Publications
Browse peer-reviewed publications featuring Volpara Health science and technologies.
*full bibliography available upon request
Featured
Supplemental Breast MRI for Women with Extremely Dense Breasts: Results of the Second Screening Round of the DENSE Trial
“The incremental cancer detection rate in the second round was 5.8 per 1000 screening examinations—compared with 16.5 per 1000 screening examinations in the first round. This was accompanied by a strong reduction in the number of false positive results.”
Veenhuizen, de Lange, Bakker, Pijnappel, Mann, Monninkhof, Emaus, de Koekkoek-Doll, Bisschops, Lobbes, de Jong, Duvivier, Veltman, Karssemeijer, de Koning, van Diest, Mali, van den Bosch, van Gils, Veldhuis
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Featured
Supplemental Breast MRI for Women with Extremely Dense Breasts: Results of the Second Screening Round of the DENSE Trial
Veenhuizen, de Lange, Bakker, Pijnappel, Mann, Monninkhof, Emaus, de Koekkoek-Doll, Bisschops, Lobbes, de Jong, Duvivier, Veltman, Karssemeijer, de Koning, van Diest, Mali, van den Bosch, van Gils, Veldhuis
“The incremental cancer detection rate in the second round was 5.8 per 1000 screening examinations—compared with 16.5 per 1000 screening examinations in the first round. This was accompanied by a strong reduction in the number of false positive results.”
Artificial intelligence in radiology: 100 commercially available products and their scientific evidence
van Leeuwen, Schalekamp, Rutten, van Ginneken, de Rooij
“The overview included 100 CE-marked AI products from 54 different vendors. For 64/100 products, there was no peer-reviewed evidence of its efficacy.”
Volpara had the most scientific papers of all breast radiology AI software reviewed in the study.
Assessment of breast positioning criteriain mammographic screening: Agreement between artificial intelligence software and radiographers
Waade, Danielsen, Holen, Larsen, Hanestad, Hopland, Kalcheva, Hofvind
“AI has great potential in evaluating breast position criteria in mammography by reducing subjectivity.”
Digital breast tomosynthesis: sensitivity for cancer in younger symptomatic women
Whelehan, Ali, Vinnicombe, Ball, Cox, Farry, Jenkin, Lowry, McIntosh, Nutt, Oeppen, Reilly, Stahnke, Steel, Sim, Warwick, Wilkinson, Zafeiris, Evans
“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.”
Parenchymal pattern in women with dense breasts. Variation with age and impact on screening outcomes: observations from a UK screening programme
Ward, Heller, Hudson, Wilkinson
“A total of 40,760 women who underwent screening during the
study period had Volpara data available … There was a significant correlation between a diagnosis of cancer and nodular PP compared to not nodular PP (p = 0.043).”
Monte Carlo calculation of conversion coefficients for dose estimation in mammography based on a 3D detailed breast model
Wang, Qiu, Ren, Liu, Wu, Li, Niu, Li
“A series of glandular tissue dose conversion coefficients for dose estimation in mammography were calculated. The conversion coefficients calculated in this study were compared with those estimated with the simple breast model. A discrepancy of 5.4–38.0% was observed.”
Agreement of Mammographic Measures of Volumetric Breast Density to MRI
Wang, Azziz, Fan, Malkov, Klifa, Newitt, Yitta, Hylton, Kerlikowske, Shepherd
“Automated volumetric fibroglandular tissue measures from screening digital mammograms were in substantial agreement with MRI and if associated with breast cancer could be used in clinical practice to enhance risk assessment and prevention.”
The combined effect of mammographic texture and density on breast cancer risk: a cohort study
Wanders, van Gils, Karssemeijer, Holland, Kallenberg, Peeters, Nielsen, Lillholm
“Deep-learning-based texture pattern scores, measured automatically on digital mammograms, are associated with breast cancer risk, independently of volumetric mammographic density, and augment the capacity to discriminate between future breast cancer and non-breast cancer cases.”
The effect of volumetric breast density on the risk of screen-detected and interval breast cancers: a cohort study
Wanders, Holland, Karssemeijer, Peeters, Veldhuis, Mann, van Gils
“Our results suggest that both absolute dense volume and percentage dense volume are strong markers of breast cancer risk, but that they are even stronger markers for predicting the occurrence of tumors that are not detected during mammography breast cancer screening.”
Breast compression across consecutive examinations among females participating in BreastScreen Norway
Waade, Sebuødegård, Hogg, Hofvind
“Breast compression force, compression pressure and compressed breast thickness increased across consecutive screening examinations,
which might be of influence for the females’ experiences of discomfort and pain during the examination and for image quality.”
Compression forces used in the Norwegian Breast Cancer Screening Program
Waade, Moshina, Sebuødegård, Hogg, Hofvind
“A wide variation in applied compression force was observed between the breast centres in the NBCSP. This variation indicates a need for evidence based recommendations for compression force aimed at optimizing the image quality and individualizing breast compression.”