Optimising the diagnostic accuracy of First post-contrAst SubtracTed breast MRI (FAST MRI) through interpretation-training: a multicentre e-learning study, mapping the learning curve of NHS Breast Screening Programme (NHSBSP) mammogram readers using an enriched dataset.

BACKGROUND: Abbreviated breast MRI (FAST MRI) is being introduced into clinical practice to screen women with mammographically dense breasts or with a personal history of breast cancer. This study aimed to optimise diagnostic accuracy through the adaptation of interpretation-training. METHODS: A FAST MRI interpretation-training programme (short presentations and guided hands-on workstation teaching) was adapted to provide additional training during the assessment task (interpretation of an enriched dataset of 125 FAST MRI scans) by giving readers feedback about the true outcome of each scan immediately after each scan was interpreted (formative assessment). Reader interaction with the FAST MRI scans used developed software (RiViewer) that recorded reader opinions and reading times for each scan. The training programme was additionally adapted for remote e-learning delivery. STUDY DESIGN: Prospective, blinded interpretation of an enriched dataset by multiple readers. RESULTS: 43 mammogram readers completed the training, 22 who interpreted breast MRI in their clinical role (Group 1) and 21 who did not (Group 2). Overall sensitivity was 83% (95%CI 81-84%; 1994/2408), specificity 94% (95%CI 93-94%; 7806/8338), readers' agreement with the true outcome kappa = 0.75 (95%CI 0.74-0.77) and diagnostic odds ratio = 70.67 (95%CI 61.59-81.09). Group 1 readers showed similar sensitivity (84%) to Group 2 (82% p = 0.14), but slightly higher specificity (94% v. 93%, p = 0.001). Concordance with the ground truth increased significantly with the number of FAST MRI scans read through the formative assessment task (p = 0.002) but by differing amounts depending on whether or not a reader had previously attended FAST MRI training (interaction p = 0.02). Concordance with the ground truth was significantly associated with reading batch size (p = 0.02), tending to worsen when more than 50 scans were read per batch. Group 1 took a median of 56 seconds (range 8-47,466) to interpret each FAST MRI scan compared with 78 (14-22,830, p < 0.0001) for Group 2. CONCLUSIONS: Provision of immediate feedback to mammogram readers during the assessment test set reading task increased specificity for FAST MRI interpretation and achieved high diagnostic accuracy. Optimal reading-batch size for FAST MRI was 50 reads per batch. Trial registration (25/09/2019): ISRCTN16624917.

Predicting the response to neoadjuvant chemotherapy. Can the addition of tomosynthesis improve the accuracy of contrast-enhanced spectral mammography? A comparison with breast MRI.

OBJECTIVES: Image monitoring is essential to monitor response to neoadjuvant chemotherapy (NACT). Whilst breast MRI is the gold-standard technique, evidence suggests contrast-enhanced spectral mammography (CESM) is comparable. We investigate whether the addition of digital breast tomosynthesis (DBT) to CESM increases the accuracy of response prediction. METHODS: Women receiving NACT for breast cancer were included. Imaging with CESM+DBT and MRI was performed post-NACT. Imaging appearance was compared with pathological specimens. Accuracy for predicting pathological complete response (pCR) and concordance with size of residual disease was calculated. RESULTS: Sixteen cancers in 14 patients were included, 10 demonstrated pCR. Greatest accuracy for predicting pCR was with CESM enhancement (accuracy: 81.3%, sensitivity: 100%, specificity: 57.1%), followed by MRI (accuracy: 62.5%, sensitivity: 44.4%, specificity: 85.7%). Concordance with invasive tumour size was greater for CESM enhancement than MRI, concordance-coefficients 0.70 vs 0.66 respectively. MRI demonstrated greatest concordance with whole tumour size followed by CESM+microcalcification, concordance coefficients 0.86 vs 0.69. DBT did not improve accuracy for prediction of pCR or residual disease size. CESM+DBT underestimated size of residual disease, MRI overestimated but no significant differences were seen (p>0.05). CONCLUSIONS: CESM is similar to MRI for predicting residual disease post-NACT. Size of enhancement alone demonstrates best concordance with invasive disease. Inclusion of residual microcalcification improves concordance with ductal carcinoma in situ. The addition of DBT to CESM does not improve accuracy. ADVANCES IN KNOWLEDGE: The addition ofDBT to CESM does not improve NACT response prediction. CESM enhancement has greatest accuracy for residual invasive disease, CESM+calcification has greater accuracy for residual in situ disease.

Development and Evaluation of Machine Learning in Whole-Body Magnetic Resonance Imaging for Detecting Metastases in Patients With Lung or Colon Cancer: A Diagnostic Test Accuracy Study.

OBJECTIVES: Whole-body magnetic resonance imaging (WB-MRI) has been demonstrated to be efficient and cost-effective for cancer staging. The study aim was to develop a machine learning (ML) algorithm to improve radiologists' sensitivity and specificity for metastasis detection and reduce reading times. MATERIALS AND METHODS: A retrospective analysis of 438 prospectively collected WB-MRI scans from multicenter Streamline studies (February 2013-September 2016) was undertaken. Disease sites were manually labeled using Streamline reference standard. Whole-body MRI scans were randomly allocated to training and testing sets. A model for malignant lesion detection was developed based on convolutional neural networks and a 2-stage training strategy. The final algorithm generated lesion probability heat maps. Using a concurrent reader paradigm, 25 radiologists (18 experienced, 7 inexperienced in WB-/MRI) were randomly allocated WB-MRI scans with or without ML support to detect malignant lesions over 2 or 3 reading rounds. Reads were undertaken in the setting of a diagnostic radiology reading room between November 2019 and March 2020. Reading times were recorded by a scribe. Prespecified analysis included sensitivity, specificity, interobserver agreement, and reading time of radiology readers to detect metastases with or without ML support. Reader performance for detection of the primary tumor was also evaluated. RESULTS: Four hundred thirty-three evaluable WB-MRI scans were allocated to algorithm training (245) or radiology testing (50 patients with metastases, from primary 117 colon [n = 117] or lung [n = 71] cancer). Among a total 562 reads by experienced radiologists over 2 reading rounds, per-patient specificity was 86.2% (ML) and 87.7% (non-ML) (-1.5% difference; 95% confidence interval [CI], -6.4%, 3.5%; P = 0.39). Sensitivity was 66.0% (ML) and 70.0% (non-ML) (-4.0% difference; 95% CI, -13.5%, 5.5%; P = 0.344). Among 161 reads by inexperienced readers, per-patient specificity in both groups was 76.3% (0% difference; 95% CI, -15.0%, 15.0%; P = 0.613), with sensitivity of 73.3% (ML) and 60.0% (non-ML) (13.3% difference; 95% CI, -7.9%, 34.5%; P = 0.313). Per-site specificity was high (>90%) for all metastatic sites and experience levels. There was high sensitivity for the detection of primary tumors (lung cancer detection rate of 98.6% with and without ML [0.0% difference; 95% CI, -2.0%, 2.0%; P = 1.00], colon cancer detection rate of 89.0% with and 90.6% without ML [-1.7% difference; 95% CI, -5.6%, 2.2%; P = 0.65]). When combining all reads from rounds 1 and 2, reading times fell by 6.2% (95% CI, -22.8%, 10.0%) when using ML. Round 2 read-times fell by 32% (95% CI, 20.8%, 42.8%) compared with round 1. Within round 2, there was a significant decrease in read-time when using ML support, estimated as 286 seconds (or 11%) quicker ( P = 0.0281), using regression analysis to account for reader experience, read round, and tumor type. Interobserver variance suggests moderate agreement, Cohen κ = 0.64; 95% CI, 0.47, 0.81 (with ML), and Cohen κ = 0.66; 95% CI, 0.47, 0.81 (without ML). CONCLUSIONS: There was no evidence of a significant difference in per-patient sensitivity and specificity for detecting metastases or the primary tumor using concurrent ML compared with standard WB-MRI. Radiology read-times with or without ML support fell for round 2 reads compared with round 1, suggesting that readers familiarized themselves with the study reading method. During the second reading round, there was a significant reduction in reading time when using ML support.

The association of age at menarche and adult height with mammographic density in the International Consortium of Mammographic Density.

BACKGROUND: Early age at menarche and tall stature are associated with increased breast cancer risk. We examined whether these associations were also positively associated with mammographic density, a strong marker of breast cancer risk. METHODS: Participants were 10,681 breast-cancer-free women from 22 countries in the International Consortium of Mammographic Density, each with centrally assessed mammographic density and a common set of epidemiologic data. Study periods for the 27 studies ranged from 1987 to 2014. Multi-level linear regression models estimated changes in square-root per cent density (√PD) and dense area (√DA) associated with age at menarche and adult height in pooled analyses and population-specific meta-analyses. Models were adjusted for age at mammogram, body mass index, menopausal status, hormone therapy use, mammography view and type, mammographic density assessor, parity and height/age at menarche. RESULTS: In pooled analyses, later age at menarche was associated with higher per cent density (ß√PD = 0.023 SE = 0.008, P = 0.003) and larger dense area (ß√DA = 0.032 SE = 0.010, P = 0.002). Taller women had larger dense area (ß√DA = 0.069 SE = 0.028, P = 0.012) and higher per cent density (ß√PD = 0.044, SE = 0.023, P = 0.054), although the observed effect on per cent density depended upon the adjustment used for body size. Similar overall effect estimates were observed in meta-analyses across population groups. CONCLUSIONS: In one of the largest international studies to date, later age at menarche was positively associated with mammographic density. This is in contrast to its association with breast cancer risk, providing little evidence of mediation. Increased height was also positively associated with mammographic density, particularly dense area. These results suggest a complex relationship between growth and development, mammographic density and breast cancer risk. Future studies should evaluate the potential mediation of the breast cancer effects of taller stature through absolute breast density.

Evaluating the effectiveness of abbreviated breast MRI (abMRI) interpretation training for mammogram readers: a multi-centre study assessing diagnostic performance, using an enriched dataset.

BACKGROUND: Abbreviated breast MRI (abMRI) is being introduced in breast screening trials and clinical practice, particularly for women with dense breasts. Upscaling abMRI provision requires the workforce of mammogram readers to learn to effectively interpret abMRI. The purpose of this study was to examine the diagnostic accuracy of mammogram readers to interpret abMRI after a single day of standardised small-group training and to compare diagnostic performance of mammogram readers experienced in full-protocol breast MRI (fpMRI) interpretation (Group 1) with that of those without fpMRI interpretation experience (Group 2). METHODS: Mammogram readers were recruited from six NHS Breast Screening Programme sites. Small-group hands-on workstation training was provided, with subsequent prospective, independent, blinded interpretation of an enriched dataset with known outcome. A simplified form of abMRI (first post-contrast subtracted images (FAST MRI), displayed as maximum-intensity projection (MIP) and subtracted slice stack) was used. Per-breast and per-lesion diagnostic accuracy analysis was undertaken, with comparison across groups, and double-reading simulation of a consecutive screening subset. RESULTS: 37 readers (Group 1: 17, Group 2: 20) completed the reading task of 125 scans (250 breasts) (total = 9250 reads). Overall sensitivity was 86% (95% confidence interval (CI) 84-87%; 1776/2072) and specificity 86% (95%CI 85-86%; 6140/7178). Group 1 showed significantly higher sensitivity (843/952; 89%; 95%CI 86-91%) and higher specificity (2957/3298; 90%; 95%CI 89-91%) than Group 2 (sensitivity = 83%; 95%CI 81-85% (933/1120) p < 0.0001; specificity = 82%; 95%CI 81-83% (3183/3880) p < 0.0001). Inter-reader agreement was higher for Group 1 (kappa = 0.73; 95%CI 0.68-0.79) than for Group 2 (kappa = 0.51; 95%CI 0.45-0.56). Specificity improved for Group 2, from the first 55 cases (81%) to the remaining 70 (83%) (p = 0.02) but not for Group 1 (90-89% p = 0.44), whereas sensitivity remained consistent for both Group 1 (88-89%) and Group 2 (83-84%). CONCLUSIONS: Single-day abMRI interpretation training for mammogram readers achieved an overall diagnostic performance within benchmarks published for fpMRI but was insufficient for diagnostic accuracy of mammogram readers new to breast MRI to match that of experienced fpMRI readers. Novice MRI reader performance improved during the reading task, suggesting that additional training could further narrow this performance gap.

Contrast-enhanced digital breast tomosythesis and breast MRI to monitor response to neoadjuvant chemotherapy: patient tolerance and preference.

OBJECTIVE: Contrast-enhanced digital breast tomosynthesis (CE-DBT) is a novel imaging technique, combining contrast-enhanced spectral mammography and tomosynthesis. This may offer an alternative imaging technique to breast MRI for monitoring of response to neoadjuvant chemotherapy. This paper addresses patient experience and preference regarding the two techniques. METHODS: Conducted as part of a prospective pilot study; patients were asked to complete questionnaires pertaining to their experience of CE-DBT and MRI following pre-treatment and end-of-treatment imaging. Questionnaires consisted of eight questions answered on a categorical scale, two using a visual analogue scale (VAS), and a question to indicate preference of imaging technique. Statistical analysis was performed with Wilcoxon signed rank test and McNemar test for related samples using SPSS v. 25. RESULTS: 18 patients were enrolled in the pilot study. Matched CE-DBT and MRI questionnaires were completed after 22 patient episodes. Patient preference was indicated after 31 patient episodes. Overall, on 77% of occasions patients preferred CE-DBT with no difference between pre-treatment and end-of-treatment imaging. Overall experience (p = 0.008), non-breast pain (p = 0.046), anxiety measured using VAS (p = 0.003), and feeling of being put at ease by staff (p = 0.023) was better for CE-DBT. However, more breast pain was experienced during CE-DBT when measured on both VAS (p = 0.011) and categorical scale (p = 0.021). CONCLUSION: Our paper suggests that patients prefer CE-DBT to MRI, adding further evidence in favour of contrast-enhanced mammographic techniques. ADVANCES IN KNOWLEDGE: Contrast mammographic techniques offer an alternative, more accessible imaging technique to breast MRI. Whilst other studies have addressed patient experience of contrast-enhanced spectral mammography, this is the first study to directly explore patient preference for CE-DBT over MRI in the setting of neoadjuvant chemotherapy, finding that overall, patients preferred CE-DBT despite the relatively long breast compression.

Fair shares: building and benefiting from healthcare AI with mutually beneficial structures and development partnerships.

Artificial intelligence (AI) algorithms are used in an increasing range of aspects of our lives. In particular, medical applications of AI are being developed and deployed, including many in image analysis. Deep learning methods, which have recently proved successful in image classification, rely on large volumes of clinical data generated by healthcare institutions. Such data is collected from their served populations. In this opinion article, using digital mammographic screening as an example, we briefly consider the background to AI development and some issues around its deployment. We highlight the importance of high quality clinical data as fundamental to these technologies, and question how the ownership of resultant tools should be defined. Though many of the ethical issues concerning the development and use of medical AI technologies continue to be discussed, the value of the data on which they rely remains a subject that is seldom considered. This potentially controversial issue can and should be addressed in a way which is beneficial to all parties, particularly the population in general and the patients we serve.

Digital breast tomosynthesis: sensitivity for cancer in younger symptomatic women.

OBJECTIVE: Full-field digital mammography (FFDM) has limited sensitivity for cancer in younger women with denser breasts. Digital breast tomosynthesis (DBT) can reduce the risk of cancer being obscured by overlying tissue. The primary study aim was to compare the sensitivity of FFDM, DBT and FFDM-plus-DBT in women under 60 years old with clinical suspicion of breast cancer. METHODS: This multicentre study recruited 446 patients from UK breast clinics. Participants underwent both standard FFDM and DBT. A blinded retrospective multireader study involving 12 readers and 300 mammograms (152 malignant and 148 benign cases) was conducted. RESULTS: Sensitivity for cancer was 86.6% with FFDM [95% CI (85.2-88.0%)], 89.1% with DBT [95% CI (88.2-90%)], and 91.7% with FFDM+DBT [95% CI (90.7-92.6%)]. In the densest breasts, the maximum sensitivity increment with FFDM +DBT over FFDM alone was 10.3%, varying by density measurement method. Overall specificity was 81.4% with FFDM [95% CI (80.5-82.3%)], 84.6% with DBT [95% CI (83.9-85.3%)], and 79.6% with FFDM +DBT [95% CI (79.0-80.2%)]. No differences were detected in accuracy of tumour measurement in unifocal cases. CONCLUSIONS: Where available, DBT merits first-line use in the under 60 age group in symptomatic breast clinics, particularly in women known to have very dense breasts. ADVANCES IN KNOWLEDGE: This study is one of very few to address the accuracy of DBT in symptomatic rather than screening patients. It quantifies the diagnostic gains of DBT in direct comparison with standard digital mammography, supporting informed decisions on appropriate use of DBT in this population.

Determining patient abdomen thickness from a single digital radiograph with a computational model: clinical results from a proof of concept study.

OBJECTIVE: A computational model has been created to estimate the abdominal thickness of a patient following an X-ray examination; its intended application is assisting with patient dose audit of paediatric X-ray examinations. This work evaluates the accuracy of the computational model in a clinical setting for adult patients undergoing anteroposterior (AP) abdomen X-ray examinations. METHODS: The model estimates patient thickness using the radiographic image, the exposure factors with which the image was acquired, a priori knowledge of the characteristics of the X-ray unit and detector and the results of extensive Monte Carlo simulation of patient examinations. For 20 patients undergoing AP abdominal X-ray examinations, the model was used to estimate the patient thickness; these estimates were compared against a direct measurement made at the time of the examination. RESULTS: Estimates of patient thickness made using the model were on average within ±5.8% of the measured thickness. CONCLUSION: The model can be used to accurately estimate the thickness of a patient undergoing an AP abdominal X-ray examination where the patient's size falls within the range of the size of patients used to create the computational model. ADVANCES IN KNOWLEDGE: This work demonstrates that it is possible to accurately estimate the AP abdominal thickness of an adult patient using the digital X-ray image and a computational model.

Breast MRI and tumour biology predict axillary lymph node response to neoadjuvant chemotherapy for breast cancer.

BACKGROUND: In patients who have had axillary nodal metastasis diagnosed prior to neoadjuvant chemotherapy for breast cancer, there is little consensus on how to manage the axilla subsequently. The aim of this study was to explore whether a combination of breast magnetic resonance imaging (MRI) assessed response and primary tumour pathology factors could identify a subset of patients that might be spared axillary node clearance. METHODS: A retrospective data analysis was performed of patients with core biopsy-proven axillary nodal metastasis prior to commencement of neoadjuvant chemotherapy (NAC) who had subsequent axillary node clearance (ANC) at definitive breast surgery. Breast tumour and axillary response at MRI before, during and on completion of NAC, core biopsy tumour grade, tumour type and immunophenotype were correlated with pathological response in the breast and the number of metastatic nodes in the ANC specimens. RESULTS: Of 87 consecutive patients with MRI at baseline, interim and after neoadjuvant chemotherapy who underwent ANC at time of breast surgery, 33 (38%) had no residual macrometastatic axillary disease, 28 (32%) had 1-2 metastatic nodes and 26 (30%) had more than 2 metastatic nodes. Factors that predicted axillary nodal complete response were MRI complete response in the breast (p < 0.0001), HER2 positivity (p = 0.02) and non-lobular tumour type (p = 0.015). CONCLUSION: MRI assessment of breast tumour response to NAC and core biopsy factors are predictive of response in axillary nodes, and can be used to guide decision making regarding appropriate axillary surgery.

Are baseline ultrasound and mammographic features associated with rates of pathological completes response in patients receiving neoadjuvant chemotherapy for breast cancer?

BACKGROUND: Increasing numbers of breast cancer patients receive neoadjuvant chemotherapy (NACT). We seek to investigate whether baseline mammographic and ultrasound features are associated with complete pathological response (pCR) after NACT. METHODS: A database of NACT patients was reviewed. Baseline imaging parameters assessed were ultrasound: posterior effect; echo pattern; margin and lesion diameter; mammography: spiculation and microcalcification. Core biopsy grade and immunophenotype were documented. Data were analysed for the whole study group and by immunophenotype. RESULTS: Of the 222 cancers, 83 (37%) were triple negative (TN), 61 (27%) ER positive/HER-2 negative and 78 (35%) HER-2 positive. A pCR occurred in 46 of 222 cancers (21%). For the whole group, response was associated with high core biopsy grade (grade 3 vs. grade 1 or 2) (26% vs. 9%, p = 0.0044), absence of posterior shadowing on ultrasound (26% vs. 10%, p <  0.001) and the absence of mammographic spiculation (26 vs. 6%, p <  0.001). Within the HER-2 positive group; the absence of shadowing and spiculation remained highly associated with pCR, in addition to small ultrasound size (AUC = 0.71, p < 0.001) and the absence of microcalcification (39% vs. 21%, p < 0.02). On multivariable analysis absence of spiculation and core grade remained significant for the whole cohort, size and absence of spiculation remained significant for HER-2 positive tumours. No feature predicted pCR in TN tumours. CONCLUSION: A pCR is less likely when there is mammographic spiculation. Small ultrasound size is associated with pCR in HER-2 positive tumours. These findings may be helpful when discussing NACT and surgical options with patients. TRIAL REGISTRATION: UK Clinical Trials Gateway: registration number 16712.

Periprostatic fat adipokine expression is correlated with prostate cancer aggressiveness in men undergoing radical prostatectomy for clinically localized disease.

OBJECTIVES: To investigate the relationship between periprostatic adipose tissue (PPAT) adipokine expression and prostate cancer (PCa) aggressiveness using both pathological features of radical prostatectomy (RP) and multiparametric magnetic resonance imaging ( MRI) variables. PATIENTS AND METHODS: Sixty-nine men were recruited to assess immunohistochemical expression of tumour necrosis factor (TNF)α and vascular endothelial growth factor (VEGF) of periprostatic fat of RP specimens. Per cent immunopositivity was quantified on scanned slides using the Aperio Positive Pixel Count algorithm for PPAT TNFα, VEGF and androgen receptors. Periprostatic fat volume (PFV) was segmented on contiguous T1 -weighted axial MRI slices from the level of the prostate base to apex. PFV was normalized to prostate volume (PV) to account for variations in PV (normalized PFV = PFV/PV). MRI quantitative values (Kep , Ktrans and apparent diffusion coefficient) were measured from the PCa primary lesion using Olea Sphere software. Patients were stratified into three groups according to RP Gleason score (GS): ≤6, 7(3 + 4) and ≥7(4 + 3). RESULTS: The mean rank of VEGF and TNFα was significantly different between the groups [H(2) = 11.038, P = 0.004] and [H(2) = 13.086, P = 0.001], respectively. Patients with stage pT3 had higher TNFα (18.2 ± 8.95) positivity than patients with stage pT2 (13.27 ± 10.66; t [67] = -2.03, P = 0.047). TNFα expression significantly correlated with Ktrans (ρ = 0.327, P = 0.023). TNFα (P = 0.043), and VEGF (P = 0.02) correlated with high grade PCa (GS ≥ 7) in RP specimens and also correlated significantly with upgrading of GS from biopsy to RP histology. CONCLUSIONS: The expression levels of TNFα and VEGF on immunostaining significantly correlated with aggressivity of PCa. As biomarkers, these indicate the risk of having high grade PCa in men undergoing RP.

Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk.

BACKGROUND: Fully automated assessment of mammographic density (MD), a biomarker of breast cancer risk, is being increasingly performed in screening settings. However, data on body mass index (BMI), a confounder of the MD-risk association, are not routinely collected at screening. We investigated whether the amount of fat in the breast, as captured by the amount of mammographic non-dense tissue seen on the mammographic image, can be used as a proxy for BMI when data on the latter are unavailable. METHODS: Data from a UK case control study (numbers of cases/controls: 414/685) and a Norwegian cohort study (numbers of cases/non-cases: 657/61059), both with volumetric MD measurements (dense volume (DV), non-dense volume (NDV) and percent density (%MD)) from screening-age women, were analysed. BMI (self-reported) and NDV were taken as measures of adiposity. Correlations between BMI and NDV, %MD and DV were examined after log-transformation and adjustment for age, menopausal status and parity. Logistic regression models were fitted to the UK study, and Cox regression models to the Norwegian study, to assess associations between MD and breast cancer risk, expressed as odds/hazard ratios per adjusted standard deviation (OPERA). Adjustments were first made for standard risk factors except BMI (minimally adjusted models) and then also for BMI or NDV. OPERA pooled relative risks (RRs) were estimated by fixed-effect models, and between-study heterogeneity was assessed by the I2 statistics. RESULTS: BMI was positively correlated with NDV (adjusted r = 0.74 in the UK study and r = 0.72 in the Norwegian study) and with DV (r = 0.33 and r = 0.25, respectively). Both %MD and DV were positively associated with breast cancer risk in minimally adjusted models (pooled OPERA RR (95% confidence interval): 1.34 (1.25, 1.43) and 1.46 (1.36, 1.56), respectively; I2 = 0%, P >0.48 for both). Further adjustment for BMI or NDV strengthened the %MD-risk association (1.51 (1.41, 1.61); I2 = 0%, P = 0.33 and 1.51 (1.41, 1.61); I2 = 0%, P = 0.32, respectively). Adjusting for BMI or NDV marginally affected the magnitude of the DV-risk association (1.44 (1.34, 1.54); I2 = 0%, P = 0.87 and 1.49 (1.40, 1.60); I2 = 0%, P = 0.36, respectively). CONCLUSIONS: When volumetric MD-breast cancer risk associations are investigated, NDV can be used as a measure of adiposity when BMI data are unavailable.

A comparison of the imaging features of pleomorphic and classical invasive lobular carcinoma.

PURPOSE: Pleomorphic invasive lobular carcinoma (pILC) is a distinct morphological variant of ILC with a poorer prognosis than classical ILC (cILC). The aim of this study was to ascertain whether the conventional imaging appearances of the two entities differ. METHODS: A single-center retrospective review of conventional imaging was undertaken in 150 consecutive patients with histopathologically confirmed ILC (38 pILC; 112 cILC) between April 2010 and July 2015. Mammographic and sonographic findings were evaluated using the BI-RADS lexicon by a radiologist blinded to pathology, and the findings in the two groups were compared. The degree of discrepancy between imaging and pathological sizing in the two groups was evaluated. RESULTS: Lesions were mammographically occult in 11% of pILC and 14% of cILC (p = 0.56). On mammography, skin or trabecular thickening and microcalcification were commoner in pILC than cILC (13% vs. 1%, p < 0.01; 25% vs. 5%, p < 0.01). Architectural distortion was more frequent in cILC than pILC (26% vs. 9%, p = 0.01). On ultrasound, pILC more frequently exhibited mixed echogenicity (28% vs. 13%; p = 0.04), skin thickening, subcutaneous or parenchymal edema (8% vs. 0%; p = 0.02), echogenic surrounding fat (33% vs. 9%; p < 0.01), and posterior acoustic enhancement (10% vs. 1%; p = 0.02) than cILC. CILC was more frequently manifested as a focal area of altered echogenicity (24% vs. 8%; p = 0.04). Mean elastography stiffness was higher for pILC (174.8 vs. 124.6 kPa; p = 0.02). Imaging-pathological size disparity was similar for both subtypes. CONCLUSION: There are differences in the imaging features between pILC and cILC which reflect the more aggressive nature of pILC.

Pre-operative stromal stiffness measured by shear wave elastography is independently associated with breast cancer-specific survival.

INTRODUCTION: With the increased use of neoadjuvant therapy for breast cancer, there is a need for pre-operative prediction of prognosis. We aimed to assess the prognostic value of tumour stiffness measured by ultrasound shear wave elastography (SWE). METHODS: A consecutive cohort of patients with invasive breast cancer underwent breast ultrasound (US) including SWE. The following were recorded prospectively: US diameter, stiffness at SWE, presentation source, core biopsy grade, oestrogen receptor (ER) status and pre-operative nodal status. Breast cancer-specific survival (BCSS) was analysed with regard to US size and stiffness, tumour grade on core biopsy, ER status, presentation mode and pre-operative nodal status. Analysis used Cox proportional hazards regression. RESULTS: Of the 520 patients, 42 breast cancer and 53 non-breast cancer deaths were recorded at mean follow-up of 5.4 years. Hazard ratios (HR) for tertiles of stiffness were 1, 4.8 and 8.1 (P = 0.0001). HR for 2 groups based on US size < or ≥ 20 mm were 1 and 5.1 (P < 0.0001). HR for each unit increase in tumour grade on core biopsy was 3.9 (P < 0.0001). The HR for ER positivity compared to ER negativity was 0.21 (P < 0.001). BCSS was also associated with presentation mode and pre-operative nodal status. In a multivariable model, stiffness, US size and ER status were independently associated with BCSS. CONCLUSION: Multiple pre-operative factors including stromal stiffness at SWE have independent prognostic significance. A larger dataset with longer follow-up could be used in the future to construct a pre-operative prognostic model to guide treatment decisions.

Breast cancer: influence of tumour volume estimation method at MRI on prediction of pathological response to neoadjuvant chemotherapy.

OBJECTIVE: Does method of tumour volume measurement on MRI influence prediction of treatment outcome in patients with primary breast cancer undergoing neoadjuvant chemotherapy (NAC)?. METHOD: The study comprised of 136 women with biopsy-proven breast cancer scheduled for MRI monitoring during NAC treatment. Dynamic contrast-enhanced images were acquired at baseline (pre-NAC) and interim (post three NAC cycles) time points. Functional tumour volumes (FTVs), automatically derived using vendor software and enhancing tumour volumes (ETVs), user-derived using a semi-automated thresholding technique, were calculated at each time point and percentage changes calculated. Response, assessed using residual cancer burden (RCB) score on surgically resected specimens, was compared statistically with volumetric changes and receiver operating characteristic analysis performed. RESULTS: Mean volumetric differences for each RCB response category were (FTV/ETV): pathological complete response (pCR) 95.5/96.8%, RCB-I 69.8/66.7%, RCB-II 64.0/65.5%, RCB-III 25.4/24.0%. Differences were significant between pCR and RCB-II/RCB-III categories (p < 0.040; unpaired t-test) using FTV measures and between pCR and RCB-I/RCB-II/RCB-III categories (p < 0.006; unpaired t-test) when ETV was used. Receiver operating characteristic analysis for pCR identification post-NAC yielded area under the curve for FTV/ETV of 0.834/0.920 respectively. Sensitivity and specificity for FTV was 80.0 and 76.8% for FTV and 81.0 and 91.8% for ETV. CONCLUSION: ETV changes can identify patients likely to achieve a complete response to NAC. Potentially, this could impact patient management regarding the possible avoidance of post-NAC surgery. Advances in Knowledge: Interim changes in ETV are more useful than FTV in predicting final pathological response to NAC. ETV differentiates patients who will achieve a complete response from those who will have residual disease.

Determining paediatric patient thickness from a single digital radiograph-a proof of principle.

OBJECTIVE: This work presents a proof of principle for a method of estimating the thickness of an attenuator from a single radiograph using the image, the exposure factors with which it was acquired and a priori knowledge of the characteristics of the X-ray unit and detector used for the exposure. It is intended this could be developed into a clinical tool to assist with paediatric patient dose audit, for which a measurement of patient size is required. METHODS: The proof of principle used measured pixel value and effective linear attenuation coefficient to estimate the thickness of a Solid Water attenuator. The kerma at the detector was estimated using a measurement of pixel value on the image and measured detector calibrations. The initial kerma was estimated using a lookup table of measured output values. The effective linear attenuation coefficient was measured for Solid Water at varying kVp. 11 test images of known and varying thicknesses of Solid Water were acquired at 60, 70 and 81 kVp. Estimates of attenuator thickness were made using the model and the results compared to the known thickness. RESULTS: Estimates of attenuator thickness made using the model differed from the known thickness by 3.8 mm (3.2%) on average, with a range of 0.5-10.8 mm (0.5-9%). CONCLUSION: A proof of principle is presented for a method of estimating the thickness of an attenuator using a single radiograph of the attenuator. The method has been shown to be accurate using a Solid Water attenuator, with a maximum difference between estimated and known attenuator thickness of 10.8 mm (9%). The method shows promise as a clinical tool for estimating abdominal paediatric patient thickness for paediatric patient dose audit, and is only contingent on the type of data routinely collected by Medical Physics departments. Advances in knowledge: A computational model has been created that is capable of accurately estimating the thickness of a uniform attenuator using only the radiographic image, the exposure factors with which it was acquired and a priori knowledge of the characteristics of the X-ray unit and detector used for the exposure.

Feasibility study to assess the impact of a lifestyle intervention ('LivingWELL') in people having an assessment of their family history of colorectal or breast cancer.

OBJECTIVES: To assess the feasibility of delivering and evaluating a weight management (WM) programme for overweight patients with a family history (FH) of breast cancer (BC) or colorectal cancer (CRC). STUDY DESIGN: A two-arm (intervention vs usual care) randomised controlled trial. SETTING: National Health Service (NHS) Tayside and NHS Grampian. PARTICIPANTS: People with a FH of BC or CRC aged≥18 years and body mass index of ≥25 kg/m2 referred to NHS genetic services. INTERVENTION: Participants were randomised to a control (lifestyle booklet) or 12-week intervention arm where they were given one face-to-face counselling session, four telephone consultations and web-based support. A goal of 5% reduction in body weight was set, and a personalised diet and physical activity (PA) programme was provided. Behavioural change techniques (motivational interviewing, action and coping plans and implementation intentions) were used. PRIMARY OUTCOME: Feasibility measures: recruitment, programme implementation, fidelity measures, achieved measurements and retention, participant satisfaction assessed by questionnaire and qualitative interviews. SECONDARY OUTCOMES: Measured changes in weight and PA and reported diet and psychosocial measures between baseline and 12-week follow-up. RESULTS: Of 480 patients approached, 196 (41%) expressed interest in the study, and of those, 78 (40%) patients were randomised. Implementation of the programme was challenging within the time allotted and fidelity to the intervention modest (62%). Qualitative findings indicated the programme was well received. Questionnaires and anthropometric data were completed by >98%. Accelerometer data were attained by 84% and 54% at baseline and follow-up, respectively. Retention at 12 weeks was 76%. Overall, 36% of the intervention group (vs 0% in control) achieved 5% weight loss. Favourable increases in PA and reduction in dietary fat were also reported. CONCLUSIONS: A lifestyle programme for people with a family history of cancer is feasible to conduct and acceptable to participants, and indicative results suggest favourable outcomes. TRIAL REGISTRATION NUMBER: ISRCTN13123470; Pre-results.

Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy for Primary Breast Cancer Comparing Interim Ultrasound, Shear Wave Elastography and MRI.

BACKGROUND: Prediction of pathological complete response (pCR) of primary breast cancer to neoadjuvant chemotherapy (NACT) may influence planned surgical approaches in the breast and axilla. The aim of this project is to assess the value of interim shear wave elastography (SWE), ultrasound (US) and magnetic resonance imaging (MRI) after 3 cycles in predicting pCR. METHODS: 64 patients receiving NACT had baseline and interim US, SWE and MRI examinations. The mean lesion stiffness at SWE, US and MRI diameter was measured at both time points. We compared four parameters with pCR status: a) Interim mean stiffness ≤ or > 50 kPa; b) Percentage stiffness reduction; c) Percentage US diameter reduction and d) Interim MRI response using RECIST criteria. The Chi square test was used to assess significance. RESULTS: Interim stiffness of ≤ or > 50 kPa gave the best prediction of pCR with pCR seen in 10 of 14 (71 %) cancers with an interim stiffness of ≤ 50 kPa, compared to 7 of 50 (14 %) of cancers with an interim stiffness of > 50 kPa, (p < 0.0001) (sensitivity 59 %, specificity 91 %, PPV 71 %, NPV 86 % and diagnostic accuracy 83 %). Percentage reduction in stiffness was the next best parameter (sensitivity 59 %, specificity 85 %, p < 0.0004) followed by reduction in MRI diameter of > 30 % (sensitivity 50 % and specificity 79 %, p = 0.03) and % reduction in US diameter (sensitivity 47 %, specificity 81 %, p = 0.03). Similar results were obtained from ROC analysis. CONCLUSION: SWE stiffness of breast cancers after 3 cycles of NACT and changes in stiffness from baseline are strongly associated with pCR after 6 cycles.

Correlation of X-ray diffraction signatures of breast tissue and their histopathological classification.

This pilot study examines the correlation of X-ray diffraction (XRD) measurements with the histopathological analysis of breast tissue. Eight breast cancer samples were investigated. Each sample contained a mixture of normal and cancerous tissues. In total, 522 separate XRD measurements were made at different locations across the samples (8 in total). The resulting XRD spectra were subjected to principal component analysis (PCA) in order to determine if there were any distinguishing features that could be used to identify different tissue components. 99.0% of the variation between the spectra were described by the first two principal components (PC). Comparing the location of points in PC space with the classification determined by histopathology indicated correlation between the shape/magnitude of the XRD spectra and the tissue type. These results are encouraging and suggest that XRD could be used for the intraoperative or postoperative classification of bulk tissue samples.