A Model to Predict Upstaging to Invasive Carcinoma in Patients Preoperatively Diagnosed with Low-Grade Ductal Carcinoma In Situ of the Breast

Background: We aimed to create a model of radiological and pathological criteria able to predict the upgrade rate of low-grade ductal carcinoma in situ (DCIS) to invasive carcinoma, in patients undergoing vacuum-assisted breast biopsy (VABB) and subsequent surgical excision. Methods: A total of 3100 VABBs were retrospectively reviewed, among which we reported 295 low-grade DCIS who subsequently underwent surgery. The association between patients’ features and the upgrade rate to invasive breast cancer (IBC) was evaluated by univariate and multivariate analysis. Finally, we developed a nomogram for predicting the upstage at surgery, according to the multivariate logistic regression model. Results: The overall upgrade rate to invasive carcinoma was 10.8%. At univariate analysis, the risk of upgrade was significantly lower in patients with greater age (p = 0.018), without post-biopsy residual lesion (p < 0.001), with a smaller post-biopsy residual lesion size (p < 0.001), and in the presence of low-grade DCIS only in specimens with microcalcifications (p = 0.002). According to the final multivariable model, the predicted probability of upstage at surgery was lower than 2% in 58 patients; among these 58 patients, only one (1.7%) upstage was observed, showing a good calibration of the model. Conclusions: An easy-to-use nomogram for predicting the upstage at surgery based on radiological and pathological criteria is able to identify patients with low-grade carcinoma in situ with low risk of upstaging to infiltrating carcinomas.

Nomogram for predicting postoperative cancer-specific early death in patients with epithelial ovarian cancer based on the SEER database: a large cohort study

Purpose Ovarian cancer is a common gynecological malignant tumor. Poor prognosis is strongly associated with early death, but there is no effective tool to predict this. This study aimed to construct a nomogram for predicting cancer-specific early death in patients with ovarian cancer. Methods We used data from the Surveillance, Epidemiology, and End Results database of patients with ovarian cancer registered from 1988 to 2016. Important independent prognostic factors were determined by univariate and multivariate logistic regression and LASSO Cox regression. Several risk factors were considered in constructing the nomogram. Nomogram discrimination and calibration were evaluated using C-index, internal validation, and receiver operating characteristic (ROC) curves. Results A total of 4769 patients were included. Patients were assigned to the training set (n = 3340; 70%) and validation set (n = 1429; 30%). Based on the training set, eight variables were shown to be significant factors for early death and were incorporated in the nomogram: American Joint Committee on Cancer (AJCC) stage, residual lesion size, chemotherapy, serum CA125 level, tumor size, number of lymph nodes examined, surgery of primary site, and age. The concordance indices and ROC curves showed that the nomogram had better predictive ability than the AJCC staging system and good clinical practicability. Internal validation based on validation set showed good consistency between predicted and observed values for early death. Conclusion Compared with predictions made based on AJCC stage or residual lesion size, the nomogram could provide more robust predictions for early death in patients with ovarian cancer.

Revisiting Intraoperative 2D USG with Saline–Air Mixture as Contrast for Resection of Eloquent Area Glioma in Resource-Deficient Countries

Background Advanced ultrasound, intraoperative magnetic resonance imaging (MRI), neuromonitoring, and aminolevulenic acid have improved the resection and safety of eloquent area gliomas. However, availability of these modern gadgets is a major concern in resource-deficient countries. A two-dimensional ultrasonography 2D USG is cheaper, provides real-time imaging, and is already established but underutilized instrument. Objective Here, we revisited the principles of 2D USG and used it for eloquent-area glioma surgery. Materials and Methods Fifty-eight patients with eloquent area gliomas were operated in last 2 years with the aid of 2D USG with 6-13 MHz curvilinear probe. Preoperative diagnosis was high-grade glioma in 38 and low-grade glioma (LGG) in 20 patients. Tumors were categorized as predominantly hyperechoic (27), uniformly hyperechoic (7), mixed echogenicity (21), and cystic (3). Results Intraoperatively, 2D USG could define the tumor margins in 46 cases. Of these, USG suggested gross total excision in 38 patients and subtotal in 8 patients. The findings matched with follow-up MRI in 34 patients who showed hyperechogenicity (predominant/uniform). Injecting saline with air in to the resection cavity and insinuating through adjacent brain parenchyma helped in detecting residual lesion in three cystic gliomas and in two LGG where the tumor cavity collapsed. Conclusion 2D USG is a helpful tool in eloquent area glioma surgery, especially in resource-limited countries. Visualization through adjacent parenchyma and injection of saline–air mixture in to the resection cavity helped in delineating residual lesion. Extent of resection is best monitored by 2D USG when tumor appeared hyperechoic (predominant/uniform).

Nomogram for Predicting Postoperative Cancer-specific Early Death in Patients with Epithelial Ovarian Cancer based on the SEER Database: A Large Cohort Study

Background: Ovarian cancer is a common gynecological malignant tumor. Poor prognosis is strongly associated with early death, but there is no effective tool to predict this. This study aimed to construct a nomogram for predicting cancer-specific early death in ovarian cancer patients.Methods: Our study used data from the Surveillance, Epidemiology, and End Results (SEER) database of ovarian cancer patients registered from 1988 to 2016. Important independent prognostic factors were determined by univariate and multivariate logistic regression and LASSO Cox regression. Several risk factors were considered in constructing the nomogram. Nomogram discrimination and calibration were evaluated using C-index, internal validation, and receiver operating characteristic (ROC) curves.Results: A total of 4769 patients were included. Patients were assigned to the training set (n = 3340; 70%) and validation set (n = 1429; 30%). Based on the training set, eight variables were shown to be significant factors for early death and were incorporated in the nomogram: AJCC (American Joint Committee on Cancer) stage, residual lesion size, chemotherapy, serum CA125 level, tumor size, number of lymph nodes examined, surgery of primary site, and age. The C-indices and ROC curves showed that the nomogram had better predictive ability than the AJCC staging system and good clinical practicability. Internal validation based on validation set showed good consistency between predicted and observed values for early death. Conclusions: Compared with predictions made using AJCC stage or residual lesion size, the nomogram was able to provide more robust predictions for early death in ovarian cancer patients.

Complete Removal of the Lesion as a Guidance in the Management of Patients with Breast Ductal Carcinoma In Situ

Background: Considering highly selected patients with ductal carcinoma in situ (DCIS), active surveillance is a valid alternative to surgery. Our study aimed to show the reliability of post-biopsy complete lesion removal, documented by mammogram, as additional criterion to select these patients. Methods: A total of 2173 vacuum-assisted breast biopsies (VABBs) documented as DCIS were reviewed. Surgery was performed in all cases. We retrospectively collected the reports of post-VABB complete lesion removal and the histological results of the biopsy and surgery. We calculated the rate of upgrade of DCIS identified on VABB upon excision for patients with post-biopsy complete lesion removal and for those showing residual lesion. Results: We observed 2173 cases of DCIS: 408 classified as low-grade, 1262 as intermediate-grade, and 503 as high-grade. The overall upgrading rate to invasive carcinoma was 15.2% (330/2173). The upgrade rate was 8.2% in patients showing mammographically documented complete removal of the lesion and 19% in patients without complete removal. Conclusion: The absence of mammographically documented residual lesion following VABB was found to be associated with a lower upgrading rate of DCIS to invasive carcinoma on surgical excision and should be considered when deciding the proper management DCIS diagnosis.

Active Surveillance in the Management of Ductal Carcinoma in Situ: The Radiologist’s Point of View

(1) Background: Considering highly selected patients with ductal carcinoma in situ (DCIS), active surveillance is a valid alternative to surgery. Our study is aimed at showing the reliability of post-biopsy complete lesion removal, documented by mammogram, as additional criterion to select these patients. (2) Methods: 2173 Vacuum Assisted Breast Biopsies (VABB) documented as DCIS have been reviewed. Surgery has been performed in all cases. We retrospectively collected the reports of post-VABB complete lesion removal and the histological results of the biopsy and surgery. We calculated the rate of upgrade of DCIS identified on VABB upon excision for patients with post-biopsy complete lesion removal and for those showing residual lesion. (3) Results: We observed 2173 cases of DCIS: 408 classified as low grade; 1262 as intermediate grade; 503 as high grade. The overall upgrading rate to invasive carcinoma was 15.2% (330/2173). The upgrade rate was significantly lower (8.2%) when considering patients showing mammographically documented complete removal of the lesion. (4) Conclusion: The absence of mammographically documented residual lesion following VABB is associated to a lower upgrading rate of DCIS to invasive carcinoma on surgical excision and should be considered when deciding the proper management DCIS diagnosis.

Diagnostic Value of Contrast-enhanced Digital Mammography Versus Contrast-enhanced MRI for Detecting Residual Disease after Neoadjuvant Chemotherapy for Breast Cancer

Background: Preoperative evaluation of breast cancer using contrast-enhanced digital mammography (CEDM) as a possible alternative to contrast-enhanced magnetic resonance imaging (CEMRI) has gained acceptance. Our aim is to compare the diagnostic performance of CEDM and CEMRI for chemotherapeutic response in breast cancer patients who underwent neoadjuvant chemotherapy (NAC).Methods: From November 2017 to October 2018, 30 patients with invasive carcinoma who performed both CEDM and CEMRI were included. Residual malignancy sizes after NAC were compared with histopathological results. The diagnostic performances for detecting residual cancers were compared using Lin concordance and Pearson correlation coefficients.Results: Thirty patients were included for the analysis. Mean tumor size after NAC was 1.22 cm (range: 0–7.0 cm) for CEDM and 1.13 cm (range: 0–5.1cm) for CEMRI compared with 1.89 cm (range: 0–12.0 cm) at final pathology measurement. Sensitivity for identifying residual lesion was for CEDM and CEMRI is as follows (CEDM 62.5%, 95% CI 40.6–81.2, CEMRI 66.7%, 95% CI 44.7–84.4). The positive predictive value (PPV) for residual lesion was 93.8% (95% CI 69.8–99.8) for CEDM and 88.9% (95% CI 65.3–98.6) for CEMRI. CEDM had a mean difference from pathology measurement of 0.668 cm, with a concordance coefficient of 0.202 and a Pearson correlation coefficient of 0.231 (p=0.220).Conclusions: Diagnostic value of CEDM for detecting residual tumor extent after NAC was comparable to that of CEMRI.