Clinical outcomes of radiofrequency catheter ablation guided by intracardiac echocardiography for Chinese atrial fibrillation patients: a single-center, retrospective study.

Background: Intracardiac echocardiography (ICE) is a novel technology with certain advantages in treatment of atrial fibrillation (AF), yet there is limited research on the use of ICE in radiofrequency ablation for AF treatment in China. The aim of this study was to investigate the total fluoroscopy time and dose, safety, and effectiveness of ICE guided vs. traditional fluoroscopy (non-ICE) guided radiofrequency ablation for AF in China. Methods: We conducted a single-center retrospective analysis of patients who underwent ICE or traditional fluoroscopy-guided radiofrequency ablation for AF. The primary endpoint of this study was total fluoroscopy time, and the secondary endpoints included total fluoroscopy dose, acute surgery failure, transseptal puncture time, ablation time, total procedure time, and 6-month surgery success (no AF recurrence or atrial flutter). As an exploratory analysis, outcomes of interest by different types of AF were examined. Results: A total of 97 patients were included in the analysis. Forty-eight were in the ICE group and 49 were in the non-ICE group with comparable demographic and clinical characteristics at the baseline. None of patients experienced acute surgery failure with no major procedure-related complications occurred. The fluoroscopic time and dose were significantly lower in the ICE group compared to the non-ICE group (0.00 vs. 9.67±4.88 min, P<0.001; 0.00 vs. 77.10±44.28 mGy/cm2, P<0.001, respectively). There were no statistically significant differences in transseptal puncture time, ablation time and total procedure time between the two groups. There were two AF recurrences observed during the 6-month follow-up in each group (P>0.99). Conclusions: ICE significantly reduced the fluoroscopic time and dose for radiofrequency catheter ablation in AF patients. There were no significant differences in safety or effectiveness outcomes between the ICE and non-ICE groups.

Cadmium ions mediated turn-on electrogenerated chemiluminescence of ZnS nanoparticles for highly selective cadmium detection in seafood.

Cd2+ is one of the most toxic heavy metal ions that can be easily accumulated in human body via food chain. Thus, the onsite detection of Cd2+ in food is very important. However, present methods for Cd2+ detection either require the use of large equipment, or suffer from the severe interference from other analogical metal ions. This work establishes a facile Cd2+ mediated turn-on ECL method for highly selective detection of Cd2+ via cation exchanging with the nontoxic ZnS nanoparticles, owing to the unique surface-state ECL properties of CdS nanomaterials. The linear range of the calibration curve is from 7.0 × 10-8 to 1.0 × 10-6 M, while other analogical metal ions do not interfere, facilitating the selective detection of Cd2+ in oyster samples. The result agrees well with that obtained using atomic emission spectroscopy, indicating the potential for wider application of this approach.

Delayed papillary muscle rupture after radiofrequency catheter ablation: A case report.

BACKGROUND: With an increased number of surgical procedures involving the mitral annular region, the risk of mitral valve prolapse (MVP) has also increased. Previous studies have reported that worsening of MVP occurred early after radiofrequency catheter ablation (RFCA) at papillary muscles in ventricular tachycardia (VT) patients with preoperative MVP. CASE SUMMARY: We report a case where MVP and papillary muscle rupture occurred 2 wk after RFCA in a papillary muscle originated VT patient without mitral valve regurgitation or prolapse before. The patient then underwent mitral valve replacement with no premature ventricular contraction or VT. During the surgery, a papillary muscle rupture was identified. Pathological examination showed necrosis of the papillary muscle. The patient recovered after mitral valve replacement. CONCLUSION: Too many ablation procedures and energy should be avoided.

Revision of Pancreatic Neck Margins Based on Intraoperative Frozen Section Analysis Is Associated With Improved Survival in Patients Undergoing Pancreatectomy for Ductal Adenocarcinoma.

OBJECTIVE: To test the hypothesis that complete, tumor-free resection at the pancreatic neck, achieved either en-bloc or non-en-bloc (ie, revision based on intraoperative frozen section [FS] analysis), is associated with improved survival as compared with incomplete resection (IR) in pancreatic ductal adenocarcinoma. SUMMARY BACKGROUND DATA: Given the likely systemic nature of pancreatic ductal adenocarcinoma, the oncologic benefit of achieving a histologically complete local resection, particularly through revision of a positive intraoperative FS at the pancreatic neck, remains controversial. METHODS: Clinicopathologic and treatment data were reviewed for 986 consecutive patients with ductal adenocarcinoma at the head, neck, or uncinate process of the pancreas who underwent open pancreatectomy as well as intraoperative FS analysis between 1998 and 2012 at Massachusetts General Hospital and between 1998 and 2013 at the University of Verona. Overall survival (OS) and perioperative morbidity and mortality were compared across 3 groups: complete resection achieved en-bloc (CR-EB), complete resection achieved non-en-bloc (CR-NEB), and IR. RESULTS: The CR-EB cohort comprised 749 (76%) patients, CR-NEB 159 patients (16%), and IR 78 patients (8%). Other than a higher incidence of vascular resection among CR-NEB and IR patients, no demographic, pathologic (eg, tumor grade, lymph node positivity, superior mesenteric artery involvement), or treatment factors (eg, neoadjuvant and adjuvant therapy use) differed between the groups. Median OS was significantly higher in patients with CR-EB (28 mo, P = 0.01) and CR-NEB resections (24 mo, P = 0.02) as compared with patients with IR resections (19 mo). After adjusting for clinicopathologic and treatment characteristics, CR-EB and CR-NEB margin status were found to be independent predictors of improved OS (relative to IR, CR-EB hazard ratio [HR] 0.65, 95% confidence interval [CI] 0.49-0.86; CR-NEB HR 0.69, 95% CI 0.50-0.96). There were no intergroup differences in perioperative morbidity and mortality, including rates of pancreatic fistula. CONCLUSIONS: For patients with ductal adenocarcinoma at the head, neck, or uncinate process of the pancreas undergoing pancreatectomy, complete tumor extirpation via either en-bloc or non-en-bloc complete resection based on FS analysis is associated with improved OS, without an associated increased perioperative morbidity or mortality.

What is Elective Oncologic Surgery in the Time of COVID-19? A Literature Review of the Impact of Surgical Delays on Outcomes in Patients with Cancer.

BACKGROUND: The impact of the COVID-19 pandemic has spread beyond those infected with SARS-CoV-2. Its widespread consequences have affected cancer patients whose surgeries may be delayed in order to minimize exposure and conserve resources. METHODS: Experts in each surgical oncology subspecialty were selected to perform a review of the relevant literature. Articles were obtained through PubMed searches in each cancer subtype using the following terms: delay to surgery, time to surgery, outcomes, and survival. RESULTS: Delays in surgery > 4 weeks in breast cancer, ductal carcinoma in situ, T1 pancreatic cancer, ovarian cancer, and pediatric osteosarcoma, negatively impacted survival. Studies on hepatocellular cancer, colon cancer, and melanoma (Stage I) demonstrated reduced survival with delays > 3 months. CONCLUSION: Studies have shown that short-term surgical delays can result in negative impacts on patient outcomes in multiple cancer types as well as in situ carcinoma. Conversely, other cancers such as gastric cancer, advanced melanoma and pancreatic cancer, well-differentiated thyroid cancer, and several genitourinary cancers demonstrated no significant outcome differences with surgical delays.

Practice patterns and work environments that influence gender inequality among academic surgeons.

BACKGROUND: Practice pattern and work environment differences may impact career advancement opportunities and contribute to the gender gap within highly competitive surgical specialties. METHODS: Using a 2000-2015 New York statewide dataset, we compared board-certified pediatric surgeons by specialist case volume and Herfindahl-Hirschman Index (HHI), which quantifies surgeon focus within specialist case mix. RESULTS: 51 pediatric surgeons were analyzed for 461 surgeon-years. Female surgeons had lower case volume (159 cases/year versus 214, p < 0.01), lower shares of specialist cases (14.1% versus 16.7%, p = 0.04), and less focused practices (HHI 0.16 versus 0.20, p = 0.03). Female surgeons' networks had fewer colleagues (7.2 versus 12.1, p < 0.01), and lower annual total (388 versus 726, p < 0.01) and specialist case volume (83 versus 159, p < 0.01), even after accounting for career length. However, female surgeons performed more cases within their networks (49% versus 36%, p = 0.04) and worked at major teaching hospitals as often as men (76% versus 76%, p = 0.97). CONCLUSION: The challenges that female surgeons face may be reflective of organizational inequities that necessitate intentional scrutiny and change.

Trends in Unilateral and Contralateral Prophylactic Mastectomy Use in Ductal Carcinoma In Situ of the Breast: Patterns and Predictors.

BACKGROUND: Increased use of contralateral prophylactic mastectomy (CPM) as treatment for ductal carcinoma in situ (DCIS) in the US was first noted in the early 2000s. Optimization of treatment guidelines for DCIS requires an understanding of current surgical treatment trends, particularly as they may differ by patient sociodemographic and community resource factors. OBJECTIVE: The aim of this study was to evaluate surgical treatment trends among US women with DCIS and to assess the impact of sociodemographic and community resource factors on surgical treatment choice. METHODS: The Surveillance, Epidemiology, and End Results dataset was queried for women aged 40 years and older who were diagnosed with unilateral DCIS between 2000 and 2014. Annual mastectomy rates were compared over time by age and race/ethnicity. Multivariable logistic regressions were performed to identify predictors of mastectomy use, with patient sociodemographics, tumor characteristics, and community resource factors (i.e. plastic surgeon density) as covariates. RESULTS: A total of 130,731 women with DCIS met the inclusion criteria. Overall mastectomy rates remained relatively unchanged over the study period (25-30%). CPM use increased for all age and race/ethnic groups, with the greatest increase exhibited by women aged 40-49 years [relative to 2000; 2014 odds ratio (OR) 10.6]. With respect to community resource factors, CPM use, as opposed to unilateral mastectomy, was associated with counties of higher education level (OR 1.52), higher income level (OR 1.22), and lower plastic surgeon density (OR 1.26). CONCLUSION AND RELEVANCE: While the popularity of mastectomy in the management of DCIS has remained relatively unchanged since the turn of the century, the use of CPM has risen substantially. Younger women with DCIS have seen the greatest increase in CPM use, a choice that remains influenced by race/ethnicity as well as income, education, and health resource availability. Until clinical risk stratifiers of DCIS are identified, the surgical decision-making paradigm must be improved so that treatment choice remains sensitive to cultural differences but becomes independent of income, education, and health resource availability.

Twenty-Five Year Trends in the Incidence of Ductal Carcinoma in Situ in US Women.

BACKGROUND: The rising incidence of ductal carcinoma in situ (DCIS) since the widespread enactment of mammography screening has been well documented. Patterns in DCIS incidence among women of various ages and across different racial and ethnic groups have not been well described. STUDY DESIGN: The Surveillance, Epidemiology, and End Results public-use data set was queried for all women aged 40 years and older diagnosed with DCIS between 1990 and 2014. Annual age-adjusted incidence rates were compared among white, black, Hispanic, and Asian-Pacific Islander women. Additionally, using mammography screening data obtained from the CDC, patterns in mammography screening over time and as they relate to DCIS incidence rates by race and ethnicity were evaluated. RESULTS: We identified 200,400 women aged 40 years or older with DCIS. Between 1998 and 2014, a period that saw flux in national breast screening guidelines, DCIS incidence rates increased in blacks, Hispanics, and Asian-Pacific Islanders, but remained relatively unchanged in whites (increase in number of DCIS diagnoses per 100,000 individuals in the population per year among blacks +0.66/p < 0.01, Hispanics +3.0/p < 0.01, Asian-Pacific Islanders +0.53/p < 0.01, and whites +0.07/p = 0.21). After accounting for age, year of diagnosis, and mammography screening rates, DCIS incidence was found to be similar between white and black women (0.8 fewer diagnoses per 100,000 individuals compared with whites; p = 0.36) but lower for Hispanic women (9.7 fewer diagnoses per 100,000 individuals compared with whites; p < 0.01). CONCLUSIONS: The DCIS incidence rates are influenced substantially by breast cancer mammography screening patterns. However, differences exist by race and ethnicity and are not fully explained by screening mammography trends alone. Consideration should be given to including race and ethnicity in determining optimal breast screening guidelines.

Use of Patient-Reported Outcome Measures in Quality Oncology Practice Initiative-Registered Practices: Results of a National Survey.

PURPOSE: Measuring patient-reported outcomes (PROs) in clinical practice has been associated with improved survival and quality of life for patients with cancer. However, this application of PROs is relatively new, and little is known about how practices collect PROs, which PROs are measured, and what challenges are met in implementation. METHODS: We surveyed Quality Oncology Practice Initiative-registered practices in December 2015 to understand the current state of PROs use and identify areas where implementation support may be needed. PRO collectors were asked to describe their views, practices, and challenges with implementation; noncollectors were asked about their interest in and perceived barriers to collection. RESULTS: Eighty-nine practices (38% of those that viewed the participation request) completed ≥ 50% of the survey and comprised the analytic sample. Most (79%) responders noted that collecting PROs was a high priority; slightly fewer actually collected PROs (69%). Most collectors (79%) were affiliated with hospitals or medical centers, and nearly all (94%) had electronic health records (EHRs). Collectors saw more patients per week than noncollectors ( P < .01). The PROs used by collectors addressed several topics, including patient distress (78%), symptoms (76%), and experience or satisfaction (70%). Perceived implementation challenges were similar for collectors and noncollectors: patient unwillingness to complete questionnaires and insufficient staff support; noncollectors additionally cited lack of PRO integration in the electronic health records. CONCLUSION: Widespread agreement that PRO collection is important has led to early adoption among a sizable minority of Quality Oncology Practice Initiative practices. Reaching consensus regarding which PROs are meaningful and developing and sharing best-practices that overcome implementation barriers could facilitate implementation and maximize PRO utility.

Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging.

Purpose: Isocitrate dehydrogenase (IDH) mutations in glioma patients confer longer survival and may guide treatment decision making. We aimed to predict the IDH status of gliomas from MR imaging by applying a residual convolutional neural network to preoperative radiographic data.Experimental Design: Preoperative imaging was acquired for 201 patients from the Hospital of University of Pennsylvania (HUP), 157 patients from Brigham and Women's Hospital (BWH), and 138 patients from The Cancer Imaging Archive (TCIA) and divided into training, validation, and testing sets. We trained a residual convolutional neural network for each MR sequence (FLAIR, T2, T1 precontrast, and T1 postcontrast) and built a predictive model from the outputs. To increase the size of the training set and prevent overfitting, we augmented the training set images by introducing random rotations, translations, flips, shearing, and zooming.Results: With our neural network model, we achieved IDH prediction accuracies of 82.8% (AUC = 0.90), 83.0% (AUC = 0.93), and 85.7% (AUC = 0.94) within training, validation, and testing sets, respectively. When age at diagnosis was incorporated into the model, the training, validation, and testing accuracies increased to 87.3% (AUC = 0.93), 87.6% (AUC = 0.95), and 89.1% (AUC = 0.95), respectively.Conclusions: We developed a deep learning technique to noninvasively predict IDH genotype in grade II-IV glioma using conventional MR imaging using a multi-institutional data set. Clin Cancer Res; 24(5); 1073-81. ©2017 AACR.

Multimodal MRI features predict isocitrate dehydrogenase genotype in high-grade gliomas.

BACKGROUND: High-grade gliomas with mutations in the isocitrate dehydrogenase (IDH) gene family confer longer overall survival relative to their IDH-wild-type counterparts. Accurate determination of the IDH genotype preoperatively may have both prognostic and diagnostic value. The current study used a machine-learning algorithm to generate a model predictive of IDH genotype in high-grade gliomas based on clinical variables and multimodal features extracted from conventional MRI. METHODS: Preoperative MRIs were obtained for 120 patients with primary grades III (n = 35) and IV (n = 85) glioma in this retrospective study. IDH genotype was confirmed for grade III (32/35, 91%) and IV (22/85, 26%) tumors by immunohistochemistry, spectrometry-based mutation genotyping (OncoMap), or multiplex exome sequencing (OncoPanel). IDH1 and IDH2 mutations were mutually exclusive, and all mutated tumors were collapsed into one IDH-mutated cohort. Cases were randomly assigned to either the training (n = 90) or validation cohort (n = 30). A total of 2970 imaging features were extracted from pre- and postcontrast T1-weighted, T2-weighted, and apparent diffusion coefficient map. Using a random forest algorithm, nonredundant features were integrated with clinical data to generate a model predictive of IDH genotype. RESULTS: Our model achieved accuracies of 86% (area under the curve [AUC] = 0.8830) in the training cohort and 89% (AUC = 0.9231) in the validation cohort. Features with the highest predictive value included patient age as well as parametric intensity, texture, and shape features. CONCLUSION: Using a machine-learning algorithm, we achieved accurate prediction of IDH genotype in high-grade gliomas with preoperative clinical and MRI features.

Physician Recommendations Trump Patient Preferences in Prostate Cancer Treatment Decisions.

OBJECTIVE: To assess the influence of patient preferences and urologist recommendations in treatment decisions for clinically localized prostate cancer. METHODS: We enrolled 257 men with clinically localized prostate cancer (prostate-specific antigen <20; Gleason score 6 or 7) seen by urologists (primarily residents and fellows) in 4 Veterans Affairs medical centers. We measured patients' baseline preferences prior to their urology appointments, including initial treatment preference, cancer-related anxiety, and interest in sex. In longitudinal follow-up, we determined which treatment patients received. We used hierarchical logistic regression to determine the factors that predicted treatment received (active treatment v. active surveillance) and urologist recommendations. We also conducted a directed content analysis of recorded clinical encounters to determine if urologists discussed patients' interest in sex. RESULTS: Patients' initial treatment preferences did not predict receipt of active treatment versus surveillance, Δχ2(4) = 3.67, P = 0.45. Instead, receipt of active treatment was predicted primarily by urologists' recommendations, Δχ2(2) = 32.81, P < 0.001. Urologists' recommendations, in turn, were influenced heavily by medical factors (age and Gleason score) but were unrelated to patient preferences, Δχ2(6) = 0, P = 1. Urologists rarely discussed patients' interest in sex (<15% of appointments). CONCLUSIONS: Patients' treatment decisions were based largely on urologists' recommendations, which, in turn, were based on medical factors (age and Gleason score) and not on patients' personal views of the relative pros and cons of treatment alternatives.

Multimodal imaging patterns predict survival in recurrent glioblastoma patients treated with bevacizumab.

BACKGROUND: Bevacizumab is a humanized antibody against vascular endothelial growth factor approved for treatment of recurrent glioblastoma. There is a need to discover imaging biomarkers that can aid in the selection of patients who will likely derive the most survival benefit from bevacizumab. METHODS: The aim of the study was to examine if pre- and posttherapy multimodal MRI features could predict progression-free survival and overall survival (OS) for patients with recurrent glioblastoma treated with bevacizumab. The patient population included 84 patients in a training cohort and 42 patients in a testing cohort, separated based on pretherapy imaging date. Tumor volumes of interest were segmented from contrast-enhanced T1-weighted and fluid attenuated inversion recovery images and were used to derive volumetric, shape, texture, parametric, and histogram features. A total of 2293 pretherapy and 9811 posttherapy features were used to generate the model. RESULTS: Using standard radiographic assessment criteria, the hazard ratio for predicting OS was 3.38 (P < .001). The hazard ratios for pre- and posttherapy features predicting OS were 5.10 (P < .001) and 3.64 (P < .005) for the training and testing cohorts, respectively. CONCLUSION: With the use of machine learning techniques to analyze imaging features derived from pre- and posttherapy multimodal MRI, we were able to develop a predictive model for patient OS that could potentially assist clinical decision making.