The breast stromal microenvironment is a pivotal factor in breast cancer development, growth and metastases. Although pathologists often detect morphologic changes in stroma by light microscopy, ...visual classification of such changes is subjective and non-quantitative, limiting its diagnostic utility. To gain insights into stromal changes associated with breast cancer, we applied automated machine learning techniques to digital images of 2387 hematoxylin and eosin stained tissue sections of benign and malignant image-guided breast biopsies performed to investigate mammographic abnormalities among 882 patients, ages 40–65 years, that were enrolled in the Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project. Using deep convolutional neural networks, we trained an algorithm to discriminate between stroma surrounding invasive cancer and stroma from benign biopsies. In test sets (928 whole-slide images from 330 patients), this algorithm could distinguish biopsies diagnosed as invasive cancer from benign biopsies solely based on the stromal characteristics (area under the receiver operator characteristics curve = 0.962). Furthermore, without being trained specifically using ductal carcinoma in situ as an outcome, the algorithm detected tumor-associated stroma in greater amounts and at larger distances from grade 3 versus grade 1 ductal carcinoma in situ. Collectively, these results suggest that algorithms based on deep convolutional neural networks that evaluate only stroma may prove useful to classify breast biopsies and aid in understanding and evaluating the biology of breast lesions.
Background:
Anterior cruciate ligament (ACL) injuries are disabling and are associated with the early onset of posttraumatic osteoarthritis. Little is known regarding the incidence rate of first-time ...noncontact ACL injuries sustained during athletic events and how they are independently influenced by level of competition, type of sport, and the participant’s sex.
Hypothesis:
Level of competition (college or high school), type of sport (soccer, basketball, lacrosse, field hockey, football, rugby, volleyball), and the athlete’s sex independently influence the incidence rate of first-time noncontact ACL injuries.
Study Design:
Cohort study; Level of evidence, 2.
Methods:
Between fall 2008 and spring 2012, first-time noncontact ACL injury data were collected from 8 colleges and 18 high schools across 7 sports. Athlete exposure was computed retrospectively using team rosters and numbers of scheduled practices and games. Injury incidence rates (IRs) were computed per 1000 athlete exposures. The independent effects of level of competition, sport, and sex on ACL injury risk were estimated by Poisson regression.
Results:
Colleges reported 48 ACL injuries with 320,719 athlete exposures across all sports studied (IR = 0.150 per 1000 person-days), while high schools reported 53 injuries with 873,057 athlete exposures (IR = 0.061). After adjustment for differences in sport and sex, college athletes had a significantly higher injury risk than did high school athletes (adjusted relative risk RR, 2.38; 95% CI, 1.55-3.54). The overall IR for female athletes was 0.112 compared with 0.063 for males. After adjustment for sport and level of play, females were more than twice as likely to have a first-time ACL injury compared with males (RR, 2.10; 95% CI, 1.34-3.27). With lacrosse as the reference group, risk of first-time noncontact ACL injury was significantly higher for soccer players (RR, 1.77) and for rugby players (RR, 2.23), independent of level of play and sex.
Conclusion:
An athlete’s risk of having a first-time noncontact ACL injury is independently influenced by level of competition, the participant’s sex, and type of sport, and there are no interactions between their effects. Female college athletes have the highest risk of having a first-time noncontact ACL injury among the groups studied.
Background:
Knee joint geometry has been associated with risk of suffering an anterior cruciate ligament (ACL) injury; however, few studies have utilized multivariate analysis to investigate how ...different aspects of knee joint geometry combine to influence ACL injury risk.
Hypotheses:
Combinations of knee geometry measurements are more highly associated with the risk of suffering a noncontact ACL injury than individual measurements, and the most predictive combinations of measurements are different for males and females.
Study Design:
Case-control study; Level of evidence, 3.
Methods:
A total of 88 first-time, noncontact, grade III ACL-injured subjects and 88 uninjured matched-control subjects were recruited, and magnetic resonance imaging data were acquired. The geometry of the tibial plateau subchondral bone, articular cartilage, and meniscus; geometry of the tibial spines; and size of the femoral intercondylar notch and ACL were measured. Multivariate conditional logistic regression was used to develop risk models for ACL injury in females and males separately.
Results:
For females, the best fitting model included width of the femoral notch at its anterior outlet and the posterior-inferior–directed slope of the lateral compartment articular cartilage surface, where a millimeter decrease in notch width and a degree increase in slope were independently associated with a 50% and 32% increase in risk of ACL injury, respectively. For males, a model that included ACL volume and the lateral compartment posterior meniscus to subchondral bone wedge angle was most highly associated with risk of ACL injury, where a 0.1 cm3 decrease in ACL volume (approximately 8% of the mean value) and a degree decrease in meniscus wedge angle were independently associated with a 43% and 23% increase in risk, correspondingly.
Conclusion:
Combinations of knee joint geometry measurements provided more information about the risk of noncontact ACL injury than individual measures, and the aspects of geometry that best explained the relationship between knee geometry and the risk of injury were different between males and females. Consequently, a female with both a decreased femoral notch width and an increased posterior-inferior–directed lateral compartment tibial articular cartilage slope combined or a male with a decreased ACL volume and decreased lateral compartment posterior meniscus angle were most at risk for sustaining an ACL injury.
Background: Anterior cruciate ligament (ACL) injuries are immediately disabling, costly, take a significant amount of time to rehabilitate, and are associated with an increased risk of developing ...posttraumatic osteoarthritis of the knee. Specific multiplanar movement patterns of the lower extremity, such as those associated with the drop vertical jump (DVJ) test, have been shown to be associated with an increased risk of suffering noncontact ACL injuries. The Landing Error Scoring System (LESS) has been developed as a tool that can be applied to identify individuals who display at-risk movement patterns during the DVJ.
Hypothesis: An increase in LESS score is associated with an increased risk of noncontact ACL injury.
Study Design: Case-control study; Level of evidence, 3.
Methods: Over a 3-year interval, 5047 high school and college participants performed preseason DVJ tests that were recorded using commercial video cameras. All participants were followed for ACL injury during their sports season, and video data from injured participants and matched controls were then assessed with the LESS. Conditional logistic regression analysis was used to examine the association between LESS score and ACL injury risk in all participants as well as subgroups of female, male, high school, and college participants.
Results: There was no relationship between the risk of suffering ACL injury and LESS score whether measured as a continuous or a categorical variable. This was the case for all participants combined (odds ratio, 1.04 per unit increase in LESS score; 95% confidence interval, 0.80-1.35) as well as within each subgroup (odds ratio range, 0.99-1.14).
Conclusion: The LESS did not predict ACL injury in our cohort of high school and college athletes.
Elevated mammographic breast density is a strong breast cancer risk factor with poorly understood etiology. Increased deposition of collagen, one of the main fibrous proteins present in breast ...stroma, has been associated with increased mammographic density. Collagen fiber architecture has been linked to poor outcomes in breast cancer. However, relationships of quantitative collagen fiber features assessed in diagnostic biopsies with mammographic density and lesion severity are not well-established.
Clinically indicated breast biopsies from 65 in situ or invasive breast cancer cases and 73 frequency matched-controls with a benign biopsy result were used to measure collagen fiber features (length, straightness, width, alignment, orientation and density (fibers/µm
)) using second harmonic generation microscopy in up to three regions of interest (ROIs) per biopsy: normal, benign breast disease, and cancer. Local and global mammographic density volumes were quantified in the ipsilateral breast in pre-biopsy full-field digital mammograms. Associations of fibrillar collagen features with mammographic density and severity of biopsy diagnosis were evaluated using generalized estimating equation models with an independent correlation structure to account for multiple ROIs within each biopsy section.
Collagen fiber density was positively associated with the proportion of stroma on the biopsy slide (p < 0.001) and with local percent mammographic density volume at both the biopsy target (p = 0.035) and within a 2 mm perilesional ring (p = 0.02), but not with global mammographic density measures. As severity of the breast biopsy diagnosis increased at the ROI level, collagen fibers tended to be less dense, shorter, straighter, thinner, and more aligned with one another (p < 0.05).
Collagen fiber density was positively associated with local, but not global, mammographic density, suggesting that collagen microarchitecture may not translate into macroscopic mammographic features. However, collagen fiber features may be markers of cancer risk and/or progression among women referred for biopsy based on abnormal breast imaging.
Abstract Background We present a fully articulated protocol for the Hamilton Rating Scale for Depression (HAM-D), including item scoring rules, rater training procedures, and a data management ...algorithm to increase accuracy of scores prior to outcome analyses. The latter involves identifying potentially inaccurate scores as interviews with discrepancies between two independent raters on the basis of either scores (> 5-point difference) or meeting threshold for depression recurrence status, a long-term treatment outcome with public health significance. Discrepancies are resolved by assigning two new raters, identifying items with disagreement per an algorithm, and reaching consensus on the most accurate scores for those items. Methods These methods were applied in a clinical trial where the primary outcome was the Structured Interview Guide for the Hamilton Rating Scale for Depression—Seasonal Affective Disorder version (SIGH-SAD), which includes the 21-item HAM-D and 8 items assessing atypical symptoms. 177 seasonally depressed adult patients were enrolled and interviewed at 10 time points across treatment and the 2-year followup interval for a total of 1,589 completed interviews with 1,535 (96.6%) archived. Results Inter-rater reliability ranged from ICCs of.923 to.967. Only 86 (5.6%) interviews met criteria for a between-rater discrepancy. HAM-D items “Depressed Mood,” “Work and Activities,” “Middle Insomnia,” and “Hypochondriasis” and Atypical items “Fatigability” and “Hypersomnia” contributed most to discrepancies. Limitations Generalizability beyond well-trained, experienced raters in a clinical trial is unknown. Conclusions Researchers might want to consider adopting this protocol in part or full. Clinicians might want to tailor it to their needs.
The lifetime risk of silicosis associated with low-level occupational exposure to respirable crystalline silica remains unclear because most previous radiographic studies included workers with ...varying exposure concentrations and durations. This study assessed the prevalence of silicosis after lengthy exposure to respirable crystalline silica at levels ≤ 0.10 mg/m
. Vermont granite workers employed any time during 1979-1987 were traced and chest radiographs were obtained for 356 who were alive in 2017 and residing in Vermont. Work history, smoking habits and respiratory symptoms were obtained by interview, and exposure was estimated using a previously developed job-exposure matrix. Associations between radiographic findings, exposure, and respiratory symptoms were assessed by ANOVA, chi-square tests and binary regression. Fourteen workers (3.9%) had radiographic evidence of silicosis, and all had been employed ≥30 years. They were more likely to have been stone cutters or carvers and their average exposure concentrations and cumulative exposures to respirable crystalline silica were significantly higher than workers with similar durations of employment and no classifiable parenchymal abnormalities. This provides direct evidence that workers with long-term exposure to low-level respirable crystalline silica (≤0.10 mg/m
) are at risk of developing silicosis.
Background: Risk prediction models for breast cancer can be improved by the addition of recently identified risk factors, including breast density and use of hormone therapy. We used prospective risk ...information to predict a diagnosis of breast cancer in a cohort of 1 million women undergoing screening mammography. Methods: There were 2 392 998 eligible screening mammograms from women without previously diagnosed breast cancer who had had a prior mammogram in the preceding 5 years. Within 1 year of the screening mammogram, 11 638 women were diagnosed with breast cancer. Separate logistic regression risk models were constructed for premenopausal and postmenopausal examinations by use of a stringent (P<.0001) criterion for the inclusion of risk factors. Risk models were constructed with 75% of the data and validated with the remaining 25%. Concordance of the predicted with the observed outcomes was assessed by a concordance (c) statistic after logistic regression model fit. All statistical tests were two-sided. Results: Statistically significant risk factors for breast cancer diagnosis among premenopausal women included age, breast density, family history of breast cancer, and a prior breast procedure. For postmenopausal women, the statistically significant factors included age, breast density, race, ethnicity, family history of breast cancer, a prior breast procedure, body mass index, natural menopause, hormone therapy, and a prior false-positive mammogram. The model may identify high-risk women better than the Gail model, although predictive accuracy was only moderate. The c statistics were 0.631 (95% confidence interval CI = 0.618 to 0.644) for premenopausal women and 0.624 (95% CI = 0.619 to 0.630) for postmenopausal women. Conclusion: Breast density is a strong additional risk factor for breast cancer, although it is unknown whether reduction in breast density would reduce risk. Our risk model may be able to identify women at high risk for breast cancer for preventive interventions or more intensive surveillance.
Seasonal patterns are often undetectable in population-based depression studies, calling into question the existence of winter seasonal affective disorder (SAD). If SAD has construct validity, ...individuals with SAD should show spontaneous depression remission in the summer. Data are sparse on prospectively assessed summer mood status in confirmed SAD patients.
We conducted prospective summer followup of community adults who, the winter before, were diagnosed with Major Depression, Recurrent with Seasonal Pattern on the Structured Clinical Interview for DSM-IV Axis I Disorders, developed a current SAD episode on the Structured Interview Guide for the Hamilton Rating Scale for Depression—Seasonal Affective Disorder Version (SIGH-SAD), and enrolled in a clinical trial comparing group cognitive-behavioral therapy for SAD and light therapy. In July/August after treatment, 143/153 (93.5 %) participants provided data on the SIGH-SAD, the Beck Depression Inventory-Second Edition, and the Longitudinal Interval Followup Evaluation (LIFE).
Summer mean depression scores were in the normal range, with the substantial majority in remission across different measures. On the LIFE, 113/143 (79.0 %) experienced complete summer remission, 19/143 (13.3 %) experienced partial summer remission, and 11/143 (7.7 %) had major depression in the summer. Depression scores were significantly lower at summer than post-treatment in both treatments, indicating incomplete treatment response.
This was a single-site study with a relatively homogeneous sample.
Supporting construct validity for SAD, the substantial majority experienced complete summer remission, with a minority in partial remission and a very small minority in episode. Both treatments left residual symptoms at treatment endpoint compared to summer.
•Construct validity for winter seasonal affective disorder (SAD) has been questioned.•Full remission at prospective summer assessment would support construct validity.•143 confirmed SAD patients were identified in winter and followed the next summer.•79 % showed complete, and 13 % showed partial, summer remission; 8 % were in episode.•Results support construct validity for SAD.
Objective:The central public health challenge for winter seasonal affective disorder (SAD) is recurrence prevention. Preliminary studies suggest better long-term outcomes following ...cognitive-behavioral therapy tailored for SAD (CBT-SAD) than light therapy. The present study is a large, randomized head-to-head comparison of these treatments on outcomes one and two winters after acute treatment.Method:Community adults with major depression, recurrent with seasonal pattern (N=177) were followed one and two winters after a randomized trial of 6 weeks of CBT-SAD (N=88) or light therapy (N=89). Prospective follow-up visits occurred in January or February of each year, and major depression status was assessed by telephone in October and December of the first year. The primary outcome was winter depression recurrence status on the Structured Interview Guide for the Hamilton Depression Rating Scale-Seasonal Affective Disorder Version (SIGH-SAD). Other outcomes were depression severity on the SIGH-SAD and the Beck Depression Inventory-Second Edition (BDI-II), remission status based on severity cutoff scores, and major depression status from tracking calls.Results:The treatments did not differ on any outcome during the first year of follow-up. At the second winter, CBT-SAD was associated with a smaller proportion of SIGH-SAD recurrences (27.3% compared with 45.6%), less severe symptoms on both measures, and a larger proportion of remissions defined as a BDI-II score ≤8 (68.3% compared with 44.5%) compared with light therapy. Nonrecurrence at the next winter was more highly associated with nonrecurrence at the second winter among CBT-SAD participants (relative risk=5.12) compared with light therapy participants (relative risk=1.92).Conclusions:CBT-SAD was superior to light therapy two winters following acute treatment, suggesting greater durability for CBT-SAD.
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