Faculty Bibliography

RATIONALE AND OBJECTIVES: This study aimed to assess the performance of a text classification machine-learning model in predicting highly cited articles within the recent radiological literature and to identify the model's most influential article features. MATERIALS AND METHODS: We downloaded from PubMed the title, abstract, and medical subject heading terms for 10,065 articles published in 25 general radiology journals in 2012 and 2013. Three machine-learning models were applied to predict the top 10% of included articles in terms of the number of citations to the article in 2014 (reflecting the 2-year time window in conventional impact factor calculations). The model having the highest area under the curve was selected to derive a list of article features (words) predicting high citation volume, which was iteratively reduced to identify the smallest possible core feature list maintaining predictive power. Overall themes were qualitatively assigned to the core features. RESULTS: The regularized logistic regression (Bayesian binary regression) model had highest performance, achieving an area under the curve of 0.814 in predicting articles in the top 10% of citation volume. We reduced the initial 14,083 features to 210 features that maintain predictivity. These features corresponded with topics relating to various imaging techniques (eg, diffusion-weighted magnetic resonance imaging, hyperpolarized magnetic resonance imaging, dual-energy computed tomography, computed tomography reconstruction algorithms, tomosynthesis, elastography, and computer-aided diagnosis), particular pathologies (prostate cancer; thyroid nodules; hepatic adenoma, hepatocellular carcinoma, non-alcoholic fatty liver disease), and other topics (radiation dose, electroporation, education, general oncology, gadolinium, statistics). CONCLUSIONS: Machine learning can be successfully applied to create specific feature-based models for predicting articles likely to achieve high influence within the radiological literature.

PURPOSE: To identify factors associated with the patient experience in radiology based on patient feedback reports from a single institution. METHODS: In a departmental patient experience committee initiative, all imaging outpatients are provided names and roles of all departmental employees with whom they interact, along with contact information for providing feedback after their appointment. All resulting feedback was recorded in a web-based database. A total of 3,675 patient comments over a 3-year period were assessed in terms of major themes. Roles of employees recognized within the patient comments were also assessed. RESULTS: Patient feedback comments most commonly related to professional staff behavior (74.5%) and wait times (11.9%), and less commonly related to a spectrum of other issues (comfort during the exam, quality of the facilities, access to information regarding the exam, patient privacy, medical records, the radiology report, billing). The most common attributes relating to staff behavior involved patients' perceptions of staff caring, professionalism, pleasantness, helpfulness, and efficiency. Employees most commonly recognized by the comments were the technologist (50.2%) and receptionist (31.6%) and much less often the radiologist (2.2%). No radiologist was in the top 10% of employees in terms of the number of comments received. CONCLUSION: Patients' comments regarding their experiences in undergoing radiologic imaging were largely influenced by staff behavior and communication (particularly relating to technologists and receptionists), as well as wait times, with radiologists having a far lesser immediate impact. Radiologists are encouraged to engage in activities that promote direct visibility to their patients and thereby combat risks of the perceived "invisible" radiologist.

RATIONALE AND OBJECTIVE: The purpose of this study was to evaluate themes related to patients' experience in undergoing mammography, as expressed on Twitter. METHODS: A total of 464 tweets from July to December 2015 containing the hashtag #mammogram and relating to a patient's experience in undergoing mammography were reviewed. RESULTS: Of the tweets, 45.5% occurred before the mammogram compared to 49.6% that occurred afterward (remainder of tweets indeterminate). However, in patients undergoing their first mammogram, 32.8% occurred before the examination, whereas in those undergoing follow-up mammogram, 53.0% occurred before the examination. Identified themes included breast compression (24.4%), advising other patients to undergo screening (23.9%), recognition of the health importance of the examination (18.8%), the act of waiting (10.1%), relief regarding results (9.7%), reflection that the examination was not that bad (9.1%), generalized apprehension regarding the examination (8.2%), interactions with staff (8.0%), the gown (5.0%), examination costs or access (3.4%), offering or reaching out for online support from other patients (3.2%), perception of screening as a sign of aging (2.4%), and the waiting room or waiting room amenities (1.3%). Of the tweets, 31.9% contained humor, of which 56.1% related to compression. Themes that were more common in patients undergoing their first, rather than follow-up, mammogram included breast compression (16.4% vs 9.1%, respectively) and that the test was not that bad (26.2% vs 7.6%, respectively). CONCLUSION: Online social media provides a platform for women to share their experiences and reactions in undergoing mammography, including humor, positive reflections, and encouragement of others to undergo the examination. Social media thus warrants further evaluation as a potential tool to help foster greater adherence to screening guidelines.

Multiparametric MRI of the prostate demonstrates strong potential to address many limitations of traditional prostate cancer diagnosis and management strategies. Recent evidence supports roles for prostate MRI in prebiopsy risk stratification, guidance of targeted biopsy and preoperative disease staging. Prostate MRI may also assist the planning and follow-up of investigational partial gland ablative therapies. This article reviews the impact of prostate MRI on such diagnostic and therapeutic paradigms in contemporary prostate cancer management.

PURPOSE: Anxiety has been called a "harm" of screening mammography. The authors provided direct, interactive education to lay audiences and measured these sessions' impact on anxiety and any increased understanding of breast cancer screening. METHODS: Academic breast radiologist provided seven 1-hour sessions of structured lectures and question-and-answer periods. Lay language and radiologic images were used to discuss disease background, screening guidelines, and areas of debate. One hundred seventeen participants (mean age, 45 +/- 15 years) completed voluntary, anonymous, institutional review board-approved pre and postsession questionnaires relaying their attitudes regarding screening and the impact of the sessions. Results are summarized descriptively. RESULTS: Mean reported anxiety regarding screening (on a scale ranging from 1-5; 1 = no anxiety) was 2.5 +/- 1.3. Anxiety was attributed to unknown results (56.4%), anticipation of pain (21.8%), known risk factors (14.5%), general uncertainty (12.7%), waiting for results (9.1%), possibility of more procedures (3.6%), and personal breast cancer history (3.6%). Ninety-seven percent reported that immediate results would lower anxiety (78% of those women indicated a 75%-100% decrease in anxiety); 93% reported that radiologist consultation with images would lower anxiety (75.6% indicated a 75%-100% decrease in anxiety). After the lecture, women reported (on a scale ranging from 1-5) increased understanding of the topic (4.7 +/- 0.6), encouragement to screen (4.6 +/- 0.7), and reduced anxiety (4.0 +/- 1.1). Ninety-seven percent to 100% provided correct responses to these questions: rationale for screening in the absence of family history, recall does not equate to cancer diagnosis, benefit of prior films, and continued importance of physical examination. CONCLUSION: Attendees of radiologist-provided direct public lectures reported decreased anxiety and improved knowledge regarding screening mammography. The resultant reduced anxiety ("harm") and educational empowerment help enable informed decision making and may promote screening attendance.

OBJECTIVES: To evaluate the cancer detection rates (CDR) for men undergoing 12 core systematic prostate biopsy with negative prebiopsy mpMRI (NegMR). MATERIALS & METHODS: Clinical data from consecutive men undergoing prostate biopsy with prebiopsy 3T mpMRI from December 2011 to August 2014 were reviewed from an IRB approved prospective database. Prebiopsy mpMRI was read by a single radiologist and men with NegMR prior to biopsy were identified for this analysis. Clinical features, CDR, and NPV rates were summarized. RESULTS: Seventy five men underwent SPB with a NegMRI during the study period. For the entire cohort, men with no prior biopsy, men with prior negative biopsy, and men enrolled in active surveillance protocols, overall CDR was 18.7%, 13.8%, 8.0% and 38.1%, respectively, and detection of Gleason sum >/= 7 (GS>/=7) cancer was 1.3%, 0%, 4.0% and 0%, respectively. The NPV for all cancers was 81.3%, 86.2%, 92.0%, and 61.9%, and for GS>/=7 cancer was 98.7%, 100%, 96.0% and 100%, respectively. CONCLUSIONS: Negative prebiopsy mpMRI confers an overall NPV of 82% on 12 core biopsy for all cancer and 98% for GS>/=7. Based upon biopsy indication, these findings assist in prebiopsy risk stratification for detection of high risk disease and may provide guidance in the decision to pursue biopsy