Topologic Parametric Response Mapping Identifies Tissue Subtypes Associated with Emphysema Progression

RATIONALE AND OBJECTIVES

Small airways disease (SAD) and emphysema are significant components of chronic obstructive pulmonary disease (COPD), a heterogenous disease where predicting progression is difficult. SAD, a principal cause of airflow obstruction in mild COPD, has been identified as a precursor to emphysema. Parametric Response Mapping (PRM) of chest computed tomography (CT) can help distinguish SAD from emphysema. Specifically, topologic PRM can define local patterns of both diseases to characterize how and in whom COPD progresses. We aimed to determine if distribution of CT-based PRM of functional SAD (fSAD) is associated with emphysema progression.

MATERIALS AND METHODS

We analyzed paired inspiratory-expiratory chest CT scans at baseline and 5-year follow up in 1495 COPDGene subjects using topological analyses of PRM classifications. By spatially aligning temporal scans, we mapped local emphysema at year five to baseline lobar PRM-derived topological readouts. K-means clustering was applied to all observations. Subjects were subtyped based on predominant PRM cluster assignments and assessed using non-parametric statistical tests to determine differences in PRM values, pulmonary function metrics, and clinical measures.

RESULTS

We identified distinct lobar imaging patterns and classified subjects into three radiologic subtypes: emphysema-dominant (ED), fSAD-dominant (FD), and fSAD-transition (FT: transition from healthy lung to fSAD). Relative to year five emphysema, FT showed rapid local emphysema progression (-57.5% ± 1.1) compared to FD (-49.9% ± 0.5) and ED (-33.1% ± 0.4). FT consisted primarily of at-risk subjects (roughly 60%) with normal spirometry.

CONCLUSION

The FT subtype of COPD may allow earlier identification of individuals without spirometrically-defined COPD at-risk for developing emphysema.

Computed tomography-based machine learning for donor lung screening before transplantation

BACKGROUND

Assessment and selection of donor lungs remain largely subjective and experience based. Criteria to accept or decline lungs are poorly standardized and are not compliant with the current donor pool. Using ex vivo computed tomography (CT) images, we investigated the use of a CT-based machine learning algorithm for screening donor lungs before transplantation.

METHODS

Clinical measures and ex situ CT scans were collected from 100 cases as part of a prospective clinical trial. Following procurement, donor lungs were inflated, placed on ice according to routine clinical practice, and imaged using a clinical CT scanner before transplantation while stored in the icebox. We trained and tested a supervised machine learning method called dictionary learning, which uses CT scans and learns specific image patterns and features pertaining to each class for a classification task. The results were evaluated with donor and recipient clinical measures.

RESULTS

Of the 100 lung pairs donated, 70 were considered acceptable for transplantation (based on standard clinical assessment) before CT screening and were consequently implanted. The remaining 30 pairs were screened but not transplanted. Our machine learning algorithm was able to detect pulmonary abnormalities on the CT scans. Among the patients who received donor lungs, our algorithm identified recipients who had extended stays in the intensive care unit and were at 19 times higher risk of developing chronic lung allograft dysfunction within 2 years posttransplant.

CONCLUSIONS

We have created a strategy to ex vivo screen donor lungs using a CT-based machine learning algorithm. As the use of suboptimal donor lungs rises, it is important to have in place objective techniques that will assist physicians in accurately screening donor lungs to identify recipients most at risk of posttransplant complications.

Local heterogeneity of normal lung parenchyma and small airways disease are associated with COPD severity and progression

BACKGROUND

Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline.

METHODS

PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n = 8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model.

RESULTS

Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (β of 0.106, p < 0.001) and VfSAD (β of 0.065, p = 0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69.

CONCLUSIONS

We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Quantitative CT of Normal Lung Parenchyma and Small Airways Disease Topologies are Associated With COPD Severity and Progression

Objectives

Small airways disease (SAD) is a major cause of airflow obstruction in COPD patients, and has been identified as a precursor to emphysema. Although the amount of SAD in the lungs can be quantified using our Parametric Response Mapping (PRM) approach, the full breadth of this readout as a measure of emphysema and COPD progression has yet to be explored. We evaluated topological features of PRM-derived normal parenchyma and SAD as surrogates of emphysema and predictors of spirometric decline.

Materials and Methods

PRM metrics of normal lung (PRMNorm) and functional SAD (PRMfSAD) were generated from CT scans collected as part of the COPDGene study (n=8956). Volume density (V) and Euler-Poincaré Characteristic (χ) image maps, measures of the extent and coalescence of pocket formations (i.e., topologies), respectively, were determined for both PRMNorm and PRMfSAD. Association with COPD severity, emphysema, and spirometric measures were assessed via multivariable regression models. Readouts were evaluated as inputs for predicting FEV1 decline using a machine learning model.

Results

Multivariable cross-sectional analysis of COPD subjects showed that V and χ measures for PRMfSAD and PRMNorm were independently associated with the amount of emphysema. Readouts χfSAD (β of 0.106, p<0.001) and VfSAD (β of 0.065, p=0.004) were also independently associated with FEV1% predicted. The machine learning model using PRM topologies as inputs predicted FEV1 decline over five years with an AUC of 0.69.

Conclusions

We demonstrated that V and χ of fSAD and Norm have independent value when associated with lung function and emphysema. In addition, we demonstrated that these readouts are predictive of spirometric decline when used as inputs in a ML model. Our topological PRM approach using PRMfSAD and PRMNorm may show promise as an early indicator of emphysema onset and COPD progression.

Lung cancer lesion detection in histopathology images using graph-based sparse PCA network

Early detection of lung cancer is critical for improvement of patient survival. To address the clinical need for efficacious treatments, genetically engineered mouse models (GEMM) have become integral in identifying and evaluating the molecular underpinnings of this complex disease that may be exploited as therapeutic targets. Assessment of GEMM tumor burden on histopathological sections performed by manual inspection is both time consuming and prone to subjective bias. Therefore, an interplay of needs and challenges exists for computer-aided diagnostic tools, for accurate and efficient analysis of these histopathology images. In this paper, we propose a simple machine learning approach called the graph-based sparse principal component analysis (GS-PCA) network, for automated detection of cancerous lesions on histological lung slides stained by hematoxylin and eosin (H&E). Our method comprises four steps: 1) cascaded graph-based sparse PCA, 2) PCA binary hashing, 3) block-wise histograms, and 4) support vector machine (SVM) classification. In our proposed architecture, graph-based sparse PCA is employed to learn the filter banks of the multiple stages of a convolutional network. This is followed by PCA hashing and block histograms for indexing and pooling. The meaningful features extracted from this GS-PCA are then fed to an SVM classifier. We evaluate the performance of the proposed algorithm on H&E slides obtained from an inducible K-ras^G12D lung cancer mouse model using precision/recall rates, F_β-score, Tanimoto coefficient, and area under the curve (AUC) of the receiver operator characteristic (ROC) and show that our algorithm is efficient and provides improved detection accuracy compared to existing algorithms.

The adapter protein FADD provides an alternate pathway for entry into the cell cycle by regulating APC/C-Cdh1 E3 ubiquitin ligase activity

The E3 ubiquitin ligase APC/C-Cdh1 maintains the G0/G1 state, and its inactivation is required for cell cycle entry. We reveal a novel role for Fas-associated protein with death domain (FADD) in the cell cycle through its function as an inhibitor of APC/C-Cdh1. Using real-time, single-cell imaging of live cells combined with biochemical analysis, we demonstrate that APC/C-Cdh1 hyperactivity in FADD- deficient cells leads to a G1 arrest despite persistent mitogenic signaling through oncogenic EGFR/KRAS. We further show that FADD_WT interacts with Cdh1, while a mutant lacking a consensus KEN-box motif (FADD_KEN) fails to interact with Cdh1 and results in a G1 arrest due to it its inability to inhibit APC/C-Cdh1. Additionally, enhanced expression of FADD_WT but not FADD_KEN, in cells arrested in G1 upon CDK4/6 inhibition, leads to APC/C-Cdh1 inactivation and entry into the cell cycle in the absence of retinoblastoma protein (Rb)- phosphorylation. FADD's function in the cell cycle requires its phosphorylation by CK1α at Ser-194 which promotes its nuclear translocation. Overall, FADD provides a CDK4/6-Rb-E2F independent "bypass" mechanism for cell cycle entry and thus a therapeutic opportunity for CDK4/6 inhibitor resistance.

Machine learning for screening of at-risk, mild and moderate COPD patients at risk of FEV1 decline: results from COPDGene and SPIROMICS

Purpose: The purpose of this study was to train and validate machine learning models for predicting rapid decline of forced expiratory volume in 1 s (FEV1) in individuals with a smoking history at-risk-for chronic obstructive pulmonary disease (COPD), Global Initiative for Chronic Obstructive Lung Disease (GOLD 0), or with mild-to-moderate (GOLD 1-2) COPD. We trained multiple models to predict rapid FEV1 decline using demographic, clinical and radiologic biomarker data. Training and internal validation data were obtained from the COPDGene study and prediction models were validated against the SPIROMICS cohort. Methods: We used GOLD 0-2 participants (n = 3,821) from COPDGene (60.0 ± 8.8 years, 49.9% male) for variable selection and model training. Accelerated lung function decline was defined as a mean drop in FEV1% predicted of > 1.5%/year at 5-year follow-up. We built logistic regression models predicting accelerated decline based on 22 chest CT imaging biomarker, pulmonary function, symptom, and demographic features. Models were validated using n = 885 SPIROMICS subjects (63.6 ± 8.6 years, 47.8% male). Results: The most important variables for predicting FEV1 decline in GOLD 0 participants were bronchodilator responsiveness (BDR), post bronchodilator FEV1% predicted (FEV1.pp.post), and CT-derived expiratory lung volume; among GOLD 1 and 2 subjects, they were BDR, age, and PRMlower lobes fSAD. In the validation cohort, GOLD 0 and GOLD 1-2 full variable models had significant predictive performance with AUCs of 0.620 ± 0.081 (p = 0.041) and 0.640 ± 0.059 (p < 0.001). Subjects with higher model-derived risk scores had significantly greater odds of FEV1 decline than those with lower scores. Conclusion: Predicting FEV1 decline in at-risk patients remains challenging but a combination of clinical, physiologic and imaging variables provided the best performance across two COPD cohorts.

CT-based Machine Learning for Donor Lung Screening Prior to Transplantation

Background

Assessment and selection of donor lungs remains largely subjective and experience based. Criteria to accept or decline lungs are poorly standardized and are not compliant with the current donor pool. Using ex vivo CT images, we investigated the use of a CT-based machine learning algorithm for screening donor lungs prior to transplantation.

Methods

Clinical measures and ex-situ CT scans were collected from 100 cases as part of a prospective clinical trial. Following procurement, donor lungs were inflated, placed on ice according to routine clinical practice, and imaged using a clinical CT scanner prior to transplantation while stored in the icebox. We trained and tested a supervised machine learning method called dictionary learning , which uses CT scans and learns specific image patterns and features pertaining to each class for a classification task. The results were evaluated with donor and recipient clinical measures.

Results

Of the 100 lung pairs donated, 70 were considered acceptable for transplantation (based on standard clinical assessment) prior to CT screening and were consequently implanted. The remaining 30 pairs were screened but not transplanted. Our machine learning algorithm was able to detect pulmonary abnormalities on the CT scans. Among the patients who received donor lungs, our algorithm identified recipients who had extended stays in the ICU and were at 19 times higher risk of developing CLAD within 2 years post-transplant.

Conclusions

We have created a strategy to ex vivo screen donor lungs using a CT-based machine learning algorithm. As the use of suboptimal donor lungs rises, it is important to have in place objective techniques that will assist physicians in accurately screening donor lungs to identify recipients most at risk of post-transplant complications.

AB1250 TOFACITINIB IS A SAFE AND EFFECTIVE TREATMENT OPTION FOR JUVENILE IDIOPATHIC ARTHRITIS

Background

The management of juvenile idiopathic arthritis(JIA) is often constrained by the limited number of oral drugs available. Whether JAK inhibitors would add a much needed therapeutic armamentarium in this regard needs to be explored.

Objectives

To assess the safety and efficacy of tofacitinib in juvenile idiopathic arthritis (JIA) patient who were prescribed during the period January 2021 to December 2021.

Methods

It’s a retrospective study of JIA patients who were prescribed tofacitinib during the period Jan 21 to Dec 21 with minimum of 3 months’ follow-up after prescribing tofacitinib. The demographics,details of medications,investigations parameters and any adverse events were noted.

Results

There were a total of 35 patients who were given tofacitinib during this period. Male is to female ratio is 25:10, mean age of 12.91(4.81) yrs., the mean disease duration was 58.6 months. Enthesitis related arthritis(ERA) was the commonest seen in 12, followed by oligo articular in 10, polyarticular in 7 and systemic onset in 6. In the ERA group 10 were HLA B27 +VE, of the oligo articular 6 were ANA +VE, in the polyarticular one was RF +ve. Out of the 35,14 were already on biologicals (tocilizumab and anti TNFs). Tofacitinib was stopped in 8 patients during this period, 5 as they achieved remission, 2 with no response and one because of itching and abdominal pain. There were no documented infections. There was significant reduction in the inflammatory markers (ESR, CRP), leucocyte count and platelet count.

Before tofaAfter tofap valueMethotrexate in mg (week) mean(stdev)9.64(1.94)8.88(3.34)0.66Steroid in mg mean (stdev)3(2.35)2.8(1.8)0.91Leucocyte count mean(stdev)11242(1858)7884(1471)0.005Platelet count in lakhsMean(stdev)4.51(0.48)3.37(0.82)0.017ESR mm/1hr57.75(17.25)30.83(11.48)0.009CRP mg/L25.36(10.9)12.36(7.97)0.05

Conclusion

Tofacitinib seems to be a promising drug in the management of JIA with good safety profile and efficacy.

References

[1] Brunner HI, Schanberg LE, Kimura Y et al. New medications are needed for children with juvenile idiopathic arthritis. Arthritis Rheumatol. 2020; 72: 1945-1951.

Disclosure of Interests

None declared

CT-Based Commercial Software Applications: Improving Patient Care Through Accurate COPD Subtyping

Chronic obstructive pulmonary disease (COPD) is heterogenous in its clinical manifestations and disease progression. Patients often have disease courses that are difficult to predict with readily available data, such as lung function testing. The ability to better classify COPD into well-defined groups will allow researchers and clinicians to tailor novel therapies, monitor their effects, and improve patient-centered outcomes. Different modalities of assessing these COPD phenotypes are actively being studied, and an area of great promise includes the use of quantitative computed tomography (QCT) techniques focused on key features such as airway anatomy, lung density, and vascular morphology. Over the last few decades, companies around the world have commercialized automated CT software packages that have proven immensely useful in these endeavors. This article reviews the key features of several commercial platforms, including the technologies they are based on, the metrics they can generate, and their clinical correlations and applications. While such tools are increasingly being used in research and clinical settings, they have yet to be consistently adopted for diagnostic work-up and treatment planning, and their full potential remains to be explored.

Associations between breast implants and postpartum lactational mastitis in breastfeeding women: retrospective study

OBJECTIVE

To examine the putative associations between breast implants and postpartum lactational mastitis.

DESIGN

Observational retrospective study.

SETTING

Digital database of Maccabi Healthcare Services, integrated health maintenance organisation in Israel.

POPULATION

Breastfeeding mothers from 2003 to 2016 based on an initial health maintenance organisation data set of 28 383 singleton live births in Israel.

METHODS

Multivariate analysis and propensity score matching were used to test the extent to which breast implants were associated with lactational mastitis during the 6-month postpartum period in breastfeeding mothers. Analyses for potential confounders were adjusted for socio-economic status, smoking and parity.

MAIN OUTCOME MEASURE

Lactational mastitis among breastfeeding women with breast implants compared with women without breast implants.

RESULTS

Mothers with breast implants (n = 6099) were significantly (P < 0.001) more likely to be diagnosed with postpartum mastitis (8.3%) than mothers with no breast implants(n = 22 284) (6.6%) at an odds ratio of 1.22 (95% CI 1.09-1.35) after adjusting for confounders.

CONCLUSION

Breast augmentation is associated with an increased risk of postpartum lactational mastitis in the 6-month postpartum period. In light of these findings, it is important for health professionals to instruct women who have undergone breast augmentation on correct breastfeeding techniques, ways to avoid risk factors, and to be alert to signs permitting the early detection of lactational mastitis.

TWEETABLE ABSTRACT

A study of over 28,000 breastfeeding women has shown that breast augmentation is associated with an increased risk of postpartum lactational mastitis in the six-month postpartum period.

Spin-up conversion, exchange-interactions, and tailored magnetic properties in core-shell La2NiMnO6of small crystallites

La₂NiMnO₆-a ferromagnetic (FM) insulator offers tunable charge carriers and spins useful to devise its multiple properties and applications. In this view, we studied a core-shell La₂NiMnO₆(2-3 nm shell on 65 - 80 nm core) of a Ni²⁺/Ni³⁺(d⁷) to Mn⁴⁺/Mn³⁺(d⁴) spin-up conversion- revived a new FM phase-2, raising a spin-densityσ_s = 0.7 s a^-1over the Ni^2+/Mn⁴⁺species (phase-1),σ_s = 0.5 s a^-1, i.e. 2.12μ_B/f.u. larger spin moment. HRTEM images studied with x-ray diffraction characterizing core-shell structure that plays a crucial role in tuning the high spin FM phase-2 of profound properties. Below 110 K, the dc magnetization and ac magnetic susceptibilityχ(ω,T) reveal a metastable magnetic behavior on an antiferromagnetic canting of a spin-glass nature. The results follow a Vogel-Fulcher type relaxation with a relaxation timeτ₀∼ 10^-13s, confirming a spin-glass freezing behavior. Uniquely, FM field of phase-1 controls magnetics of phase 2 of a coupled magnet, modulating joint features with small thermal magnetic hysteresis on heating-cooling cycles.

Improved detection of air trapping on expiratory computed tomography using deep learning

BACKGROUND

Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are highly variable, resulting in limited efficacy for monitoring disease progression.

OBJECTIVE

To investigate the effectiveness of a convolutional neural network (CNN) model for quantifying and monitoring AT, and to compare it with other quantitative AT measures obtained from threshold-based techniques.

MATERIALS AND METHODS

Paired volumetric whole lung inspiratory and expiratory CT scans were obtained at four time points (0, 3, 12 and 24 months) on 36 subjects with mild CF lung disease. A densely connected CNN (DN) was trained using AT segmentation maps generated from a personalized threshold-based method (PTM). Quantitative AT (QAT) values, presented as the relative volume of AT over the lungs, from the DN approach were compared to QAT values from the PTM method. Radiographic assessment, spirometric measures, and clinical scores were correlated to the DN QAT values using a linear mixed effects model.

RESULTS

QAT values from the DN were found to increase from 8.65% ± 1.38% to 21.38% ± 1.82%, respectively, over a two-year period. Comparison of CNN model results to intensity-based measures demonstrated a systematic drop in the Dice coefficient over time (decreased from 0.86 ± 0.03 to 0.45 ± 0.04). The trends observed in DN QAT values were consistent with clinical scores for AT, bronchiectasis, and mucus plugging. In addition, the DN approach was found to be less susceptible to variations in expiratory deflation levels than the threshold-based approach.

CONCLUSION

The CNN model effectively delineated AT on expiratory CT scans, which provides an automated and objective approach for assessing and monitoring AT in CF patients.

Abstract PO-086: Detection of cancer lesions in histopathological lung images using a sparse PCA network

Purpose: Lung cancer has been the leading cause of cancer-related deaths worldwide. To address the clinical need for efficacious treatments, genetically engineered mouse models (GEMMs) have become integral in identifying and evaluating unique pathways that may be exploited as therapeutic targets. Assessment of GEMM tumor burden on histopathological sections performed by manual inspection is both time consuming and prone to subjective bias. Therefore, an interplay of needs and challenges exists for computer aided detection tools, for the accurate and efficient analysis of these histopathology images. Our work demonstrates a simple machine learning approach called sparse principal component analysis (PCA) network, for automated detection of cancerous lesions on histological lung slides stained by hematoxylin and eosin (H&E). Methods: Our method comprises four steps: 1) cascaded sparse PCA; 2) graph-based PCA hashing; 3) block-wise histograms; and 4) support vector machine (SVM) classification. In our proposed architecture, sparse PCA is employed to learn the filter banks of the multiple stages. This is followed by a graph-based PCA hashing and block histograms for indexing and pooling. The meaningful features extracted from this sparse PCA are then fed to an SVM classifier. We tested the proposed sparse PCA network on H&E slides obtained from an inducible KrasG12D lung cancer mouse model. Our dataset consists of N = 21 whole slide histopathology lung images with 9 non-tumor bearing control mice and 12 mice with visible lung tumors. Tumor lesions from 12 lung images with visible tumors were visually identified by three trained individuals, which served as ground truth. The size of each image in our dataset is 2048 × 2048 pixels. Each image was divided into non-overlapping image patches of size 20 × 20 pixels consisting of a total of 12,361 cancer lesion patches and 207,839 non-cancer patches. We used 50% of the data for training and 50% of the data for testing our proposed sparse PCA network. We evaluated our algorithm using conventional metrics that have been used for evaluation of classification algorithms, namely precision (P), recall (R), and coverage measure (F-score). Results: The automatic cancer lesion detection results were compared with manually annotated ground truth. The proposed method achieves a cancer lesion detection accuracy of 97.98% with P = 0.8624, R = 0.9062 and F-score = 0.8790. The proposed method was found to take on average 17 minutes to train and learn a good representation for accurate and efficient classification of cancerous lesions within the images. Conclusion: We demonstrated a simple machine learning methodology for detection of cancerous lesions within histopathological lung images. Experimental results show that the proposed method is able to classify the regions of interest both efficiently and accurately. Future work will focus on feature extraction of individual tumors and tumor location within lungs.

Citation Format: Sundaresh Ram, Wenfei Tang, Alexander J. Bell, Cara Spencer, Alexander Buschhuas, Charles R. Hatt, Marina P. di Magliano, Stefanie Galban, Craig J. Galban. Detection of cancer lesions in histopathological lung images using a sparse PCA network [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PO-086.

In vivo quantitative imaging biomarkers of bone quality and mineral density using multi-band-SWIFT magnetic resonance imaging

Bone is a composite biomaterial of mineral crystals, organic matrix, and water. Each contributes to bone quality and strength and may change independently, or together, with disease progression and treatment. Even so, there is a near ubiquitous reliance on ionizing x-ray-based approaches to measure bone mineral density (BMD) which is unable to fully characterize bone strength and may not adequately predict fracture risk. Characterization of treatment efficacy in bone diseases of altered remodeling is complicated by the lack of imaging modality able to safely monitor material-level and biochemical changes in vivo. To improve upon the current state of bone imaging, we tested the efficacy of Multi Band SWeep Imaging with Fourier Transformation (MB-SWIFT) magnetic resonance imaging (MRI) as a readout of bone derangement in an estrogen deficient ovariectomized (OVX) rat model during growth. MB-SWIFT MRI-derived BMD correlated significantly with BMD measured using micro-computed tomography (μCT). In this rodent model, growth appeared to overcome estrogen deficiency as bone mass continued to increase longitudinally over the duration of the study. Nonetheless, after 10 weeks of intervention, MB-SWIFT detected significant changes consistent with estrogen deficiency in cortical water, cortical matrix organization (T₁), and marrow fat. Findings point to MB-SWIFT's ability to quantify BMD in good agreement with μCT while providing additive quantitative outcomes about bone quality in a manner consistent with estrogen deficiency. These results indicate MB-SWIFT as a non-ionizing imaging strategy with value for bone imaging and may be a promising technique to progress to the clinic for monitoring and clinical management of patients with bone diseases such as osteoporosis.

Abstract 3855: Oncogenic Kras-mediated regulation of the tumor microenvironment in lung cancer

Lung cancer remains the leading cause of cancer-related deaths worldwide, with an estimated 1.6 million deaths each year. Non-small cell lung cancer (NSCLC) is with 85% by far the most common subtype of lung cancer, comprising adenocarcinomas and lung squamous cell carcinoma. Mutations in Kirsten rat sarcoma viral oncogene homolog (KRAS), epidermal growth factor receptor (EGFR) and anaplastic lymphoma receptor tyrosine kinase (ALK) genes are common with the worst overall survival for KRAS mutant adenocarcinoma patients. We have established a murine model of lung cancer, wherein expression of oncogenic Kras can be controlled genetically, allowing activation of oncogenic KrasG12D (Kras*) to initiate tumor growth, tumor eradication upon Kras* depletion and re-activation as a means to model relapse. Oncogenic Kras depletion (deactivation) has previously been reported to result in tumor cell apoptosis even in the presence of tumor suppressor loss. However, the mechanisms of apoptosis, the role of the immune system on these changes, and the mechanisms allowing some tumor cells to escape apoptosis, which typically results in tumor relapse, are unknown. Here, we interrogated the immune response in mediating tumor regression and relapse using this genetically engineered models. Multiplex immunohistochemistry as well as CyTOF provided insight into the changes in immune contexture upon Kras* depletion in mice haploinsufficient for tumor suppressor p53 or mutant for p53 (R172H). Interestingly, total number of T cells including cytotoxic T cells (CTLs) was elevated in lung tumors from p53 mutant mice supporting findings of heightened immune activation and overall response to immune therapy with an increased mutational burden. Kras* inactivation and thus inhibition of MAPK signaling resulted in an overall decrease in abundance of CTLs and antigen presenting cells (APC) as well as engagement of CTL with tumor cells and APCs indicating a decrease in immune presence likely due to proceeding tumor cell kill and immune recruitment. However, intracellular distance of CTL with tumor cells indicated active tumor cell kill of the CTLs to eradicate remaining tumor cells. In summary, these findings support recent observation of increased immune activation in tumors with higher mutational load as well as changes mediated by inhibition of MAPK signaling which both maybe harnessed for enhancing future immunotherapies.

Citation Format: Nina Steele, Kristena Y. Abdelmalak, Sarah F. Ferris, Jennifer M. Lee, Carlos Espinoza, Yaqing Zhang, Sundaresh Ram, Craig Galban, Nithya Ramnath, Timothy L. Frankel, Marina Pasca di Magliano, Stefanie Galbán. Oncogenic Kras-mediated regulation of the tumor microenvironment in lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3855.

Multicenter evaluation of parametric response mapping as an indicator of bronchiolitis obliterans syndrome after hematopoietic stem cell transplantation

Parametric response mapping (PRM) is a novel computed tomography (CT) technology that has shown potential for assessment of bronchiolitis obliterans syndrome (BOS) after hematopoietic stem cell transplantation (HCT). The primary aim of this study was to evaluate whether variations in image acquisition under real-world conditions affect the PRM measurements of clinically diagnosed BOS. CT scans were obtained retrospectively from 72 HCT recipients with BOS and graft-versus-host disease from Fred Hutchinson Cancer Research Center, Karolinska Institute, and the University of Michigan. Whole lung volumetric scans were performed at inspiration and expiration using site-specific acquisition and reconstruction protocols. PRM and pulmonary function measurements were assessed. Patients with moderately severe BOS at diagnosis (median forced expiratory volume at 1 second [FEV1] 53.5% predicted) had similar characteristics between sites. Variations in site-specific CT acquisition protocols had a negligible effect on the PRM-derived small airways disease (SAD), that is, BOS measurements. PRM-derived SAD was found to correlate with FEV1% predicted and FEV1/ forced vital capacity (R = -0.236, P = .046; and R = -0.689, P < .0001, respectively), which suggests that elevated levels in the PRM measurements are primarily affected by BOS airflow obstruction and not CT scan acquisition parameters. Based on these results, PRM may be applied broadly for post-HCT diagnosis and monitoring of BOS.

Green Synthesis of Cr3+ Doped CaIn₂O₄-Carbon Hybrid Nanostructure and Its Light Absorption and Emission Properties

In this research article, we have used a novel route for synthesis of a greenish phosphor C-CaIn₂O₄ doped with Cr³⁺ ions using green plant (aloe vera gel) and measured its light absorption and emission properties. Our main aim was to enhance the light absorption and emission properties of undoped C-CaIn₂O₄ in order to widen its applications. The introduction of CrO₃ ions can produce Cr ion defects that favor charge balance in Cr³⁺:C-CaIn₂O₄ to facilitate its photoluminescence. The effect of doping in core-shell nanostructure can effectively transfer energy from charge-transfer absorption band of optical host material to characteristic transition of Cr³⁺ ions, utilizing more energy from host absorption for the photoluminescence of Cr³⁺ ions. As-prepared Cr³⁺:C-CaIn₂O₄ exhibits two bands at 270 nm and 370 nm, which are shifted to at 265 and 370 nm when it is annealed at higher dosage of Cr³⁺ ions. These are the ligand-to-metal O^2- to Cr³⁺ charge transfer bands. The light-emission is studied in analyzing migration, transfer and recombination processes of light-induced e^--h⁺ pairs. The results are described in correlation to a Cr³⁺:C-CaIn₂O₄ core-shell nanostructure.

The importance of ensuring artificial intelligence and machine learning can be understood at the human level

With rapid developments in big data technology and the prevalence of large-scale datasets from diverse sources, the healthcare predictive analytics (HPA) field is witnessing a dramatic surge in interest. In healthcare, it is not only important to provide accurate predictions, but also critical to provide reliable explanations to the underlying black-box models making the predictions. Such explanations can play a crucial role in not only supporting clinical decision-making but also facilitating user engagement and patient safety. If users and decision makers do not have faith in the HPA model, it is highly likely that they will reject its use. Furthermore, it is extremely risky to blindly accept and apply the results derived from black-box models, which might lead to undesirable consequences or life-threatening outcomes in domains with high stakes such as healthcare. As machine learning and artificial intelligence systems are becoming more capable and ubiquitous, explainable artificial intelligence and machine learning interpretability are garnering significant attention among practitioners and researchers. The introduction of policies such as the General Data Protection Regulation (GDPR), has amplified the need for ensuring human interpretability of prediction models. In this talk I will discuss methods and applications for developing local as well as global explanations from machine learning and the value they can provide for healthcare prediction.

Synthesis of Broad Band Violet-Blue Light-Emitting Core-Shell Cr3+:C-CaIn₂O₄ Nanowires

We developed a simple, effective and green method for synthesis of broad band violet-blue lightemitting core-shell Cr³⁺:C-CaIn²O⁴ nanowires (1-10 mol% of Cr³⁺) using aloe vera nectar. Calcium indate (CaIn²O⁴) is an important wideband gap semiconductor that could be explored for optical doping such as transition metals and/or rare-earths useful to make light-emitters, optical data storage, and other devices. The nectar embeds the cations in a gel so as it controls an ionic conversion Cr⁶⁺ to Cr³⁺ in ambient air. When grafting a carbon layer on surface of Cr³⁺:CaIn²O⁴ crystallites it yields a core-shell structure of tailored dielectric, optical and other properties. Asprepared Cr³⁺:CaIn²O⁴-C exhibits two bands at 270 nm and 360 nm, which got shifted-to at 265 and 370 nm when annealed at higher dosage of Cr³⁺ ions. These are the ligand-to-metal O^2- to Cr³⁺ charge transfer bands. We studied the light-emission properties in analyzing migration, transfer and recombination processes of light-induced e^--h⁺ pairs in detail in correlation to a Cr³⁺:CaIn²O⁴-C core-shell nanostructure.

Racioethnic differences in the biomechanical response of the lamina cribrosa

Glaucoma is the second leading cause of irreversible blindness in the world with a higher prevalence in those of African Descent (AD) and Hispanic Ethnicity (HE) than in those of European Descent (ED). The objective of this study was to investigate the pressure dependent biomechanical response of the lamina cribrosa (LC) in normal human donor tissues from these racioethnic backgrounds. Pressure inflation tests were performed on 24 human LCs (n = 9 AD, n = 6 ED, and n = 9 HE) capturing the second harmonic generation (SHG) signal of collagen at 5, 15, 30, and 45 mmHg from an anterior view. A non-rigid image registration technique was utilized to determine the 3D displacement field in each LC from which 3D Green strains were calculated. The peak shear strain in the superior quadrant of the LC in those of ED was significantly higher than in those of AD and HE (p-value = 0.005 & 0.034, respectively) where ED = 0.017 [IQR = 0.012-0.027], AD = 0.0002 [IQR = -0.001-0.007], HE = 0.0016 [IQR = -0.002-0.012]). There were also significant differences in the regional strain heterogeneity in those of AD and HE that were absent in those of ED. This work represents, to our knowledge, the first ex-vivo study identifying significant differences in the biomechanical response of the LC in populations at increased risk of glaucoma. Future work will be necessary to assess if and how these differences play a role in predisposing those of Hispanic Ethnicity and African Descent to the onset and/or progression of primary open angle glaucoma. STATEMENT OF SIGNIFICANCE: Glaucoma is the second leading cause of irreversible blindness in the world and occurs more frequently in those of African Descent and Hispanic Ethnicity than in those of European Descent. To date, there has been no ex-vivo study quantifying differences in the biomechanical response of the non-glaucomatous lamina cribrosa (LC) across these racioethnic backgrounds. In this work we report, for the first time, differences in the pressure dependent biomechanical response of LC across different racioethnic groups as quantified using nonlinear optical microscopy. This study lays the foundation for future work investigating if and how these differences may play a role in predisposing those at increased risk to the onset and/or progression of primary open angle glaucoma.

Image Inpainting Using Nonlocal Texture Matching and Nonlinear Filtering

Nonlocal texture similarity and local intensity smoothness are both essential for solving most image inpainting problems. In this paper, we propose a novel image inpainting algorithm that is capable of reproducing the underlying textural details using a nonlocal texture measure and also smoothing pixel intensity seamlessly in order to achieve natural-looking inpainted images. For matching texture, we propose a Gaussian-weighted nonlocal texture similarity measure to obtain multiple candidate patches for each target patch. To compute the pixel intensity, we apply the -trimmed mean filter to the candidate patches to inpaint the target patch pixel-by-pixel. The proposed algorithm is compared with four current image inpainting algorithms under different scenarios, including object removal, texture synthesis, and error concealment. Experimental results show that the proposed algorithm outperforms the existing algorithms when inpainting large missing regions in images with texture and geometric structures.

Abstract PD5-08: Neoadjuvant chemotherapy alters the genomic landscape and immune microenvironment of breast cancers

Understanding how standard-of-care drug treatments affect tumor intrinsic biology and microenvironment is critical for elucidating drug resistance mechanisms and developing better combination therapies as well as new therapies. To characterize the effects of neoadjuvant chemotherapy (NAC) on the genome, transcriptome and tumor infiltrating leukocytes (TILs), we have conducted whole exome and whole transcriptome sequencing of a large longitudinal breast cancer cohort consisting of 146 cases and 281 paired tumor samples. In total, 52 (38%) patients achieved pathologic complete response (pCR) while 85 patients (62%) had residual disease with standard chemotherapy regimen. Tumor biopsies were collected for each patient at three time points – pre-treatment, three weeks after the first cycle of anthracycline and cyclophosphamide (AC) and at the time of surgery after 3 more cycles of AC followed by 4 cycles of taxane or taxane plus Herceptin in case of HER2+ subtype. We detected 5,955 protein-altering somatic mutations affecting 4,414 genes in pretreatment samples and 502 acquired mutations in surgery samples affecting 477 genes including 19recurrently mutated genes such as TP53 and NOTCH1. Across all subtypes, 4,346 genes were differentially expressed (DE) following NAC treatment and significantly enriched in pathways such as cell cycle, ER signaling, PI3K/mTOR, immune and metabolism. Expression-based virtual microdissection analysis indicated that NAC treatment induced an increase in the fractions of stromal and adjacent normal tissue compartment, consistent with observed reduction in tumor cellularity. To assess the NAC induced changes in the molecular landscape of these tumors, we compared molecular features including gene expression signatures, mutation prevalence and copy number alteration between three time points while adjusting for confounding effects of molecular subtype and tumor cellularity. We found that NAC induced dynamic changes in gene expression signatures associated with proliferation and immunomodulatory treatment response. We further validated the observed pattern of change in TILs through histopathology and digital imaging analyses. In pretreatment tumors, 116 genes were DE between patients with pCR vs. those with residual disease with significant enrichment in immune/inflammatory pathways. Further, pre-treatment TIL levels were found to be significantly associated with pCR, echoing previous reports in breast cancers that implicated anti-tumor immunity in mediating the efficacy of chemotherapies. Our analyses also revealed associations between NAC response and baseline genomic attributes such as genomic alterations that affect DNA damage repair pathways. Taken together, these results suggest that NAC induced a multitude of changes on the genomic landscape and immune microenvironment of breast cancers, some of which point to combination strategies with immunomodulatory therapies and therapies that target DNA damage repair.

Citation Format: Kan Z, Lal S, Ding Y, Lee JE, Lee S-H, Lee SK, Yu JH, Choi Y-l, Kim SW, Nam SJ, Kim J-Y, Ram S, Powell E, Ching K, Cho SY, Bonato V, Deng S, Park W-Y, Rejto P, Bienkowska J, Park Y-H. Neoadjuvant chemotherapy alters the genomic landscape and immune microenvironment of breast cancers [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD5-08.

Abstract P2-07-01: Integrative analyses of immunophenotypes and multi-omics profiles in breast cancers

The advent of immuno-oncology (IO) therapies has made it an imperative to characterize intratumoral immune microenvironment in addition to oncogenic alterations through molecular profiling of the tumor. To elucidate the baseline profiles of tumor infiltrating leukocytes (TILs) in breast cancer (BC) in the context of molecular subtypes and oncogenic alterations, we performed whole-exome sequencing (WES) and RNA-Seq of an Asian BC cohort (SMC) consisting of 178 treatment naïve primary tumors. A subset of 120 tumors was further analyzed by H&E and IHC using a panel of 8 TIL markers (CD45, CD4, CD8, CD163, PD1, PD-L1, IDO1 and FOXP3). Using expression signatures representing distinct immune cell types, we classified an expression compendium of 2,781 tumor samples, including SMC and multiple cancers from TCGA, into three immune subtypes with high, medium and low levels of TILs. Basal and HER2 subtypes show higher levels of TILs than Luminal subtypes, consistent with observed clinical responses to checkpoint blockade in clinical trials. Moreover, Asian BCs were significantly enriched in TIL-high subtype (35.3%) compared to the primarily Caucasian TCGA BC cohort (20.2%) while 50.6% of the highly immunogenic Lung adenocarcinoma was TIL-high. We then applied machine learning methods to detect and quantify TILs from H&E images of 120 SMC and 349 TCGA BC tumors. The expression signature analysis results were concordant with independently derived histology based TIL data. Taken together, our findings suggest that IO therapies may be more effective in HR negative BC subtypes and Asian BCs.

Leukocyte exclusion (LE), an immunophenotype where TILs concentrate at the tumor periphery, has been linked to worse prognosis and resistance to IO therapies. Visual assessment of whole tumor IHC images identified LE patterns in 25% of SMC cases. We observed differential distribution of LE by molecular subtype and evidence for selective exclusion of immune cell subsets. Covariate analyses with clinical and molecular data while controlling for subtype as a confounder identified significant associations with tumor proliferation index, percent tumor purity and TP53 mutations. LE is also significantly associated with expression signatures of chemokine signaling, macrophages, angiogenesis and hypoxia, indicating that marked distinctions exist in both tumor intrinsic and microenvironment characteristics between TIL excluded and TIL infiltrated tumors. To validate these findings, we independently identified LE for 200 cases of TCGA BCs based on patterns of TILs extracted from H&E images and saw significant concordance of covariate relationships identified between TCGA and SMC. Our study provided a rare comprehensive resource for studying tumor associated immunity in breast cancers by generating the integrated multi-omics and IO profiles for a large cohort of primary tumors. Comparative analyses revealed that TIL activities are highly variable across different intrinsic subtypes and geographic origins of BC, with potential implications for IO therapeutic application. Correlative analyses of immunophenotypes with molecular data further yielded insights into LE's role in immune escape and identified hallmark signatures for LE indicative of causal molecular mechanisms.

Citation Format: Kan Z, Powell E, Ram S, Ching K, Ding Y, Vizcarra P, Nichols T, Hardwick J, Lee S-H, Cho SY, Choi Y-L, Yu J-H, Park YH. Integrative analyses of immunophenotypes and multi-omics profiles in breast cancers [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-07-01.

An evidenced based checklist to support anti-dementia medication withdrawal in people with down syndrome (DS), intellectual disability (Id) and dementia

DS with aging is associated with greatly increased risk of developing dementia similar to Alzheimer's. Anti-dementia drug discontinuation is recommended when clinical benefit is not determined. In DS it is more complex as medication ill effects of stopping needs to be weighed in balance to extraneous processes such as environment changes, sensory impediments and physical ill health and natural progression of dementia.

Aim

Can identified risk factors extracted from a comprehensive literature review be developed into an evidence based check list to support risk minimized person centered withdrawal of anti-dementia drugs when considered not to be efficacious in DS?

Method

A detailed literature review using Medline, PsychInfo, Cinahl and Embase with relevant search terms in various permutations and combinations without any date limit enquiring current evidence base on anti-dementia medication withdrawal was conducted. The review also looked to extract the common risk factors in stopping medication. All risk factors were collated, reviewed by a focus group of experts, developed into a checklist.

Results

Thirty abstracts were obtained following the search. Six papers were short-listed. No papers identified a structured approach to medication reduction. An 18-factor checklist was applied prospectively to 30 cases. The checklist was sensitive to identify change to guide clinical decision-making.

Conclusions

Currently, decision to peg medication withdrawal risk is arbitrary and clinical in dementia especially in DS dementia. The evidenced based developed checklist is useful to support and structure clinical decisions. It helps clinicians and patients to focus on promoting safety, reduce harm and guide treatment.

Disclosure of interest

The authors have not supplied their declaration of competing interest.

Three-Dimensional Segmentation of the Ex-Vivo Anterior Lamina Cribrosa From Second-Harmonic Imaging Microscopy

The lamina cribrosa (LC) is a connective tissue in the posterior eye with a complex mesh-like trabecular microstructure, through which all the retinal ganglion cell axons and central retinal vessels pass. Recent studies have demonstrated that changes in the structure of the LC correlate with glaucomatous damage. Thus, accurate segmentation and reconstruction of the LC is of utmost importance. This paper presents a new automated method for segmenting the microstructure of the anterior LC in the images obtained via multiphoton microscopy using a combination of ideas. In order to reduce noise, we first smooth the input image using a 4-D collaborative filtering scheme. Next, we enhance the beam-like trabecular microstructure of the LC using wavelet multiresolution analysis. The enhanced LC microstructure is then automatically extracted using a combination of histogram thresholding and graph-cut binarization. Finally, we use morphological area opening as a postprocessing step to remove the small and unconnected 3-D regions in the binarized images. The performance of the proposed method is evaluated using mutual overlap accuracy, Tanimoto index, F-score, and Rand index. Quantitative and qualitative results show that the proposed algorithm provides improved segmentation accuracy and computational efficiency compared to the other recent algorithms.

Abstract P1-05-15: Multi-omics and immuno-oncology profiling reveal distinct molecular signatures of young Asian breast cancers

Breast cancers (BC) in younger, premenopausal patients (YBC) tend to be more aggressive with worse prognosis, higher chance of relapse and poorer response to endocrine therapies compared to breast cancers in older patients. The proportion of YBC (age ≤ 40) among BC in East Asia is estimated to be 16-32%, significantly higher than the 7% reported in Western countries. To characterize the molecular bases of Asian YBC, we have performed whole-exome sequencing (WES) and whole-transcriptome sequencing (WTS) on tumor and matched normal samples from 134 Korean BC patients consisting of 74 YBC cases (age ≤ 40) and 60 OBC cases (age &gt; 40). We then performed comparison analyses and integrative analyses with the TCGA BC cohort consisting of 1,116 tumors from primarily Caucasian patients, also grouped by age into YBC (age ≤ 40), IBC (40 &lt; age ≤ 60) and OBC (age &gt; 60).

Somatic mutation prevalence analysis identified 7 significantly mutated genes and the same top three genes – TP53, GATA3 and PIK3CA – were reported by the TCGA BC study. To identify differentially expressed (DE) genes and pathways in YBCs vs. OBCs, we performed logistic regression analyses while controlling for the confounding effects of tumor purity and stage. We were surprised to see a significant overlap in DE pathways between a comparison of adjacent normal tissues in younger vs. older TCGA cohorts and a comparison of YBC vs. OBC tumors, indicating that normal tissue compartment could contribute to observed differences between bulk tumors. To separately examine molecular signatures from tumor, stroma and normal compartments, we used non-negative matrix factorization (NMF) analyses to virtually dissect bulk tumor expression data and identified 14 factors including 3 factors associated with normal tissues, 1 factor associated with stroma and 1 factor associated with tumor infiltrating lymphocytes (TIL). Integrative analyses of tumor associated factors and DE pathways revealed that estrogen response, endocrine therapy resistance, and oxidative phosphorylation pathways are up-regulated in YBCs compared to OBCs while cell cycle and proliferation pathways are up-regulated in Asian OBCs. Interestingly, many immune and inflammation pathways correlated with the TIL factor were significantly upregulated in OBCs vs. YBCs. Using gene expression signatures representing distinct immune cell types, we classified our cohort into four subtypes of varying TIL activities and observed significant enrichment of the TIL-high subtype in OBCs compared to YBCs. These observations were confirmed by IHC analyses of four TIL markers (CD45, CD4, CD8 and CD163) in 120 tumors.

To our knowledge, this is the first large-scale multi-omics study of Asian breast cancer and would significantly contribute to the compendium of molecular data available for studying young breast cancers. The major landmarks in the molecular landscape looked similar across BCs of different ethnicities and ages, however, we have identified a number of distinguishing molecular characteristics associated with Asian YBC. The sources for some signatures were further traced to non-tumor intrinsic compartments, indicating that tumor microenvironment may play potentially important roles in driving the carcinogenesis of young breast cancers.

Citation Format: Kan Z, Ding Y, Cho S, Lee S-H, Powell E, Jung HH, Chung W, Deng S, Choi Y-l, Kim J, Park W-Y, Vizcarra P, Fernandez-Banet J, Nichols T, Ram S, Lee SK, Kim SW, Lee JE, Ching KA, Kim J-Y, Ahn JS, Im Y-H, Nam SJ, Park YH. Multi-omics and immuno-oncology profiling reveal distinct molecular signatures of young Asian breast cancers [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-05-15.

Size-Invariant Detection of Cell Nuclei in Microscopy Images

Accurate detection of individual cell nuclei in microscopy images is an essential and fundamental task for many biological studies. In particular, multivariate fluorescence microscopy is used to observe different aspects of cells in cultures. Manual detection of individual cell nuclei by visual inspection is time consuming, and prone to induce subjective bias. This makes automatic detection of cell nuclei essential for large-scale, objective studies of cell cultures. Blur, clutter, bleed-through, imaging noise and touching and partially overlapping nuclei with varying sizes and shapes make automated detection of individual cell nuclei a challenging task using image analysis. In this paper we propose a new automated method for fast and robust detection of individual cell nuclei based on their radial symmetric nature in fluorescence in-situ hybridization (FISH) images obtained via confocal microscopy. The main contributions are two-fold. 1) This work presents a more accurate cell nucleus detection system using the fast radial symmetry transform (FRST). 2) The proposed cell nucleus detection system is robust against most occlusions and variations in size and moderate shape deformations. We evaluate the performance of the proposed algorithm using precision/recall rates, Fβ-score and root-mean-squared distance (RMSD) and show that our algorithm provides improved detection accuracy compared to existing algorithms.

Screening for tuberculosis and LTBI in diabetes patients, Pohnpei, Federated States of Micronesia

A retrospective cohort study was performed in Pohnpei, a small Pacific Island, to evaluate the feasibility and results of screening adult diabetes (DM) patients for tuberculosis (TB) and latent tuberculous infection (LTBI) using a symptom screen, tuberculin skin testing and chest radiography. Of 79 patients, 65 (82%) completed screening. Two (3%) patients with active TB and 16 (25%) with LTBI were referred for anti-tuberculosis treatment and isoniazid preventive therapy, respectively. It is feasible and worthwhile to screen diabetes patients for TB, but a number of changes are needed to improve both the screening process and the diagnostic yield.

Tuberculosis case burden and treatment outcomes in children, adults and older adults, Vanuatu, 2007-2011

SETTING

All five DOTS centres in Vanuatu.

OBJECTIVES

To determine across the age spectrum the tuberculosis (TB) case burden, disease pattern and treatment outcomes in patients registered between 2007 and 2011.

DESIGN

Retrospective cohort study involving reviews of TB registers and treatment cards.

RESULTS

Of 588 TB patients, 142 (24%) were children (aged 0-14 years), 327 (56%) adults (aged 15-54 years) and 119 (20%) were older adults (aged ⩾55 years; subdivided into 55-64 and ⩾65 years); 568 were new patients, 13 had been treated previously and 7 had unknown status. Compared with adults, children with new TB had a higher prevalence of extra-pulmonary TB (75% vs. 34%, OR 5.7, 95%CI 3.6-9.0) and a lower prevalence of smear-positive pulmonary TB (11% vs. 45%, OR 0.15, 95%CI 0.1-0.3), while older adults with new TB had a higher prevalence of smear-negative pulmonary TB (38% vs. 21%, OR 2.4, 95%CI 1.5-3.8). Overall TB treatment success was 83%, but in the second category of older adults (⩾65 years) treatment success was 67% and case fatality was 18%.

CONCLUSION

Children and older adults constitute 45% of the TB burden in Vanuatu. Differences in disease patterns and poorer treatment outcomes in older adults have implications for policy and practice.

Screening adult tuberculosis patients for diabetes mellitus in Ebeye, Republic of the Marshall Islands

A retrospective cohort study was conducted to evaluate the screening of adult TB patients for diabetes (DM) using glycated haemoglobin (HbA1C) in Ebeye, Republic of the Marshall Islands. Of 62 patients registered between July 2010 and December 2012, 28 (45%) had DM. The only significant difference in baseline characteristics between those with and those without DM was higher age in those with DM. Two-month sputum smears and cultures were also not different between the two groups. Despite the limited sample size, this study shows that screening TB patients for DM in Ebeye is feasible and worthwhile and that it should be continued.

Mentorship for operational research capacity building: hands-on or hands-off?

Mentorship is a key feature of operational research training courses run by the International Union Against Tuberculosis and Lung Disease and Médecins Sans Frontières. During the recent South Pacific paper writing module, the faculty discussed 'hands-on' mentorship (direct technical assistance) vs. 'hands-off' mentorship (technical advice). This article explores the advantages and disadvantages of each approach. Our collective experience indicates that 'hands-on' mentorship is a valuable learning experience for the participant and a rewarding experience for the mentor. This approach increases the likelihood of successful course completion, including publishing a well written paper. However, mentors must allow participants to lead and take ownership of the paper, in keeping with a first author position.

Building operational research capacity in the Pacific

Operational research (OR) in public health aims to investigate strategies, interventions, tools or knowledge that can enhance the quality, coverage, effectiveness or performance of health systems. Attention has recently been drawn to the lack of OR capacity in public health programmes throughout the Pacific Islands, despite considerable investment in implementation. This lack of ongoing and critical reflection may prevent health programme staff from understanding why programme objectives are not being fully achieved, and hinder long-term gains in public health. The International Union Against Tuberculosis and Lung Disease (The Union) has been collaborating with Pacific agencies to conduct OR courses based on the training model developed by The Union and Médecins Sans Frontières Brussels-Luxembourg in 2009. The first of these commenced in 2011 in collaboration with the Fiji National University, the Fiji Ministry of Health, the World Health Organization and other partners. The Union and the Secretariat of the Pacific Community organised a second course for participants from other Pacific Island countries and territories in 2012, and an additional course for Fijian participants commenced in 2013. Twelve participants enrolled in each of the three courses. Of the two courses completed by end 2013, 18 of 24 participants completed their OR and submitted papers by the course deadline, and 17 papers have been published to date. This article describes the context, process and outputs of the Pacific courses, as well as innovations, adaptations and challenges.

Descriptive analysis of diabetes-related amputations at the Colonial War Memorial Hospital, Fiji, 2010-2012

SETTING

The Colonial War Memorial Hospital (CWMH) in Fiji.

OBJECTIVE

To determine the characteristics of patients with diabetes mellitus (DM) who underwent lower limb amputations at the CWMH from 2010 to 2012.

DESIGN

This was a retrospective review of data contained in operating theatre registers and clinical records of DM patients who had undergone amputations during the study period.

RESULT

Of the 938 amputations performed at the CWMH during the study period, significantly more patients were male than female (54.1% vs. 45.9%) and more i-Taukei (indigenous Fijian) than Indo-Fijian (71% vs. 26.2%); 15.9% of patients had not previously been diagnosed as having DM when they presented with foot sepsis. The rate of smoking was highest in male i-Taukei patients. A large proportion of patients (76.8%) had poor glycaemic control.

CONCLUSION

This study suggests that male i-Taukeis are most at risk, and that uncontrolled DM is a significant factor associated with amputations. There is a need to strengthen DM screening and improve glycaemic control. Foot care education needs to be implemented at diagnosis and re-enforced with regular clinic visits and complication screening sessions.

Pre-treatment loss to follow-up among smear-positive pulmonary tuberculosis cases: a 10-year audit of national data from Fiji

SETTING

All tuberculosis (TB) diagnostic and treatment centres in Fiji.

OBJECTIVES

To report on pre-treatment loss to follow-up rates over a 10-year period (2001-2010) and to examine if patients' age, sex and geographic origin are associated with the observed shortcomings in the health services.

METHODS

A retrospective review of routine programme data reconciling TB laboratory and treatment registers.

RESULTS

A total of 690 sputum smear-positive TB patients were diagnosed in the laboratory, of whom 579 (84%) were started on anti-tuberculosis treatment-an overall pre-treatment loss to follow-up of 111 (16%). Peak loss to follow-up rates were seen in 2003, 2004 and 2010. Pre-treatment losses were all aged ≥15 years. In the Western Division of Fiji, 33% of sputum-positive patients were declared pre-treatment loss to follow-up; this division had over five times the risk of such an adverse outcome compared to the Central Division (OR 5.2, 95%CI 3.1-8.9, P < 0.0001).

CONCLUSION

This study has identified an important shortcoming in programme linkage, communication and feedback between TB diagnostic and treatment services, leading to high pre-treatment loss to follow-up rates. This negatively influences TB services, and ways to rectify this situation are discussed.

Describing the burden of non-communicable disease risk factors among adults with diabetes in Wallis and Futuna

BACKGROUND

The South Pacific Territory of Wallis and Futuna has a high burden of non-communicable diseases (NCD): 18% of adults have diabetes mellitus (DM) and 87% are classified as overweight or obese.

OBJECTIVE

To characterise the burden of additional World Health Organization (WHO) recognised NCD risk factors, such as smoking, obesity, high blood pressure, eating less than five fruit or vegetable servings per day and a sedentary lifestyle, among adults with DM.

DESIGN

Re-analysis of cross-sectional data from a 2009 national survey. Odds ratios (ORs) and 95% confidence intervals (CIs) were calculated.

RESULTS

Of 487 adults sampled, 87 (18%) had DM. Nearly 99% of individuals with DM had at least one additional NCD risk factor, and 62% had three or more concurrent NCD risk factors. Individuals with DM were more likely to be obese (OR 1.66, 95%CI 1.01-2.74) and had a much higher prevalence of high blood pressure (OR 3.02, 95%CI 1.87-4.86).

CONCLUSION

DM is rarely identified in the absence of other NCD risk factors. We recommend an integrated approach to the management of DM and other NCD risk factors in routine care rather than a disease-specific approach.

Consecutive magnetic and magnetocaloric transitions in herringbone nanostructured Heusler Mn50Ni41Sn9 alloy

A herringbone nanostructured Mn-rich Heusler Mn50Ni50-Sndelta (8 - 9) alloy exhibits tailored magnetocaloric properties in the martensite and ferro <-> paramagnetic transitions concur in a narrow temperature window. In a Sn --> Ni substitution 8 - 9, the martensite (M) <-- austenite (A) transition up-lifts adequately well above the room temperature - 310.5 K in the DSC thermogram and magnetization scanned with temperature. A noninterrupted heating following a cooling in DSC at a given rate gives a smaller enthalpy change deltaH(M <-- A) - deltaH(M --> A approximately equal to 282 mJ/g (deltaC(P)(M <-- A) - deltaC(P)(M --> A) approximately equal to 0.025 mJ/g-K in the heat capacity), i.e., the M <-> A transition process lacks a complete reversibility. Warming a zero-field cooled sample retains lower magnetization (sigma) at low fields B, e.g., by 58% over the field cooled value at 5 mT, wherein merely low field magnetic susceptibility imparts the magnetization process. A reversible thermal hysteresis thus the transition traces in cooling and heating. The field diminishes difference in two sigma-values progressively, e.g., only - 12% lasts at 5 T. The two curves bifurcate below 160 K (B-5 mT) and the gap grows exponentially over lower temperatures before sigma(M <-- A) gets steady near 60 K in a superparamagnetic (SPM) behavior. The SPM feature (follows the Langevin model) below a paramagnetic regime begins (> or = 250 K) before a ferromagnetic A-state lines-up the successive transitions. Temperature and frequency dependence ac and dc susceptibilities describe the surface spins dynamics.

Outpatient taping in the treatment of idiopathic congenital talipes equinovarus

The Ponseti and French taping methods have reduced the incidence of major surgery in congenital idiopathic clubfoot but incur a significant burden of care, including heel-cord tenotomy. We developed a non-operative regime to reduce treatment intensity without affecting outcome. We treated 402 primary idiopathic clubfeet in patients aged < three months who presented between September 1991 and August 2008. Their Harrold and Walker grades were 6.0% mild, 25.6% moderate and 68.4% severe. All underwent a dynamic outpatient taping regime over five weeks based on Ponseti manipulation, modified Jones strapping and home exercises. Feet with residual equinus (six feet, 1.5%) or relapse within six months (83 feet, 20.9%) underwent one to three additional tapings. Correction was maintained with below-knee splints, exercises and shoes. The clinical outcome at three years of age (385 feet, 95.8% follow-up) showed that taping alone corrected 357 feet (92.7%, 'good'). Late relapses or failure of taping required limited posterior release in 20 feet (5.2%, 'fair') or posteromedial release in eight feet (2.1%, 'poor'). The long-term (> 10 years) outcomes in 44 feet (23.8% follow-up) were assessed by the Laaveg-Ponseti method as excellent (23 feet, 52.3%), good (17 feet, 38.6%), fair (three feet, 6.8%) or poor (one foot, 2.3%). These compare favourably with published long-term results of the Ponseti or French methods. This dynamic taping regime is a simple non-operative method that delivers improved medium-term and promising long-term results.