Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps

© 2017 The Author(s). This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic

Chemotherapy-Response Monitoring of Breast Cancer Patients Using Quantitative Ultrasound-Based Intra-Tumour Heterogeneities

© 2017 The Author(s). Anti-cancer therapies including chemotherapy aim to induce tumour cell death. Cell death introduces alterations in cell morphology and tissue micro-structures that cause measurable changes in tissue echogenicity. This study investigated the effectiveness of quantitative ultrasound (QUS) parametric imaging to characterize intra-tumour heterogeneity and monitor the pathological response of breast cancer to chemotherapy in a large cohort of patients (n = 100). Results demonstrated that QUS imaging can non-invasively monitor pathological response and outcome of breast cancer patients to chemotherapy early following treatment initiation. Specifically, QUS biomarkers quantifying spatial heterogeneities in size, concentration and spacing of acoustic scatterers could predict treatment responses of patients with cross-validated accuracies of 82 ± 0.7%, 86 ± 0.7% and 85 ± 0.9% and areas under the receiver operating characteristic (ROC) curve of 0.75 ± 0.1, 0.80 ± 0.1 and 0.89 ± 0.1 at 1, 4 and 8 weeks after the start of treatment, respectively. The patients classified as responders and non-responders using QUS biomarkers demonstrated significantly different survivals, in good agreement with clinical and pathological endpoints. The results form a basis for using early predictive information on survival-linked patient response to facilitate adapting standard anti-cancer treatments on an individual patient basis

Monitoring Breast Cancer Response to Neoadjuvant Chemotherapy Using Ultrasound Strain Elastography

© 2019 The Authors Strain elastography was used to monitor response to neoadjuvant chemotherapy (NAC) in 92 patients with biopsy-proven, locally advanced breast cancer. Strain elastography data were collected before, during, and after NAC. Relative changes in tumor strain ratio (SR) were calculated over time, and responder status was classified according to tumor size changes. Statistical analyses determined the significance of changes in SR over time and between response groups. Machine learning techniques, such as a naïve Bayes classifier, were used to evaluate the performance of the SR as a marker for Miller-Payne pathological endpoints. With pathological complete response (pCR) as an endpoint, a significant difference (P < .01) in the SR was observed between response groups as early as 2 weeks into NAC. Naïve Bayes classifiers predicted pCR with a sensitivity of 84%, specificity of 85%, and area under the curve of 81% at the preoperative scan. This study demonstrates that strain elastography may be predictive of NAC response in locally advanced breast cancer as early as 2 weeks into treatment, with high sensitivity and specificity, granting it the potential to be used for active monitoring of tumor response to chemotherapy

Complete Versus Incomplete Surgical Resection in Intramedullary Astrocytoma: Systematic Review with Individual Patient Data Meta-Analysis

Study Design: Systematic review Background: Considering the infiltrative nature of intramedullary astrocytoma, the goal of surgery is to have a better patient related outcome. Objective: To compare the overall survival (OS) and neurologic outcomes of complete vs incomplete surgical resection for patients with intramedullary astrocytoma. Methods: A comprehensive search of MEDLINE, CENTRAL and EMBASE was conducted by two independent reviewers. Individual patient data (IPD) analysis and multivariate Cox Proportional Hazard Model was developed to measure the effect of surgical strategies on OS, post-operative neurological improvement (PNI), and neurological improvement in the last follow up (FNI). Results: We included 1079 patients from 35 studies. Individual patient data of 228 patients (13 articles) was incorporated into the integrative IPD analysis. Kaplan-Meier survival analysis showed complete resection (CR) significantly improved OS in comparison with the incomplete resection (IR) (log-rank test, P =.004). In the multivariate IPD analysis, three prognostic factors had significant effect on the OS: (1) Extent of Resection, (2) pathology grade, and (3) adjuvant therapy. We observed an upward trend in the popularity of chemotherapy, but CR, IR, and radiotherapy had relatively stable trends during three decades. Conclusion: Our study shows that CR can improve OS when compared to IR. Patients with spinal cord astrocytoma undergoing CR had similar PNI and FNI compared to IR. Therefore, CR should be the primary goal of surgery, but intraoperative decisions on the extent of resection should be relied on to prevent neurologic adverse events. Due to significant effect of adjuvant therapy on OS, PNI and FNI, it could be considered as the routine treatment strategy for spinal cord astrocytoma

Complete Versus Incomplete Surgical Resection in Intramedullary Ependymomas: A Systematic Review and Meta-analysis

Study Design: Systematic review. Objective: To compare outcomes of complete versus incomplete resection in primary intramedullary spinal cord ependymoma. Methods: A comprehensive search of the MEDLINE, CENTRAL, and Embase databases was conducted by 2 independent investigators. Random-effect meta-analysis and meta-regression with seven covariates were performed to evaluate the reason for the heterogeneity among studies. We also used individual patient data in the integrative analysis to compare complete and incomplete resection based on 4 outcomes: progression-free survival (PFS), overall survival (OS), postoperative neurological improvement (PNI), and follow-up neurological improvement (FNI). Results: A total of 23 studies were identified, including 407 cases. Significant heterogeneity among included studies was observed in risk estimates (I2 for PFS, FNI, and PNI were 49.5%, 78.3%, and 87.2%, respectively). The mean follow-up time across cases was 48.6 ± 2.35 months. Cox proportional multivariable analysis revealed that the complete resection can prolong PFS (model, hazard ratio = 0.18, CI 0.05-0.54, P =.004,) and improve the FNI (binary logistic regression, adjusted odds ratio = 16.5, CI 1.6-171, P =.019). However, PNI and OS were similar in patients with incomplete resected spinal cord ependymoma compared with complete resection (binary logistic regression respectively and Cox multivariable analysis, P >.5). Conclusion: The data presented in this study showed that OS was not significantly affected by the degree of surgery. However, complete resection of intramedullary ependymomas provides the optimal outcomes with longer PFS and better long-term neurological outcomes than incomplete resection

Post-discharge follow-up of patients with spine trauma in the National Spinal Cord Injury Registry of Iran during the COVID-19 pandemic:Challenges and lessons learned

PURPOSE: The purpose of the National Spinal Cord Injury Registry of Iran (NSCIR-IR) is to create an infrastructure to assess the quality of care for spine trauma and in this study, we aim to investigate whether the NSCIR-IR successfully provides necessary post-discharge follow-up data for these patients.METHODS: An observational prospective study was conducted from April 11, 2021 to April 22, 2022 in 8 centers enrolled in NSCIR-IR, respectively Arak, Rasht, Urmia, Shahroud, Yazd, Kashan, Tabriz, and Tehran. Patients were classified into three groups based on their need for care resources, respectively: (1) non-spinal cord injury (SCI) patients without surgery (group 1), (2) non-SCI patients with surgery (group 2), and (3) SCI patients (group 3). The assessment tool was a self-designed questionnaire to evaluate the care quality in 3 phases: pre-hospital, in-hospital, and post-hospital. The data from the first 2 phases were collected through the registry. The post-hospital data were collected by conducting follow-up assessments. Telephone follow-ups were conducted for groups 1 and 2 (non-SCI patients), while group 3 (SCI patients) had a face-to-face visit. This study took place during the COVID-19 pandemic. Data on age and time interval from injury to follow-up were expressed as mean ± standard deviation (SD) and response rate and follow-up loss as a percentage.RESULTS: Altogether 1538 telephone follow-up records related to 1292 patients were registered in the NSCIR-IR. Of the total calls, 918 (71.05%) were related to successful follow-ups, but 38 cases died and thus were excluded from data analysis. In the end, post-hospital data from 880 patients alive were gathered. The success rate of follow-ups by telephone for groups 1 and 2 was 73.38% and 67.05% respectively, compared to 66.67% by face-to-face visits for group 3, which was very hard during the COVID-19 pandemic. The data completion rate after discharge ranged from 48% to 100%, 22%-100% and 29%-100% for groups 1 - 3.CONCLUSIONS: To improve patient accessibility, NSCIR-IR should take measures during data gathering to increase the accuracy of registered contact information. Regarding the loss to follow-ups of SCI patients, NSCIR-IR should find strategies for remote assessment or motivate them to participate in follow-ups through, for example, providing transportation facilities or financial support.</p

Predictive quantitative ultrasound radiomic markers associated with treatment response in head and neck cancer

Aim: We aimed to identify quantitative ultrasound (QUS)-radiomic markers to predict radiotherapy response in metastatic lymph nodes of head and neck cancer. Materials & methods: Node-positive head and neck cancer patients underwent pretreatment QUS imaging of their metastatic lymph nodes. Imaging features were extracted using the QUS spectral form, and second-order texture parameters. Machine-learning classifiers were used for predictive modeling, which included a logistic regression, naive Bayes, and k-nearest neighbor classifiers. Results: There was a statistically significant difference in the pretreatment QUS-radiomic parameters between radiological complete responders versus partial responders (p < 0.05). The univariable model that demonstrated the greatest classification accuracy included: spectral intercept (SI)-contrast (area under the curve = 0.741). Multivariable models were also computed and showed that the SI-contrast + SI-homogeneity demonstrated an area under the curve = 0.870. The three-feature model demonstrated that the spectral slope-correlation + SI-contrast + SI-homogeneity-predicted response with accuracy of 87.5%. Conclusion: Multivariable QUS-radiomic features of metastatic lymph nodes can predict treatment response a priori

Quantitative ultrasound delta-radiomics during radiotherapy for monitoring treatment responses in head and neck malignancies

Aim: We investigated quantitative ultrasound (QUS) in patients with node-positive head and neck malignancies for monitoring responses to radical radiotherapy (RT). Materials & methods: QUS spectral and texture parameters were acquired from metastatic lymph nodes 24 h, 1 and 4 weeks after starting RT. K-nearest neighbor and naive-Bayes machine-learning classifiers were used to build prediction models for each time point. Response was detected after 3 months of RT, and patients were classified into complete and partial responders. Results: Single-feature naive-Bayes classification performed best with a prediction accuracy of 80, 86 and 85% at 24 h, week 1 and 4, respectively. Conclusion: QUS-radiomics can predict RT response at 3 months as early as 24 h with reasonable accuracy, which further improves into 1 week of treatment

Indicators of Quality of Care in Individuals With Traumatic Spinal Cord Injury: A Scoping Review

Study Design: Scoping review. Objectives: To identify a practical and reproducible approach to organize Quality of Care Indicators (QoCI) in individuals with traumatic spinal cord injury (TSCI). Methods: A comprehensive literature review was conducted in the Cochrane Central Register of Controlled Trials (CENTRAL) (Date: May 2018), MEDLINE (1946 to May 2018), and EMBASE (1974 to May 2018). Two independent reviewers screened 6092 records and included 262 full texts, among which 60 studies were included for qualitative analysis. We included studies, with no language restriction, containing at least 1 quality of care indicator for individuals with traumatic spinal cord injury. Each potential indicator was evaluated in an online, focused group discussion to define its categorization (healthcare system structure, medical process, and individuals with Traumatic Spinal Cord Injury related outcomes), definition, survey options, and scale. Results: A total of 87 indicators were identified from 60 studies screened using our eligibility criteria. We defined each indicator. Out of 87 indicators, 37 appraised the healthcare system structure, 30 evaluated medical processes, and 20 included individuals with TSCI related outcomes. The healthcare system structure included the impact of the cost of hospitalization and rehabilitation, as well as staff and patient perception of treatment. The medical processes included targeting physical activities for improvement of health-related outcomes and complications. Changes in motor score, functional independence, and readmission rates were reported as individuals with TSCI-related outcomes indicators. Conclusion: Indicators of quality of care in the management of individuals with TSCI are important for health policy strategists to standardize healthcare assessment, for clinicians to improve care, and for data collection efforts including registries