Lifespan reference curves for harmonizing multi-site regional brain white matter metrics from diffusion MRI

Age-related white matter (WM) microstructure maturation and decline occur throughout the human lifespan, complementing the process of gray matter development and degeneration. Here, we create normative lifespan reference curves for global and regional WM microstructure by harmonizing diffusion MRI (dMRI)-derived data from ten public datasets (N = 40,898 subjects; age: 3-95 years; 47.6% male). We tested three harmonization methods on regional diffusion tensor imaging (DTI) based fractional anisotropy (FA), a metric of WM microstructure, extracted using the ENIGMA-DTI pipeline. ComBat-GAM harmonization provided multi-study trajectories most consistent with known WM maturation peaks. Lifespan FA reference curves were validated with test-retest data and used to assess the effect of the ApoE4 risk factor for dementia in WM across the lifespan. We found significant associations between ApoE4 and FA in WM regions associated with neurodegenerative disease even in healthy individuals across the lifespan, with regional age-by-genotype interactions. Our lifespan reference curves and tools to harmonize new dMRI data to the curves are publicly available as eHarmonize (https://github.com/ahzhu/eharmonize).

A Comprehensive Corpus Callosum Segmentation Tool for Detecting Callosal Abnormalities and Genetic Associations from Multi Contrast MRIs

Structural alterations of the midsagittal corpus callosum (midCC) have been associated with a wide range of brain disorders. The midCC is visible on most MRI contrasts and in many acquisitions with a limited field-of-view. Here, we present an automated tool for segmenting and assessing the shape of the midCC from T1w, T2w, and FLAIR images. We train a UNet on images from multiple public datasets to obtain midCC segmentations. A quality control algorithm is also built-in, trained on the midCC shape features. We calculate intraclass correlations (ICC) and average Dice scores in a test-retest dataset to assess segmentation reliability. We test our segmentation on poor quality and partial brain scans. We highlight the biological significance of our extracted features using data from over 40,000 individuals from the UK Biobank; we classify clinically defined shape abnormalities and perform genetic analyses.

A Comprehensive Corpus Callosum Segmentation Tool for Detecting Callosal Abnormalities and Genetic Associations from Multi Contrast MRIs

Structural alterations of the midsagittal corpus callosum (midCC) have been associated with a wide range of brain disorders. The midCC is visible on most MRI contrasts and in many acquisitions with a limited field-of-view. Here, we present an automated tool for segmenting and assessing the shape of the midCC from T1w, T2w, and FLAIR images. We train a UNet on images from multiple public datasets to obtain midCC segmentations. A quality control algorithm is also built-in, trained on the midCC shape features. We calculate intraclass correlations (ICC) and average Dice scores in a test-retest dataset to assess segmentation reliability. We test our segmentation on poor quality and partial brain scans. We highlight the biological significance of our extracted features using data from over 40,000 individuals from the UK Biobank; we classify clinically defined shape abnormalities and perform genetic analyses.

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

BACKGROUND

Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications.

METHODS

We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC).

FINDINGS

In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683-0·717]).

INTERPRETATION

In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required.

FUNDING

British Journal of Surgery Society.

A national house-staff audit of medical prophylaxis in medical patients for the PREVENTion of Venous ThromboEmbolism (PREVENT-VTE)

We established a national audit to assess the thromboprophylaxis rate for venous thromoembolism (VTE) in at risk medical patients in acute hospitals in the Republic of Ireland and to determine whether the use of stickers to alert physicians regarding thromboprophylaxis would double the rate prophylaxis in a follow-up audit. 651 acute medical admission patients in the first audit and 524 in the second re-audit were recruited. The mean age was 66.5 yrs with similar numbers of male and female patients and 265 (22.6%) patients were active smokers. The first and second audits identified 549 (84%) and 487 (93%) of patients at-risk for VTE respectively. Of the at-risk patients, 163 (29.7%) and 132 (27.1%) received LMWH in the first and second audit respectively. Mechanical thromboprophylaxis was instigated in 75 (13.6%) patients in the first and 86 (17.7%) patients in the second audit. The placement of stickers in patient charts didn't produce a significant increase in the number of at risk patients treated in the second audit. There is unacceptably low adherence to the ACCP guidelines in Ireland and more complex intervention than chart reminders are required to improve compliance.

MRI Detection of Otherwise Occult Malignancies in Women Recently Diagnosed with Breast Cancer

Objective. Breast Magnetic Resonance Imaging (MRI) is recommended as a screening test for women at high risk for breast cancer but its role as a diagnostic tool for women recently diagnosed with breast cancer is not universally accepted. We report outcomes in a center that routinely uses breast MRI to evaluate extent of disease in patients recently diagnosed with breast cancer.Material and Methods. Between 1/1/2003 and 4/30/2007, 592 patients with recently diagnosed breast cancer underwent bilateral breast MRI to assess extent of disease. All had undergone mammography prior to breast MRI. Twenty-two were excluded because they were either lost to follow up (n=7) or had a mastectomy or lumpectomy (n=15) where correlation of pathology to the study lesion was not possible or incomplete. 570 patients comprised the analysis set. Patient age, index tumor characteristics (histologic subtype, grade, ER/PR status, HER2 status and presence of angiolymphatic invasion), axillary lymph node status, and pathologic stage were recorded in addition to mammographic breast density. All MR exams were coded following the American College of Radiology Breast Imaging-Reporting and Data System (BI-RADS) breast MRI lexicon. Biopsy rates, positive predictive values of biopsy, and overall yield of detecting an occult cancer in the ipsilateral or contralateral breast were calculated and compared using Chi-square test across patient age, mammographic breast density, index tumor type, receptor status and presence or absence of lymph node metastases.Results. The distribution of tumor histologies was typical of that seen in the U.S. during the study period, with 61% having invasive ductal index cancers, 21% pure ductal carcinoma in situ, 19% invasive lobular or other invasive cancers and 67% being node negative at time of diagnosis. Additional biopsy was recommended for 152/570 (27%) patients found to have one or more suspicious lesions on MRI distinct from the index cancer, based upon mammographic, sonographic, or clinical exam measurements. Of the 152 women who underwent biopsy, 67 women had additional cancers diagnosed, for a positive predictive value of 44% (67/152). Overall, 12% (67/570) of women had otherwise occult cancers diagnosed by MRI alone: 8% of women had additional sites or greater extent of ipsilateral disease and 4% of women had unsuspected contralateral cancer detected by MRI alone. No significant differences were found in the probability of detecting an occult cancer based on patient age, breast density, index tumor characteristics, or lymph node status.Conclusion. The 12% added cancer yield of MRI in detecting additional ipsilateral or contralateral malignancies in a clinical population of women recently diagnosed with breast cancer is significantly higher than the added cancer yield of MRI screening among women at high risk for breast cancer. The positive predictive value of MRI in this clinical setting is also high, with 44% of women who undergo additional tissue sampling being diagnosed with otherwise occult cancer. The probability of finding additional malignancy does not vary significantly with patient age, breast density, or index cancer characteristics.

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 4017.

The Influence of Older Age on Physician and Patient Decision-Making Regarding Enrollment to Breast Cancer Clinical Trials

Background: More than 50% of breast cancers occur in women ≥65 years. Clear guidelines for treatment do not exist for this population, however, due to underrepresentation of older patients on clinical trials. We reported that patients 65 and older are significantly underrepresented in Southwest Oncology Group (SWOG) trials, particularly in breast cancer. (Hutchins, 1999) We conducted a prospective study (S0316) to determine physician- and patient-perceived barriers to breast cancer clinical trial enrollment in older versus younger patients.Methods: Eight geographically diverse SWOG institutions, 5 academic and 3 community, participated in S0316. Breast cancer patients were registered at time of systemic treatment decision-making. The study prospectively assessed reasons behind patients' and physicians' decisions to either enroll in or decline clinical treatment trials, including demographics, return rates to the institution, trial availability, and eligibility. Patient questionnaires elicited concerns about treatment toxicities, confidence in medical staff or institution, opposition or support by family/friends, and financial or time commitment concerns. Physician questionnaires elicited factors influencing decisions either not to discuss a trial or not to enroll the patient, including treatment toxicities, patient age or medical status, demands on personal or staff time, and reimbursement issues. Results were compared between patients <65 vs. ≥65 years.Results: 1,079 patients were registered and eligible, and 909 (84%) returned for follow-up. Clinical trial participation was 16%. The major reason for non-accrual was either trial unavailability or ineligibility (60%). Older patients were less likely to be eligible for trials (65% vs. 78%, p=.004). If eligible, trial participation rates did not differ significantly by age (34% vs. 40%, p=.32). Treatment-specific issues were the most common reasons cited by all patients for non-participation. Patients ≥65 more often were concerned about side effects (p=.02), had friends opposed to participation (p=.001), or believed that participation would not benefit other generations (p=.009). Concerns about transportation, time commitment, or posing a burden to family were similar between age groups. Physicians discussed trial participation when trials were available and patients were eligible with 76% <65 years versus 58% ≥65 years (p=.008). The study regimen and toxicity were the most common reasons influencing physician decisions not to discuss a trial, but did not differ between age groups. For patients ≥65 years, 14% of physicians indicated age as a reason the patient did not participate vs. 3% for patients <65 years (p=.002).Conclusions: Trial unavailability or patient ineligibility are major reasons for lack of enrollment on breast cancer clinical trials for patients of all ages in this prospective study. Older patients were less likely to be eligible for trials, but if eligible participated at similar rates to younger patients. Older age should not deter physicians in recommending clinical trials. Addressing stringent eligibility criteria may improve accrual rates of older patients.Supported by the Breast Cancer Research Foundation and the SWOG Hope Foundation

Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 3077.