BackgroundPrimary small cell ovarian cancer of pulmonary type (SCCOPT) is a rare aggressive ovarian tumour with an incidence of <1%, usually occurring in perimenopausal or postmenopausal women and known to have a poor prognosis. Current treatment is platinum based but has not resulted in long term survival.Case presentationWe report a case of a 77-year old Caucasian woman who presented initially with a one-week history of abdominal discomfort with raised inflammatory markers and Ca125 of 50 μ/ml. Calcium levels were normal. She underwent primary debulking surgery, and histology showed a tumour comprising areas of classical small-cell carcinoma morphology. 6 cycles of adjuvant chemotherapy with carboplatin was offered. Relapsed/progressive disease was noted after 3 months of chemotherapy and patient died 7 months after treatment completion.ConclusionsSCCOPT is a rare aggressive malignancy with majority of the women having an overall survival of 2 years. There is no clear consensus for the diagnosis and optimal treatment.

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Purpose To assess whether individual reader performance with digital breast tomosynthesis (DBT) and two-dimensional (2D) mammography varies with number of years of experience or volume of 2D mammograms read. Materials and Methods After written informed consent was obtained, 8869 women (age range, 29-85 years; mean age, 56 years) were recruited into the TOMMY trial (A Comparison of Tomosynthesis with Digital Mammography in the UK National Health Service Breast Screening Program), an ethically approved, multicenter, multireader, retrospective reading study, between July 2011 and March 2013. Each case was read prospectively for clinical assessment and to establish ground truth. A retrospective reading data set of 7060 cases was created and randomly allocated for independent blinded review of (a) 2D mammograms, (b) DBT images and 2D mammograms, and (c) synthetic 2D mammograms and DBT images, without access to previous examinations. Readers (19 radiologists, three advanced practitioner radiographers, and two breast clinicians) who had 3-25 (median, 10) years of experience in the U.K. National Health Service Breast Screening Program and read 5000-13 000 (median, 8000) cases per annum were included in this study. Specificity was analyzed according to reader type and years and volume of experience, and then both specificity and sensitivity were analyzed by matched inference. The median duration of experience (10 years) was used as the cutoff point for comparison of reader performance. Results Specificity improved with the addition of DBT for all readers. This was significant for all staff groups (56% vs 68% and 49% vs 67% [P < .0001] for radiologists and advanced practitioner radiographers, respectively; 46% vs 55% [P = .02] for breast clinicians). Sensitivity was improved for 19 of 24 (79%) readers and was significantly higher for those with less than 10 years of experience (91% vs 86%; P = .03) and those with total mammographic experience of fewer than 80 000 cases (88% vs 86%; P = .03). Conclusion The addition of DBT to conventional 2D screening mammography improved specificity for all readers, but the gain in sensitivity was greater for readers with less than 10 years of experience.

Polyunsaturated fatty acid (PUFA), a key marker in breast cancer, is non-invasively quantifiable using multiple quantum coherence (MQC) magnetic resonance spectroscopy (MRS) at the expense of losing half of the signal. Signal combination for phased array coils provides potential pathways to enhance the signal to noise ratio (SNR), with current algorithms developed for conventional brain MRS. Since PUFA spectra and the biochemical environment in the breast deviate significantly from those in the brain, we set out to identify the optimal algorithm for PUFA in breast cancer. Combination algorithms were compared using PUFA spectra from 17 human breast tumour specimens, 15 healthy female volunteers, and 5 patients with breast cancer on a clinical 3 T MRI scanner. Adaptively Optimised Combination (AOC) yielded the maximum SNR improvement in specimens (median, 39.5%; interquartile range: 35.5–53.2%, p < 0.05), volunteers (82.4 ± 37.4%, p < 0.001), and patients (median, 61%; range: 34–105%, p < 0.05), while independent from voxel volume (rho = 0.125, p = 0.632), PUFA content (rho = 0.256, p = 0.320) or water/fat ratio (rho = 0.353, p = 0.165). Using AOC, acquisition in patients is 1.5 times faster compared to non-noise decorrelated algorithms. Therefore, AOC is the most suitable current algorithm to improve SNR or accelerate the acquisition of PUFA MRS from breast in a clinical setting.