Christobel Saunders

We present a wireless and handheld optical elastography probe aimed toward improving intraoperative discrimination between malignant and benign tissue in breast-conserving surgery. If successful, this probe can contribute to reducing close or positive margins and, therefore, subsequent re-excisions. The probe visualizes mechanical contrast between tumor and surrounding benign tissue in excised human breast specimens using stereoscopic optical palpation, in which the deformation of a compliant silicone layer is measured by two parallel cameras to infer surface stress, where variations in stress correspond to differences in the mechanical properties of the underlying tissue. Wireless operation is achieved using a Wi-Fi transceiver to transmit images at 15 fps to a laptop for processing. To enhance image quality, we incorporate computational optical palpation, which utilizes finite element analysis to provide a more accurate mechanical model of the deformation of the compliant layer. This approach yields a twofold improvement in spatial resolution, from 1034 to 512 μm, and a 55% increase in stress contrast in a structured silicone phantom. In a preliminary study on four excised human breast tissue samples, we demonstrate that the probe can identify tumor and distinguish between benign tissue types, including adipose tissue, stroma, and potentially ducts.

Despite Advances, Re-Excision Rates Persist: A 25-Year National Analysis of Breast-Conserving Surgery in AustraliaAbstractBackgroundRe-excision following breast-conserving surgery (BCS) remains a key indicator of surgical quality. Although adoption of the 2014 SSO–ASTRO “no tumour on ink” margin guideline, advances in imaging and oncoplastic techniques were expected to substantially reduce re-excision, national trends in Australia have not been well studied.MethodsWe performed a retrospective population-based analysis using publicly available Medicare Benefits Schedule (MBS) procedural data from 2000–2024. Initial BCS procedures (MBS 31512 and, from 2023, 31513–31514) were used as denominators and re-excisions (MBS 31515) as numerators to calculate annual and state-based re-excision proportions. Demographic variation was assessed by age group and jurisdiction. Health-system costs were estimated using 2024–25 National Weighted Activity Unit pricing.ResultsOver 25 years, 171,715 BCS procedures and 31,987 re-excisions were recorded, yielding a national re-excision proportion of 18.6%. Following publication of the SSO–ASTRO guideline, re-excisions decreased modestly from 19.5% (2003–2013) to 18.1% (2014–2024; p <0.001) but remained persistently high. Younger patients exhibited higher re-excision proportions, while substantial geographic variation was observed across states and territories (range 12.1%–24.1%). Mastectomy volumes stabilised over time while BCS volumes continued to rise, indicating that the persistence of re-excision rates is not explained by completion mastectomy. System-level costs attributable to re-excision exceeded AUD $12 million in 2024 alone.

Menopausal symptoms are common in cancer survivors, often affecting their daily lives. Despite available treatments, few have access to adequate symptom management. Novel approaches, such as those incorporating symptom assessment and tailored or stepped approaches, are needed. This study explored perceived enablers and barriers to using an online patient-driven stepped-care platform to screen for and manage menopausal symptoms. Women with a history of cancer were invited through partner organisations by email or social media. Participants completed semi-structured interview based on a theoretical domain framework and the capability, opportunity, and motivation-behavior model. Transcripts were coded into the 14 theoretical domains. Belief statements were analysed into themes and categorised as enablers or barriers. Twenty participants (aged 30–75) were interviewed. Most were Australian-born ( n = 18), held vocational training or bachelor’s degree ( n = 12), and were employed ( n = 11). The most common cancer experienced was breast ( n = 6), most had received chemotherapy ( n = 16), were pre-menopausal before treatment ( n = 13) and reported hot flushes or vaginal dryness ( n = 14 each). Twenty-eight themes were identified. Enablers included high confidence in using mobile technologies, a user-friendly platform, and their role as “cancer survivor” to self-manage symptoms. Barriers included low awareness of the stepped-care concept, patient-related comorbidities, and time constraints. The platform’s concept was viewed positively and as important, with high intention to use and follow recommended pathways. This study provides insights into factors that could influence survivors’ engagement with the platform. Findings will guide the prototype development.

Background: The status of the axilla remains a significant prognostic factor and influences adjuvant systemic and locoregional treatment choices in early-stage breast cancer (EBC). Sentinel node (SN) biopsy continues to be the preferred technique for establishing axillary nodal status in clinically node-negative EBC. A multivariable prediction model with adequate accuracy and generalizability has been explored as a potential alternative to SN. Objective: This systematic review aims to evaluate the predictive performance, methodological quality, and risk of bias associated with the available mathematical models (MMs), excluding artificial intelligence (AI)–based models, for predicting SN status in patients with EBC. Methods: A systematic search will be conducted across PubMed, Cochrane CENTRAL, and Embase to identify studies reporting the development of an SN status prediction model. Only studies that report SN status using mathematical modeling techniques will be included. Two independent reviewers will screen the search results and extract data from the included articles. The primary outcome of this systematic review is to evaluate the methodological adequacy and generalizability of individual MMs and compare the reported predictive performances of methodologically robust MMs. The secondary objective is to identify key predictive factors contributing to SN status prediction in MMs. A narrative synthesis of all the included studies will be undertaken. The details of this protocol are accessible on PROSPERO, where it was registered on January 23, 2025. Ethics approval is not required for this study because only published data will be analyzed. Results: Funding for this review was obtained in 2022. The literature search was completed on December 15, 2023, and screening began in December 2023. Data extraction and assessment using the Prediction Model Risk of Bias Assessment Tool was completed by December 2025, with synthesis planned for March 2026. Of the 3458 screened records, 122 (3.5%) were selected for data extraction. Results will be prepared for submission for a peer review and publication in mid-2026. Conclusions: This review will provide a consolidated evaluation of non–machine learning MMs for predicting SN status in EBC. By clarifying the predictive performance and methodological quality of traditional statistical approaches, the findings will serve as a benchmark against which emerging AI-based tools can be compared. This review is also expected to identify predictors that consistently contribute to accurate modeling, informing the development of future statistical and AI-enhanced prediction tools. Trial Registration: PROSPERO CRD42025637632; https://www.crd.york.ac.uk/PROSPERO/view/CRD42025637632 International Registered Report Identifier (IRRID): DERR1-10.2196/82523

Objectives: To understand whether and how breast magnetic resonance imaging (MRI) at cancer diagnosis influences treatment planning, and whether subpopulations of patients with newly diagnosed breast cancer benefit in terms of most appropriate management. Design: Multicentre prospective observational study. Setting: Seven centres across New South Wales, Victoria and Western Australia during the period 15 September 2020 to 14 July 2022. Participants: Patients with newly diagnosed early breast cancer meeting predefined criteria for whom multidisciplinary team normal practice deemed MRI would aid treatment planning. Intervention: Preoperative contrast‐enhanced MRI. Main outcome measures: Reasons for requesting MRI; pre‐MRI versus post‐MRI changes in treatment plans; changes justified by pathology findings. Results: 387 eligible participants were enrolled. MRI was most frequently requested for dense breasts (252 [65%]), clinical and/or radiological size discrepancy (161 [42%]), multifocality (108 [28%]) and young age (105 [27%]). Change in treatment plan after MRI occurred for 198 participants (51% [95% CI, 46–56%]), including a change in breast surgery plan for 119 participants (31% [95% CI, 26–36%]). More mastectomies were planned after MRI (15% v 28%; absolute risk difference [RD], 13 percentage points [95% CI, 9–17]; P < 0.001), including unilateral mastectomy (14% v 24%; RD, 10 percentage points [95% CI, 6–14]; P < 0.001) and bilateral mastectomy (1% v 4%; RD, 3 percentage points [95% CI, 1–5]; P < 0.001). No increases in planned mastectomies occurred for women aged ≥ 70 years (RD, –3 percentage points [95% CI, –15 to 9]; or in those for whom neoadjuvant therapy was planned (RD, 2 percentage points [95% CI, –11 to 14]). Change in surgery was deemed justified by pathology findings in 75 of 88 women who experienced a change (85% [95% CI, 75–91%]). Conclusions: Preoperative MRI findings led to changes in surgical management for a third of selected women with early breast cancer, increasing the mastectomy rate. In most cases, the changes were deemed appropriate. MRI findings did not change planned mastectomy in those aged ≥ 70 years, indicating that these women may not experience changes in surgical plans after such testing.

PURPOSE: We investigated breastfeeding patterns, behaviors, and association with breast cancer (BC) outcomes in women with early hormone receptor–positive (HR+) BC who had a live birth in the POSITIVE trial. PATIENTS AND METHODS: POSITIVE is a prospective trial that demonstrated no increased short-term risk of BC events in women with early HR+ BC who interrupted endocrine therapy (ET) to attempt pregnancy. We describe the frequency, duration, and laterality of breastfeeding and estimate the cumulative incidence of BC events by breastfeeding status. RESULTS: At a median follow-up of 41 months, 317 patients had at least one live birth and 313 were eligible for this analysis. A total of 196 of 313 (62.6%) patients breastfed. A total of 130 of the 167 women (77.8%) who had breast-conserving surgery breastfed, and 90 of 130 (69.2%) breastfed from the unaffected breast only. Sixty-six of the 146 women (45.2%) who underwent unilateral mastectomy breastfed. The frequency of breastfeeding was higher in women older than 35 years (67.6% v 55.7%) and in those without previous children (66.4% v 48.5%). Over half (103 of 196, 52.6%) of women breastfed their first live birth for >4 months (median 4.4 months; 95% CI, 4.0 to 5.3). The cumulative incidence of a BC event at 24 months from first on-study live birth was 3.6% and 3.1% in the breastfeeding and nonbreastfeeding groups, respectively (0.5% difference; 95% CI, –4.3% to 5.2%). CONCLUSION: In POSITIVE, two thirds of women who gave birth after BC diagnosis breastfed, mostly for 4 months or more. In early follow-up, we did not observe differences in BC-related events in women who breastfed compared with those who did not. These results are key for women who wish to pursue pregnancy and breastfeeding after BC.

BACKGROUND The status of the axilla remains a significant prognostic factor and influences adjuvant systemic and locoregional treatment choices in early-stage breast cancer (EBC). Sentinel node (SN) biopsy continues to be the preferred technique for establishing axillary nodal status in clinically node-negative EBC. A multivariable prediction model with adequate accuracy and generalizability has been explored as a potential alternative to SN. OBJECTIVE This systematic review aims to evaluate the predictive performance, methodological quality, and risk of bias associated with the available mathematical models (MMs), excluding artificial intelligence (AI)–based models, for predicting SN status in patients with EBC. METHODS A systematic search will be conducted across PubMed, Cochrane CENTRAL, and Embase to identify studies reporting the development of an SN status prediction model. Only studies that report SN status using mathematical modeling techniques will be included. Two independent reviewers will screen the search results and extract data from the included articles. The primary outcome of this systematic review is to evaluate the methodological adequacy and generalizability of individual MMs and compare the reported predictive performances of methodologically robust MMs. The secondary objective is to identify key predictive factors contributing to SN status prediction in MMs. A narrative synthesis of all the included studies will be undertaken. The details of this protocol are accessible on PROSPERO, where it was registered on January 23, 2025. Ethics approval is not required for this study because only published data will be analyzed. RESULTS Funding for this review was obtained in 2022. The literature search was completed on December 15, 2023, and screening began in December 2023. Data extraction and assessment using the Prediction Model Risk of Bias Assessment Tool was completed by December 2025, with synthesis planned for March 2026. Of the 3458 screened records, 122 (3.5%) were selected for data extraction. Results will be prepared for submission for a peer review and publication in mid-2026. CONCLUSIONS This review will provide a consolidated evaluation of non–machine learning MMs for predicting SN status in EBC. By clarifying the predictive performance and methodological quality of traditional statistical approaches, the findings will serve as a benchmark against which emerging AI-based tools can be compared. This review is also expected to identify predictors that consistently contribute to accurate modeling, informing the development of future statistical and AI-enhanced prediction tools. CLINICALTRIAL PROSPERO CRD42025637632; https://www.crd.york.ac.uk/PROSPERO/view/CRD42025637632 INTERNATIONAL REGISTERED REPORT DERR1-10.2196/82523

Background: Design and delivery of specific palliative care in many lower middle-income countries such as Bhutan remains limited. Designing care programmes to respond to the needs of patients and family networks is essential, but evidence on these preferences is limited. Aim: We have conducted a discrete choice experiment on Bhutanese patients and family members to explore preferences for palliative care. Design: The discrete choice experiment consisted of 15 choice tasks in which each respondent considered two competing palliative care services. Data were collected through the recruitment of respondents in conjunction with the clinician support teams, with data collected from both patients and their family members. All responses were pooled across the groups and analysed using the conditional logit regression model. Setting/participants: Fifty-seven respondents (20 patients and 37 family members) out of 98 (50 patients and 48 family members) identified (58.2%) were recruited through the three large referral hospitals in Bhutan. Patients had to be diagnosed with an advanced illness or at the end-of-life phase, but be able to understand and be willing to complete the survey. Similarly, family members had to be willing and able to complete the survey, and to be defined as the primary caregiver by the patient. Results: Transparent information provision, cost, family training and use of traditional healing practices were keen drivers of choice, with location of care and place of death relatively less important. Conclusion: Our results will guide future service design decisions in Bhutan and demonstrate the need for localised preference studies to enable culturally appropriate care including the provision of traditional healing practices.