The SHED Index: a tool for assessing a Sustainable HEalthy Diet.

PURPOSE: Promoting sustainable diets through sustainable food choices is essential for achieving the sustainable development goals set by the United Nations. Establishing a practical tool that can measure and score sustainable and healthy eating is highly important. METHODS: We established a 30-item questionnaire to evaluate sustainable-dietary consumption. Based on the literature and a multidisciplinary advisory panel, the questionnaire was computed by principal component analysis, yielding the Sustainable-HEalthy-Diet (SHED) Index. A rigorous multi-stage process included validation in training-verification sets, across recycling efforts, as an indicator of environmental commitment; and validation across the proportion of animal-protein consumption, as an indicator of adherence to a sustainable and healthy dietary-pattern. The EAT-Lancet reference-diet and the Mediterranean-Diet-score were used to investigate the construct validity of the SHED Index score. Reliability was assessed with a test-retest sample. RESULTS: Three-hundred-forty-eight men and women, aged 20-45 years, completed both the SHED Index questionnaire and a validated Food-Frequency-Questionnaire. Increased dietary animal-protein intake was associated with a lower SHED Index total score (p < 0.001). Higher recycling efforts were associated with a higher total SHED Index score (p < 0.001). A linear correlation was found between the SHED Index score and food-groups of the Eat-Lancet-reference diet. A significant correlation was found between the Mediterranean-Diet-score and the SHED Index score (r = 0.575, p < 0.001). The SHED Index score revealed high reliability in test-retest, high validity in training and verification sets, and internal consistency. CONCLUSION: We developed the SHED Index score, a simple, practical tool, for measuring healthy and sustainable individual-diets. The score reflects the nutritional, environmental and sociocultural aspects of sustainable diets; and provides a tangible tool to be used in intervention studies and in daily practice.

Multi-modality CADx: ROC study of the effect on radiologists' accuracy in characterizing breast masses on mammograms and 3D ultrasound images.

RATIONALE AND OBJECTIVES: To investigate the effect of a computer-aided diagnosis (CADx) system on radiologists' performance in discriminating malignant and benign masses on mammograms and three-dimensional (3D) ultrasound (US) images. MATERIALS AND METHODS: Our dataset contained mammograms and 3D US volumes from 67 women (median age, 51; range: 27-86) with 67 biopsy-proven breast masses (32 benign and 35 malignant). A CADx system was designed to automatically delineate the mass boundaries on mammograms and the US volumes, extract features, and merge the extracted features into a multi-modality malignancy score. Ten experienced readers (subspecialty academic breast imaging radiologists) first viewed the mammograms alone, and provided likelihood of malignancy (LM) ratings and Breast Imaging and Reporting System assessments. Subsequently, the reader viewed the US images with the mammograms, and provided LM and action category ratings. Finally, the CADx score was shown and the reader had the opportunity to revise the ratings. The LM ratings were analyzed using receiver-operating characteristic (ROC) methodology, and the action category ratings were used to determine the sensitivity and specificity of cancer diagnosis. RESULTS: Without CADx, readers' average area under the ROC curve, A(z), was 0.93 (range, 0.86-0.96) for combined assessment of the mass on both the US volume and mammograms. With CADx, their average A(z) increased to 0.95 (range, 0.91-0.98), which was borderline significant (P = .05). The average sensitivity of the readers increased from 98% to 99% with CADx, while the average specificity increased from 27% to 29%. The change in sensitivity with CADx did not achieve statistical significance for the individual radiologists, and the change in specificity was statistically significant for one of the radiologists. CONCLUSIONS: A well-trained CADx system that combines features extracted from mammograms and US images may have the potential to improve radiologists' performance in distinguishing malignant from benign breast masses and making decisions about biopsies.

A controlled intervention study of changing health-providers' attitudes toward personal lifestyle habits and health-promotion skills.

OBJECTIVE: Data regarding health providers' personal lifestyle and the differential effect of a short-term personal lifestyle experience intervention program on health providers are limited. METHODS: We conducted a controlled study aimed at changing personal attitudes toward lifestyle habits among 323 health professionals: 136 (42%) physicians, 140 (43%) dietitians, and 47 (15%) nurses and health promoters. In the intervention group (n = 209) individuals participated in a 2-d intensive self-experience workshop in an isolated location emphasizing healthy lifestyle and behavior-modifying techniques. Intervention and control groups were followed for 6 mo. RESULTS: At baseline, avoidance of salt, trans-fatty acids, saturated fats, and processed meat was more frequent among dietitians (P < 0.05 versus physicians). The physicians reported a lower intake of olive/canola oil, nuts/almonds, dietary fibers, vegetables, and fruits (P < 0.05). Furthermore, physicians reported lower confidence in lifestyle primary prevention and felt less useful engaging in health-promotion activities (P < 0.05 versus other health professionals). After 6 mo, waist circumference decreased in the intervention group (-1.3 versus +1.8 cm in control group, P < 0.01). The effect was more prominent among physicians. A modest differential effect of the intervention program was shown in health-promotion activities. CONCLUSION: Approaches toward primary prevention can be improved by an intervention program focusing on personal changes of health care providers. Physicians who are less likely to personally adhere to and believe in lifestyle primary prevention are more likely to benefit from this platform.

Breaking bad news in the breast imaging setting.

RATIONALE AND OBJECTIVES: The aim of this study was to investigate the experience and desire for training breast imagers in discussing "bad news" with their patients. No such information has been previously reported. MATERIALS AND METHODS: Following University of Michigan (UM) institutional review board approval and approval from the Society of Breast Imaging (SBI), questionnaires were mailed to current UM breast imaging faculty members, fellows, and residents and to SBI fellows. The final questionnaire page was mistakenly omitted in the SBI mailing. After institutional review board approval, the final page was sent to the SBI fellows. RESULTS: The response rates were 65% (61 of 94) for SBI fellows and 65% (13 of 20) for UM physicians. Ninety-five percent of respondents were aged >or= 40 years. Sixty-two percent of UM physicians were women, compared to 52% of SBI fellows. Sixty-four percent of respondents practiced in university settings and 34% in private settings. Thirty-five percent of respondents had breast imaging fellowships. The frequency of delivering bad news was most often weekly or daily, whether the news was a need for extra views, a biopsy recommendation, or positive core biopsy results. Recommendations for extra views and breast biopsies were reported to be usually given in person, whereas 59% of respondents delivered positive biopsy results by telephone. Eighty-five percent of respondents noted no previous training in delivering bad news. On a comfort scale ranging from 1 (very uncomfortable) to 10 (very comfortable), 95% of respondents rated their comfort at 8 to 10 for recommending extra views, 85% had the same comfort level for recommending biopsies, and 67% had the same level for giving positive biopsy results. Sixty-two percent of UM radiologists expressed interest in obtaining further training in how to deliver bad news, whereas only 32% of SBI fellows were desirous of such training. CONCLUSION: Although radiologists commonly delivered bad news in the breast imaging setting, very few had training in how to do so. Comfort levels declined as the severity of news increased, yet a majority of respondents were not interested in obtaining training in how to deliver bad news. These findings raise the need for further study.

Breast masses: computer-aided diagnosis with serial mammograms.

PURPOSE: To retrospectively evaluate effects of computer-aided diagnosis (CAD) involving an interval change classifier (which uses interval change information extracted from prior and current mammograms and estimates a malignancy rating) on radiologists' accuracy in characterizing masses on two-view serial mammograms as malignant or benign. MATERIALS AND METHODS: The data collection protocol had institutional review board approval. Patient informed consent was waived for this HIPAA-compliant retrospective study. Ninety temporal pairs of two-view serial mammograms (depicting 47 malignant and 43 benign biopsy-proved masses) were obtained from 68 patient files and were digitized. Biopsy was the reference standard. Eight Mammography Quality Standards Act of 1992-accredited radiologists and two breast imaging fellows assessed digitized two-view temporal pairs (in preselected regions of interest only) by estimating likelihood of malignancy and Breast Imaging Reporting and Data System (BI-RADS) category without and with CAD. Observers' rating data were analyzed with Dorfman-Berbaum-Metz (DBM) multireader multicase method. Statistical significance of differences was estimated with the DBM method and Student two-tailed paired t test. RESULTS: Average area under the receiver operating characteristic curve for likelihood of malignancy across the 10 observers was 0.83 (range, 0.74-0.88) without CAD and improved to 0.87 (range, 0.80-0.92) with CAD (P < .05). The average partial area index above a sensitivity of 0.90 for likelihood of malignancy was 0.35 (range, 0.13-0.54) without CAD and 0.49 (range, 0.18-0.73) with CAD--a nonsignificant improvement (P = .11). For BI-RADS assessment, it was estimated that with CAD, six radiologists would correctly recommend additional biopsies for malignant masses (range, 4.3%-10.6%) and five would correctly recommend reduction of biopsy (ie, fewer biopsies) for benign masses (range, 2.3%-9.3%). However, five radiologists would incorrectly recommend additional biopsy for benign masses (range, 2.3%-14.0%), and one would incorrectly recommend reduction of biopsy (4.3%). CONCLUSION: CAD involving interval change analysis of preselected regions of interest can significantly improve radiologists' accuracy in classifying masses on digitized screen-film mammograms as malignant or benign.

Improvement in radiologists' characterization of malignant and benign breast masses on serial mammograms with computer-aided diagnosis: an ROC study.

PURPOSE: To evaluate the effects of computer-aided diagnosis (CAD) on radiologists' characterization of masses on serial mammograms. MATERIALS AND METHODS: Two hundred fifty-three temporal image pairs (138 malignant and 115 benign) obtained from 96 patients who had masses on serial mammograms were evaluated. The temporal pairs were formed by matching masses of the same view from two different examinations. Eight radiologists and two breast imaging fellows assessed the temporal pairs with and without computer aid. The classification of accuracy was quantified by using the area under receiver operating characteristic curve (A(z)). The statistical significance of the difference in A(z) between the different reading conditions was estimated with the Dorfman-Berbaum-Metz method for analysis of multireader multicase data and with the Student paired t test for analysis of observer-specific paired data. RESULTS: The average A(z) for radiologists' estimates of the likelihood of malignancy was 0.79 without CAD and improved to 0.84 with CAD. The improvement was statistically significant (P =.005). The corresponding average partial area index was 0.25 without CAD and improved to 0.37 with CAD. The improvement was also statistically significant (P =.005). On the basis of Breast Imaging Reporting and Data System assessments, it was estimated that with CAD, each radiologist, on average, reduced 0.7% (0.8 of 115) of unnecessary biopsies and correctly recommended 5.7% (7.8 of 138) of additional biopsies. CONCLUSION: CAD based on analysis of interval changes can significantly increase radiologists' accuracy in classification of masses and thereby may be useful in improving correct biopsy recommendations.

Sensitivity of noncommercial computer-aided detection system for mammographic breast cancer detection: pilot clinical trial.

PURPOSE: To evaluate a noncommercial computer-aided detection (CAD) program for breast cancer detection with screening mammography. MATERIALS AND METHODS: A CAD program was developed for mammographic breast cancer detection. The program was applied to 2,389 patients' screening mammograms at two geographically remote academic institutions (institutions A and B). Thirteen radiologists who specialized in breast imaging participated in this pilot study. For each case, the individual radiologist performed a prospective Breast Imaging Reporting and Data System (BI-RADS) assessment after viewing of the screening mammogram. Subsequently, the radiologist was shown CAD results and rendered a second BI-RADS assessment by using knowledge of both mammographic appearance and CAD results. Outcome analysis of results of examination in patients recalled for a repeat examination, of biopsy, and of 1-year follow-up examination was recorded. Correct detection with CAD included a computer-generated mark indicating a possible malignancy on craniocaudal or mediolateral oblique views or both. RESULTS: Eleven (0.46%) of 2,389 patients had mammographically detected nonpalpable breast cancers. Ten (91%) of 11 (95% CI: 74%, 100%) cancers were correctly identified with CAD. Radiologist sensitivity without CAD was 91% (10 of 11; 95% CI: 74%, 100%). In 1,077 patients, follow-up findings were documented at 1 year. Five (0.46%) patients developed cancers, which were found on subsequent screening mammograms. The area where the cancers developed in two (40%) of these five patients was marked (true-positive finding) by the computer in the preceding year. Because of CAD results, a 9.7% increase in recall rate from 14.4% (344 of 2,389) to 15.8% (378 of 2,389) occurred. Radiologists' recall rate of study patients prior to use of CAD was 31% higher than the average rate for nonstudy cases (10.3%) during the same time period at institution A. CONCLUSION: Performance of the CAD program had a very high sensitivity of 91% (95% CI: 74%, 100%).