Impact of same day screening mammogram results on women's satisfaction and overall breast cancer screening experience: a quality improvement survey analysis.

BACKGROUND: Most women undergoing screening examinations in the U.S. do not receive immediate results and for many this results in increased stress, inconvenience, delayed diagnosis, and potential loss to follow-up. OBJECTIVE: To study the impact of same appointment mammogram results on breast cancer screening experience and patient satisfaction. MATERIALS AND METHODS: A 6-question survey with questions focused on breast cancer screening experience with our new service of same appointment mammogram results was distributed to 200 patients, with 185 patients returning their responses. Patients evaluated their current experience on receiving their screening results during the same appointment with their prior breast cancer screening experience. Patients who did not respond to their satisfaction score either before or after same appointment results were excluded from the patient cohort analyzing satisfaction score. Remaining questions were analyzed separately as additional satisfaction assessment tools. RESULTS: About 48% of the patients indicated an improvement in their screening experience with same appointment mammography results service, while 47% of the patients reported no significant difference in their experience. CONCLUSION: Although not statistically significant, same appointment mammogram results were able to make a positive impact on breast cancer screening experience among 48% of the patients. Further research elucidating barriers to screening and other ways to improve patient satisfaction will be required to increase breast cancer screening compliance.

Radiomics to predict immunotherapy-induced pneumonitis: proof of concept.

We present the first reported work that explores the potential of radiomics to predict patients who are at risk for developing immunotherapy-induced pneumonitis. Despite promising results with immunotherapies, immune-related adverse events (irAEs) are challenging. Although less common, pneumonitis is a potentially fatal irAE. Thus, early detection is critical for improving treatment outcomes; an urgent need to identify biomarkers that predict patients at risk for pneumonitis exists. Radiomics, an emerging field, is the automated extraction of high fidelity, high-dimensional imaging features from standard medical images and allows for comprehensive visualization and characterization of the tissue of interest and corresponding microenvironment. In this pilot study, we sought to determine whether radiomics has the potential to predict development of pneumonitis. We performed radiomic analyses using baseline chest computed tomography images of patients who did (N = 2) and did not (N = 30) develop immunotherapy-induced pneumonitis. We extracted 1860 radiomic features in each patient. Maximum relevance and minimum redundancy feature selection method, anomaly detection algorithm, and leave-one-out cross-validation identified radiomic features that were significantly different and predicted subsequent immunotherapy-induced pneumonitis (accuracy, 100% [p = 0.0033]). This study suggests that radiomic features can classify and predict those patients at baseline who will subsequently develop immunotherapy-induced pneumonitis, further enabling risk-stratification that will ultimately lead to better treatment outcomes.

Multi-center study finds postoperative residual non-enhancing component of glioblastoma as a new determinant of patient outcome.

INTRODUCTION: The aim of the present study is to assess whether postoperative residual non-enhancing volume (PRNV) is correlated and predictive of overall survival (OS) in glioblastoma (GBM) patients. METHODS: We retrospectively analyzed a total 134 GBM patients obtained from The University of Texas MD Anderson Cancer Center (training cohort, n = 97) and The Cancer Genome Atlas (validation cohort, n = 37). All patients had undergone postoperative magnetic resonance imaging immediately after surgery. We evaluated the survival outcomes with regard to PRNV. The role of possible prognostic factors that may affect survival after resection, including age, sex, preoperative Karnofsky performance status, postoperative nodular enhancement, surgically induced enhancement, and postoperative necrosis, was investigated using univariate and multivariate Cox proportional hazards regression analyses. Additionally, a recursive partitioning analysis (RPA) was used to identify prognostic groups. RESULTS: Our analyses revealed that a high PRNV (HR 1.051; p-corrected = 0.046) and old age (HR 1.031; p-corrected = 0.006) were independent predictors of overall survival. This trend was also observed in the validation cohort (higher PRNV: HR 1.127, p-corrected = 0.002; older age: HR 1.034, p-corrected = 0.022). RPA analysis identified two prognostic risk groups: low-risk group (PRNV < 70.2 cm3; n = 55) and high-risk group (PRNV ≥ 70.2 cm3; n = 42). GBM patients with low PRNV had a significant survival benefit (5.6 months; p = 0.0037). CONCLUSION: Our results demonstrate that high PRNV is associated with poor OS. Such results could be of great importance in a clinical setting, particularly in the postoperative management and monitoring of therapy.

Endovascular Thrombectomy of COVID-19-Related Large Vessel Occlusion: A Systematic Review and Summary of the Literature.

PURPOSE: Despite an overall reduction in the number of stroke cases presenting to hospitals during the COVID-19 pandemic, a remarkably high incidence of acute cerebrovascular disease associated with the infection has been reported. In this systematic review, we assess the neurological outcomes and complications of endovascular thrombectomy (EVT) for large vessel occlusions (LVO) in COVID-19 patients. METHODS: A literature search was performed in PubMed from December 1, 2019 through September 1st, 2020 using different combinations of suitable keywords. Ten studies reporting EVT outcomes and complications were identified. Two studies that included non-LVO pathologies and COVID-19 negative patients with the outcomes analysis were excluded. Patient demographics, comorbidities, anatomic thrombus location, neurological and angiographic outcomes were assessed. RESULTS: A total of 8 studies, in addition to our institutional case series, were ultimately included in this review. The mean age was 62.2 years, of which 67.6% were males. M1 segment involvement was the most commonly reported (53.8%) thrombus location. The mean NIHSS at presentation was 20.4 with no significant change at 24 h. Successful revascularization (TICI ≥ 2b) was achieved in 89%. Early proximal cerebral re-occlusion was reported in 6 patients (11%) and cerebral hemorrhage in 3 patients (4%). In hospital mortality was reported in 15 patients (28.8%). CONCLUSION: Despite angiographically successful EVT of LVOs in the majority of patients, this literature analysis demonstrates overall poor outcomes and high mortality in COVID-19 patients post EVT. An unusual incidence of early intracerebral proximal arterial re-occlusion was notable.

Multicenter study demonstrates radiomic features derived from magnetic resonance perfusion images identify pseudoprogression in glioblastoma.

Pseudoprogression (PsP) is a diagnostic clinical dilemma in cancer. In this study, we retrospectively analyse glioblastoma patients, and using their dynamic susceptibility contrast and dynamic contrast-enhanced perfusion MRI images we build a classifier using radiomic features obtained from both Ktrans and rCBV maps coupled with support vector machines. We achieve an accuracy of 90.82% (area under the curve (AUC) = 89.10%, sensitivity = 91.36%, 67 specificity = 88.24%, p = 0.017) in differentiating between pseudoprogression (PsP) and progressive disease (PD). The diagnostic performances of the models built using radiomic features from Ktrans and rCBV separately were equally high (Ktrans: AUC = 94%, 69 p = 0.012; rCBV: AUC = 89.8%, p = 0.004). Thus, this MR perfusion-based radiomic model demonstrates high accuracy, sensitivity and specificity in discriminating PsP from PD, thus provides a reliable alternative for noninvasive identification of PsP versus PD at the time of clinical/radiologic question. This study also illustrates the successful application of radiomic analysis as an advanced processing step on different MR perfusion maps.

Radiomic Phenotyping in Brain Cancer to Unravel Hidden Information in Medical Images.

Radiomics is a new area of research in the field of imaging with tremendous potential to unravel the hidden information in digital images. The scope of radiology has grown exponentially over the last two decades; since the advent of radiomics, many quantitative imaging features can now be extracted from medical images through high-throughput computing, and these can be converted into mineable data that can help in linking imaging phenotypes with clinical data, genomics, proteomics, and other "omics" information. In cancer, radiomic imaging analysis aims at extracting imaging features embedded in the imaging data, which can act as a guide in the disease or cancer diagnosis, staging and planning interventions for treating patients, monitor patients on therapy, predict treatment response, and determine patient outcomes.

Silent Sentence Completion Shows Superiority Localizing Wernicke's Area and Activation Patterns of Distinct Language Paradigms Correlate with Genomics: Prospective Study.

Preoperative mapping of language areas using fMRI greatly depends on the paradigms used, as different tasks harness distinct capabilities to activate speech processing areas. In this study, we compared the ability of 3 covert speech paradigms: Silent Sentence Completion (SSC), category naming (CAT) and verbal fluency (FAS), in localizing the Wernicke's area and studied the association between genomic markers and functional activation. Fifteen right-handed healthy volunteers and 35 mixed-handed patients were included. We focused on the anatomical areas of posterosuperior, middle temporal and angular gyri corresponding to Wernicke's area. Activity was deemed significant in a region of interest if P < 0.05. Association between fMRI activation and genomic mutation status was obtained. Results demonstrated SSC's superiority at localizing Wernicke's area. SSC demonstrated functional activity in 100% of cancer patients and healthy volunteers; which was significantly higher than those for FAS and CAT. Patients with 1p/19q non-co-deleted had higher extent of activation on SSC (P < 0.02). Those with IDH-1 wild-type were more likely to show no activity on CAT (P < 0.05). SSC is a robust paradigm for localizing Wernicke's area, making it an important clinical tool for function-preserving surgeries. We also found a correlation between tumor genomics and functional activation, which deserves more comprehensive study.