Domain Adaptation using Silver Standard Labels for Ki-67 Scoring in Digital Pathology: A Step Closer to Widescale Deployment

Deep learning systems have been proposed to improve the objectivity and efficiency of Ki- 67 PI scoring. The challenge is that while very accurate, deep learning techniques suffer from reduced performance when applied to out-of-domain data. This is a critical challenge for clinical translation, as models are typically trained using data available to the vendor, which is not from the target domain. To address this challenge, this study proposes a domain adaptation pipeline that employs an unsupervised framework to generate silver standard (pseudo) labels in the target domain, which is used to augment the gold standard (GS) source domain data. Five training regimes were tested on two validated Ki-67 scoring architectures (UV-Net and piNET), (1) SS Only: trained on target silver standard (SS) labels, (2) GS Only: trained on source GS labels, (3) Mixed: trained on target SS and source GS labels, (4) GS+SS: trained on source GS labels and fine-tuned on target SS labels, and our proposed method (5) SS+GS: trained on source SS labels and fine-tuned on source GS labels. The SS+GS method yielded significantly (p < 0.05) higher PI accuracy (95.9%) and more consistent results compared to the GS Only model on target data. Analysis of t-SNE plots showed features learned by the SS+GS models are more aligned for source and target data, resulting in improved generalization. The proposed pipeline provides an efficient method for learning the target distribution without manual annotations, which are time-consuming and costly to generate for medical images. This framework can be applied to any target site as a per-laboratory calibration method, for widescale deployment.Comment: Editors: Accepted for publication at MIDL 202

Heterogeneity of circulating tumour cell-associated genomic gains in breast cancer and its association with the host immune response.

Tumor cells that preferentially enter circulation include the precursors of metastatic cancer. Previously, we characterized circulating tumor cells (CTC) from patients with breast cancer and identified a signature of genomic regions with recurrent copy-number gains. Through FISH, we now show that these CTC-associated regions are detected within the matched untreated primary tumors of these patients (21% to 69%, median 55.5%, n = 19). Furthermore, they are more prevalent in the metastases of patients who died from breast cancer after multiple rounds of treatment (70% to 100%, median 93%, samples n = 41). Diversity indices revealed that higher spatial heterogeneity for these regions within primary tumors is associated with increased dissemination and metastasis. An identified subclone with multiple regions gained (MRG clone) was enriched in a posttreatment primary breast carcinoma as well as multiple metastatic tumors and local breast recurrences obtained at autopsy, indicative of a distinct early subclone with the capability to resist multiple lines of treatment and eventually cause death. In addition, multiplex immunofluorescence revealed that tumor heterogeneity is significantly associated with the degree of infiltration of B lymphocytes in triple-negative breast cancer, a subtype with a large immune component. Collectively, these data reveal the functional potential of genetic subclones that comprise heterogeneous primary breast carcinomas and are selected for in CTCs and posttreatment breast cancer metastases. In addition, they uncover a relationship between tumor heterogeneity and host immune response in the tumor microenvironment. SIGNIFICANCE: As breast cancers progress, they become more heterogeneous for multiple regions amplified in circulating tumor cells, and intratumoral spatial heterogeneity is associated with the immune landscape

A dual-process psychobiological model of temperament predicts liking and wanting for food and trait disinhibition

A dual-process model of temperament, incorporating the Behavioural Inhibition System (BIS), Behavioural Activation System (BAS) and effortful control (EC), may help to predict hedonic responses to palatable food and trait disinhibition. Purpose This study aimed to determine if the BIS, BAS and EC predicted liking and wanting for high-fat, sweet foods in adults with overweight and obesity, and if collectively, these variables predicted the eating behaviour trait of Disinhibition. Methods 168 adults (104 females, mean BMI = 33.3 kg/m2) completed the Three Factor Eating Questionnaire, the Carver and White BIS/BAS scales, the Adult Temperament Questionnaire-Effortful Control Scale – Short Form and the Leeds Food Preference Questionnaire. The strength of the BIS, BAS and EC in predicting wanting and liking for high-fat sweet foods, and trait Disinhibition was assessed using hierarchical multiple regression. Results Both the BIS and EC predicted liking, F (6, 161) = 5.05, p < .001, R2 = 0.16, and EC inversely predicted wanting, F (6, 161) = 3.28, p = .005, R2 = 0.11. The BIS, EC and liking predicted, F (8, 159) = 11.0, p < .001, R2 = 0.36, and explained 36% of Disinhibition. The BAS did not predict wanting, liking or Disinhibition. Conclusions These results demonstrate that a sensitive BIS and a lower level of effortful control predicts food reward and Disinhibition in overweight and obese adults. Consequently, interventions that aim to increase effortful control and reduce BIS reactivity may be beneficial for reducing hedonically motivated, disinhibited eating behaviour

A review of Australian Government funding of parenting intervention research

Objectives: Parenting is central to children's optimal development and accounts for a substantial proportion of the variance in child outcomes, including up to 40% of child mental health. Parenting is also one of the most modifiable, proximal, and direct factors for preventing and treating a range of children's problems and enhancing wellbeing. To determine the effectiveness of new approaches to parenting intervention, and to evaluate how to optimise reach and uptake, sufficient funding must be allocated for high quality research. Method: We reviewed funding awarded by the National Health and Medical Research Council (NHMRC) and Australian Research Council (ARC) for parenting intervention research during 2011–2020. Results: Parenting intervention research received 0.25% of the NHMRC and ARC research budgets. Conclusions: There is a substantial mismatch between the funding of parenting intervention research and the impact of improved parenting on short‐ and long‐term child outcomes. To rectify this, it is critical that Australian Government funding schemes include parenting interventions as priority areas for funding. Implications for public health: Changes in allocation of funding to parenting research will support the establishment of evidence for the effective development, implementation and dissemination of parenting interventions to maximise health outcomes for children and their families