为纤维腺瘤，7个为纤维腺病。术中并发症包括出血、血肿和胸大肌损伤，经及时处理后恢复，术后并发症为瘢痕形成。结论Mammotome乳腺肿块切除术具有创伤小、并发症少的优点，是一种有效的、不影响乳房外观的微创手术，超声监控能够减少和发现并发症并进行正确的处理。
目的:探讨乳腺良恶性肿块二维超声图像和彩色多普勒血流状况,提高乳腺肿块的超声诊断符合率。方法:回顾性分析105例乳腺肿块的二维及彩色多普勒超声图像特点。结果:本组恶性肿块37例,超声诊断和疑诊恶性肿块32例,符合率为865%(32/37);良性肿块68例,超声诊断良性肿块58例,符合率为853%(58/68)。乳腺良恶性肿块在形态、 边界、 包膜、 内部回声、 后方回声、 沙粒样钙化、血流形态分布,血流动力学等方面具有明显差异。结论:二维及彩色多普勒超声对良恶性乳腺肿块有较高鉴别诊断价值。
目的 探讨胰头部肿块型慢性胰腺炎的诊断要点与个体化术式的选择原则。方法 回顾性分析2000年4月至2011年9月期间我院收治的10例胰头部肿块型慢性胰腺炎患者的临床资料。结果 本组平均发病年龄47.3岁，平均病程69.1d，平均总胆红素99.4µmol/L，CA19-9 55～78U/ml。10例B超检查示肝内胆管及胆总管扩张，5例CT检查报告胰头部占位性病变伴主胰管不规则扩张或钙化灶，2例MRCP检查诊断胆总管下段占位。3例术中多点穿刺快速活检后行胆胰管引流术，7例术前误诊为胰头癌或壶腹癌均行胰十二指肠切除，术后出现并发症8例，死亡1例，9例平均随访44.2个月无复发和癌变。结论 把握发病年龄、病程、波动性黄疸等临床特征和CA19-9水平及CT、MRCP等影像检查要点是胰头部肿块型慢性胰腺炎与胰头癌鉴别诊断的关键，用个体化术式合理实施胰十二指肠切除、胆胰管内外引流术是胰头部肿块型慢性胰腺炎外科处理明智的选择。
目的 分析眼表面肿块的发病情况及组织病理学特点。 方法 对2004年1月-2008年12月收治并经病理学证实的326例眼表面肿块患者的年龄、性别、眼别、肿块发生部位、肿块性质及病理类型进行回顾性分析。 结果 326例眼表面肿块中，良性肿块264例（81.0%），恶性肿块62例（19.0%）。良性肿块中，前5位分别为色素痣67例（25.4）%，迷芽瘤63例（23.9）%，乳头状瘤39例（占14.8）%，结膜囊肿25例（9.5）%，炎性肉芽肿20例（7.6）%。恶性肿块中，前4位分别为鳞状细胞癌25例（40.3）%，淋巴瘤13例（21.0）%，恶性黑色素瘤12例（19.4）%，原位癌10例（16.1）%。 结论 眼球表面的肿块有共同的组织细胞起源，肿块的亚型表现出不同的组织结构、良恶性和好发部位；而同部位的良性、交界性和恶性病变的衍变发展，从某种程度上体现了一个疾病的不同发展阶段，三者间的鉴别和明确的病理诊断能为临床选择手术时机及手术方式提供依据。
Objective To evaluate the sensitivity， specificity, and accuracy of magnetic resonance imaging （MRI） in characterizing adnexal masses. Methods The databases such as the Cochrane Library, PubMed， EMbase， CNKI， and WanFang Data were searched on computer from 1991 to 2011. The reviewers screened the trials according to inclusion and exclusion criteria strictly, extracted the data， and assessed the methodology quality. Meta-analysis were performed using the Metadisc 1.40 software. The acquired pooled sensitivity, specificity， and summary receiver operating characteristic curve （SROC） were used to describe the diagnostic value. The pooled likelihood ratios were calculated based on the pooled sensitivity and specificity. Results Ten case-control studies involving 649 women who were suspected to have pelvic masses were included and 729 masses were confirmed by the postoperative histopathology. The pooled statistical results of meta-analysis showed that：the sensitivity and specificity of MRI were 〔89%（84%-92%）， P=0.046 6〕 and 〔87% （83%-90%）， P=0.000 2〕 respectively, the positive and negative likelihood ratios of MRI were 6.25（P=0.008 5） and 0.14（P=0.029 1） respectively, and the area under the SROC curve （AUC） was 0.941. The sensitivity and specificity of ultrasound were 〔87%（82%-91%）， P=0.000 0〕 and 〔73%（69%-77%）, P=0.000 0〕 respectively, the positive and negative likelihood ratios of MRI were 3.07（P=0.000 0） and 0.18（P=0.000 1） respectively， and the AUC was 0.897. The speci?city and accuracy of MRI in characterizing female pelvic masses were higher than ultrasound obviously. Conclusion According these evidences， the MRI should be recommended to the women who are suspected to have pelvic masses as a preferred.