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BACKGROUNDGenetic testing for breast cancer susceptibility is widely used, but for many genes,evidence of an association with breast cancer is weak, underlying risk estimatesare imprecise, and reliable subtype-specific risk estimates are lacking.METHODSWe used a panel of 34 putative susceptibility genes to perform sequencing onsamples from 60,466 women with breast cancer and 53,461 controls. In separateanalyses for protein-truncating variants and rare missense variants in these genes,we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluatedmissense-variant associations according to domain and classification of pathogenicity.RESULTSProtein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2)were associated with a risk of breast cancer overall with a P value of less than0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D,and TP53) were associated with a risk of breast cancer overall with a P value ofless than 0.05 and a Bayesian false-discovery probability of less than 0.05. Forprotein-truncating variants in 19 of the remaining 25 genes, the upper limit ofthe 95% confidence interval of the odds ratio for breast cancer overall was lessthan 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios werehigher for estrogen receptor (ER)–positive disease than for ER-negative disease;for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, andRAD51D, odds ratios were higher for ER-negative disease than for ER-positivedisease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 wereassociated with a risk of breast cancer overall with a P value of less than 0.001.For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a riskof breast cancer overall, with the risk being similar to that of protein-truncatingvariants.CONCLUSIONSThe results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimatesof the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.)

Background Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. Methods We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. Results Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07–1.30, P = 0.11 × 10–2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78–1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. Conclusion Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.

Contains fulltext : 206539.pdf (Publisher’s version ) (Closed access) BACKGROUND: BRCA1/2 mutations confer high lifetime risk of breast cancer, although other factors may modify this risk. Whether height or body mass index (BMI) modifies breast cancer risk in BRCA1/2 mutation carriers remains unclear. METHODS: We used Mendelian randomization approaches to evaluate the association of height and BMI on breast cancer risk, using data from the Consortium of Investigators of Modifiers of BRCA1/2 with 14 676 BRCA1 and 7912 BRCA2 mutation carriers, including 11 451 cases of breast cancer. We created a height genetic score using 586 height-associated variants and a BMI genetic score using 93 BMI-associated variants. We examined both observed and genetically determined height and BMI with breast cancer risk using weighted Cox models. All statistical tests were two-sided. RESULTS: Observed height was positively associated with breast cancer risk (HR = 1.09 per 10 cm increase, 95% confidence interval [CI] = 1.0 to 1.17; P = 1.17). Height genetic score was positively associated with breast cancer, although this was not statistically significant (per 10 cm increase in genetically predicted height, HR = 1.04, 95% CI = 0.93 to 1.17; P = .47). Observed BMI was inversely associated with breast cancer risk (per 5 kg/m2 increase, HR = 0.94, 95% CI = 0.90 to 0.98; P = .007). BMI genetic score was also inversely associated with breast cancer risk (per 5 kg/m2 increase in genetically predicted BMI, HR = 0.87, 95% CI = 0.76 to 0.98; P = .02). BMI was primarily associated with premenopausal breast cancer. CONCLUSION: Height is associated with overall breast cancer and BMI is associated with premenopausal breast cancer in BRCA1/2 mutation carriers. Incorporating height and BMI, particularly genetic score, into risk assessment may improve cancer management.

To describe radiographic evidence of radiation pneumonitis (rRP) and fibrosis (rRF) and determine what dosimetric parameters correlate with rRP and rRF after stereotactic ablative radiation therapy (SABR) to the lung. Ninety-eight follow-up computed tomography (CT) scans from 32 patients treated by SABR were retrospectively reviewed for CT appearance of rRP and rRF determined by the Ikezoe (≤6 months) and Koenig (≥7 months) systems. The dosimetric correlations for rRP, rRF, and fibrotic volume were analyzed. There was a 55 % incidence of rRP and 59 % incidence of rRF with a median follow-up of 10 months. Only the low-dose parameters V 2.5, V 5, V 7, and V 10 (the volume of lung receiving more than 2.5, 5, 7, and 10 Gy of radiation, respectively) were correlated to the development of rRP (p

Publisher's version (útgefin grein), Breast cancer is a common disease partially caused by genetic risk factors. Germline pathogenic variants in DNA repair genes BRCA1, BRCA2, PALB2, ATM, and CHEK2 are associated with breast cancer risk. FANCM, which encodes for a DNA translocase, has been proposed as a breast cancer predisposition gene, with greater effects for the ER-negative and triple-negative breast cancer (TNBC) subtypes. We tested the three recurrent protein-truncating variants FANCM:p.Arg658*, p.Gln1701*, and p.Arg1931* for association with breast cancer risk in 67,112 cases, 53,766 controls, and 26,662 carriers of pathogenic variants of BRCA1 or BRCA2. These three variants were also studied functionally by measuring survival and chromosome fragility in FANCM−/− patient-derived immortalized fibroblasts treated with diepoxybutane or olaparib. We observed that FANCM:p.Arg658* was associated with increased risk of ER-negative disease and TNBC (OR = 2.44, P = 0.034 and OR = 3.79; P = 0.009, respectively). In a country-restricted analysis, we confirmed the associations detected for FANCM:p.Arg658* and found that also FANCM:p.Arg1931* was associated with ER-negative breast cancer risk (OR = 1.96; P = 0.006). The functional results indicated that all three variants were deleterious affecting cell survival and chromosome stability with FANCM:p.Arg658* causing more severe phenotypes. In conclusion, we confirmed that the two rare FANCM deleterious variants p.Arg658* and p.Arg1931* are risk factors for ER-negative and TNBC subtypes. Overall our data suggest that the effect of truncating variants on breast cancer risk may depend on their position in the gene. Cell sensitivity to olaparib exposure, identifies a possible therapeutic option to treat FANCM-associated tumors., Peterlongo laboratory is supported by Associazione Italiana Ricerca sul Cancro (AIRC; IG2015 no.16732) to P. Peterlongo and by a fellowship from Fondazione Umberto Veronesi to G. Figlioli. Surrallés laboratory is supported by the ICREA-Academia program, the Spanish Ministry of Health (projects FANCOSTEM and FANCOLEN), the Spanish Ministry of Economy and Competiveness (projects CB06/07/0023 and RTI2018-098419-B-I00), the European Commission (EUROFANCOLEN project HEALTH-F5-2012-305421 and P-SPHERE COFUND project), the Fanconi Anemia Research Fund Inc, and the “Fondo Europeo de Desarrollo Regional, una manera de hacer Europa” (FEDER). CIBERER is an initiative of the Instituto de Salud Carlos III, Spain. BCAC: we thank all the individuals who took part in these studies and all the researchers, clinicians, technicians and administrative staff who have enabled this work to be carried out. ABCFS thank Maggie Angelakos, Judi Maskiell, Tu Nguyen-Dumont is a National Breast Cancer Foundation (Australia) Career Development Fellow. ABCS thanks the Blood bank Sanquin, The Netherlands. Samples are made available to researchers on a non-exclusive basis. BCEES thanks Allyson Thomson, Christobel Saunders, Terry Slevin, BreastScreen Western Australia, Elizabeth Wylie, Rachel Lloyd. The BCINIS study would not have been possible without the contributions of Dr. Hedy Rennert, Dr. K. Landsman, Dr. N. Gronich, Dr. A. Flugelman, Dr. W. Saliba, Dr. E. Liani, Dr. I. Cohen, Dr. S. Kalet, Dr. V. Friedman, Dr. O. Barnet of the NICCC in Haifa, and all the contributing family medicine, surgery, pathology and oncology teams in all medical institutes in Northern Israel. The BREOGAN study would not have been possible without the contributions of the following: Manuela Gago-Dominguez, Jose Esteban Castelao, Angel Carracedo, Victor Muñoz Garzón, Alejandro Novo Domínguez, Maria Elena Martinez, Sara Miranda Ponte, Carmen Redondo Marey, Maite Peña Fernández, Manuel Enguix Castelo, Maria Torres, Manuel Calaza (BREOGAN), José Antúnez, Máximo Fraga and the staff of the Department of Pathology and Biobank of the University Hospital Complex of Santiago-CHUS, Instituto de Investigación Sanitaria de Santiago, IDIS, Xerencia de Xestion Integrada de Santiago-SERGAS; Joaquín González-Carreró and the staff of the Department of Pathology and Biobank of University Hospital Complex of Vigo, Instituto de Investigacion Biomedica Galicia Sur, SERGAS, Vigo, Spain. BSUCH thanks Peter Bugert, Medical Faculty Mannheim. CBCS thanks study participants, co-investigators, collaborators and staff of the Canadian Breast Cancer Study, and project coordinators Agnes Lai and Celine Morissette. CCGP thanks Styliani Apostolaki, Anna Margiolaki, Georgios Nintos, Maria Perraki, Georgia Saloustrou, Georgia Sevastaki, Konstantinos Pompodakis. CGPS thanks staff and participants of the Copenhagen General Population Study. For the excellent technical assistance: Dorthe Uldall Andersen, Maria Birna Arnadottir, Anne Bank, Dorthe Kjeldgård Hansen. The Danish Cancer Biobank is acknowledged for providing infrastructure for the collection of blood samples for the cases. Investigators from the CPS-II cohort thank the participants and Study Management Group for their invaluable contributions to this research. They also acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention National Program of Cancer Registries, as well as cancer registries supported by the National Cancer Institute Surveillance Epidemiology and End Results program. The CTS Steering Committee includes Leslie Bernstein, Susan Neuhausen, James Lacey, Sophia Wang, Huiyan Ma, and Jessica Clague DeHart at the Beckman Research Institute of City of Hope, Dennis Deapen, Rich Pinder, and Eunjung Lee at the University of Southern California, Pam Horn-Ross, Peggy Reynolds, Christina Clarke Dur and David Nelson at the Cancer Prevention Institute of California, Hoda Anton-Culver, Argyrios Ziogas, and Hannah Park at the University of California Irvine, and Fred Schumacher at Case Western University. DIETCOMPLYF thanks the patients, nurses and clinical staff involved in the study. The DietCompLyf study was funded by the charity Against Breast Cancer (Registered Charity Number 1121258) and the NCRN. We thank the participants and the investigators of EPIC (European Prospective Investigation into Cancer and Nutrition). ESTHER thanks Hartwig Ziegler, Sonja Wolf, Volker Hermann, Christa Stegmaier, Katja Butterbach. FHRISK thanks NIHR for funding. GC-HBOC thanks Stefanie Engert, Heide Hellebrand, Sandra Kröber and LIFE - Leipzig Research Centre for Civilization Diseases (Markus Loeffler, Joachim Thiery, Matthias Nüchter, Ronny Baber). The GENICA Network: Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, and University of Tübingen, Germany [HB, Wing-Yee Lo], German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ) [HB], Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy - EXC 2180 - 390900677 [HB], Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany [Yon-Dschun Ko, Christian Baisch], Institute of Pathology, University of Bonn, Germany [Hans-Peter Fischer], Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, Germany [Ute Hamann], Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, Germany [TB, Beate Pesch, Sylvia Rabstein, Anne Lotz]; and Institute of Occupational Medicine and Maritime Medicine, University Medical Center Hamburg-Eppendorf, Germany [Volker Harth]. HABCS thanks Michael Bremer. HEBCS thanks Heidi Toiminen, Kristiina Aittomäki, Irja Erkkilä and Outi Malkavaara. HMBCS thanks Peter Hillemanns, Hans Christiansen and Johann H. Karstens. HUBCS thanks Shamil Gantsev. KARMA thanks the Swedish Medical Research Counsel. KBCP thanks Eija Myöhänen, Helena Kemiläinen. LMBC thanks Gilian Peuteman, Thomas Van Brussel, EvyVanderheyden and Kathleen Corthouts. MABCS thanks Milena Jakimovska (RCGEB “Georgi D. Efremov), Katerina Kubelka, Mitko Karadjozov (Adzibadem-Sistina” Hospital), Andrej Arsovski and Liljana Stojanovska (Re-Medika” Hospital) for their contributions and commitment to this study. MARIE thanks Petra Seibold, Dieter Flesch-Janys, Judith Heinz, Nadia Obi, Alina Vrieling, Sabine Behrens, Ursula Eilber, Muhabbet Celik, Til Olchers and Stefan Nickels. MBCSG (Milan Breast Cancer Study Group) thanks Daniela Zaffaroni, Irene Feroce, and the personnel of the Cogentech Cancer Genetic Test Laboratory. We thank the coordinators, the research staff and especially the MMHS participants for their continued collaboration on research studies in breast cancer. MSKCC thanks Marina Corines and Lauren Jacobs. MTLGEBCS would like to thank Martine Tranchant (CHU de Québec Research Center), Marie-France Valois, Annie Turgeon and Lea Heguy (McGill University Health Center, Royal Victoria Hospital; McGill University) for DNA extraction, sample management and skillful technical assistance. J.S. is Chairholder of the Canada Research Chair in Oncogenetics. NBHS thanks study participants and research staff for their contributions and commitment to the studies. We would like to thank the participants and staff of the Nurses’ Health Study and Nurses’ Health Study II for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The study protocol was approved by the institutional review boards of the Brigham and Women’s Hospital and Harvard T.H. Chan School of Public Health, and those of participating registries as required. The authors assume full responsibility for analyses and interpretation of these data. OFBCR thanks Teresa Selander and Nayana Weerasooriya. ORIGO thanks E. Krol-Warmerdam, and J. Blom for patient accrual, administering questionnaires, and managing clinical information. PBCS thanks Louise Brinton, Mark Sherman, Neonila Szeszenia-Dabrowska, Beata Peplonska, Witold Zatonski, Pei Chao and Michael Stagner. The ethical approval for the POSH study is MREC /00/6/69, UKCRN ID: 1137. We thank staff in the Experimental Cancer Medicine Centre (ECMC) supported Faculty of Medicine Tissue Bank and the Faculty of Medicine DNA Banking resource. PREFACE thanks Sonja Oeser and Silke Landrith. PROCAS thanks NIHR for funding. RBCS thanks Petra Bos, Jannet Blom, Ellen Crepin, Elisabeth Huijskens, Anja Kromwijk-Nieuwlaat, Annette Heemskerk, the Erasmus MC Family Cancer Clinic. We thank the SEARCH and EPIC teams. SKKDKFZS thanks all study participants, clinicians, family doctors, researchers and technicians for their contributions and commitment to this study. We thank the SUCCESS Study teams in Munich, Duessldorf, Erlangen and Ulm. SZBCS thanks Ewa Putresza. UCIBCS thanks Irene Masunaka. UKBGS thanks Breast Cancer Now and the Institute of Cancer Research for support and funding of the Breakthrough Generations Study, and the study participants, study staff, and the doctors, nurses and other health care providers and health information sources who have contributed to the study. We acknowledge NHS funding to the Royal Marsden/ICR NIHR Biomedical Research Centre. CIMBA: we are grateful to all the families and clinicians who contribute to the studies; Sue Healey, in particular taking on the task of mutation classification with the late Olga Sinilnikova; Maggie Angelakos, Judi Maskiell, Helen Tsimiklis; members and participants in the New York site of the Breast Cancer Family Registry; members and participants in the Ontario Familial Breast Cancer Registry; Vilius Rudaitis and Laimonas Griškevičius; Yuan Chun Ding and Linda Steele for their work in participant enrollment and biospecimen and data management; Bent Ejlertsen and Anne-Marie Gerdes for the recruitment and genetic counseling of participants; Alicia Barroso, Rosario Alonso and Guillermo Pita; all the individuals and the researchers who took part in CONSIT TEAM (Consorzio Italiano Tumori Ereditari Alla Mammella), thanks in particular: Giulia Cagnoli, Roberta Villa, Irene Feroce, Mariarosaria Calvello, Riccardo Dolcetti, Giuseppe Giannini, Laura Papi, Gabriele Lorenzo Capone, Liliana Varesco, Viviana Gismondi, Maria Grazia Tibiletti, Daniela Furlan, Antonella Savarese, Aline Martayan, Stefania Tommasi, Brunella Pilato, Isabella Marchi, Elena Bandieri, Antonio Russo, Daniele Calistri and the personnel of the Cogentech Cancer Genetic Test Laboratory, Milan, Italy. FPGMX: members of the Cancer Genetics group (IDIS): Ana Blanco, Miguel Aguado, Uxía Esperón and Belinda Rodríguez. We thank all participants, clinicians, family doctors, researchers, and technicians for their contributions and commitment to the DKFZ study and the collaborating groups in Lahore, Pakistan (Noor Muhammad, Sidra Gull, Seerat Bajwa, Faiz Ali Khan, Humaira Naeemi, Saima Faisal, Asif Loya, Mohammed Aasim Yusuf) and Bogota, Colombia (Diana Torres, Ignacio Briceno, Fabian Gil). Genetic Modifiers of Cancer Risk in BRCA1/2 Mutation Carriers (GEMO) study is a study from the National Cancer Genetics Network UNICANCER Genetic Group, France. We wish to pay a tribute to Olga M. Sinilnikova, who with Dominique Stoppa-Lyonnet initiated and coordinated GEMO until she sadly passed away on the 30th June 2014. The team in Lyon (Olga Sinilnikova, Mélanie Léoné, Laure Barjhoux, Carole Verny-Pierre, Sylvie Mazoyer, Francesca Damiola, Valérie Sornin) managed the GEMO samples until the biological resource centre was transferred to Paris in December 2015 (Noura Mebirouk, Fabienne Lesueur, Dominique Stoppa-Lyonnet). We want to thank all the GEMO collaborating groups for their contribution to this study. Drs.Sofia Khan, Irja Erkkilä and Virpi Palola; The Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON) consists of the following Collaborating Centers: Netherlands Cancer Institute (coordinating center), Amsterdam, NL: M.A. Rookus, F.B.L. Hogervorst, F.E. van Leeuwen, M.A. Adank, M.K. Schmidt, N.S. Russell, D.J. Jenner; Erasmus Medical Center, Rotterdam, NL: J.M. Collée, A.M.W. van den Ouweland, M.J. Hooning, C.M. Seynaeve, C.H.M. van Deurzen, I.M. Obdeijn; Leiden University Medical Center, NL: C.J. van Asperen, P. Devilee, T.C.T.E.F. van Cronenburg; Radboud University Nijmegen Medical Center, NL: C.M. Kets, A.R. Mensenkamp; University Medical Center Utrecht, NL: M.G.E.M. Ausems, M.J. Koudijs; Amsterdam Medical Center, NL: C.M. Aalfs, H.E.J. Meijers-Heijboer; VU University Medical Center, Amsterdam, NL: K. van Engelen, J.J.P. Gille; Maastricht University Medical Center, NL: E.B. Gómez-Garcia, M.J. Blok; University of Groningen, NL: J.C. Oosterwijk, A.H. van der Hout, M.J. Mourits, G.H. de Bock; The Netherlands Comprehensive Cancer Organisation (IKNL): S. Siesling, J.Verloop; The nationwide network and registry of histo- and cytopathology in The Netherlands (PALGA): A.W. van den Belt-Dusebout. HEBON thanks the study participants and the registration teams of IKNL and PALGA for part of the data collection. Overbeek; the Hungarian Breast and Ovarian Cancer Study Group members (Janos Papp, Aniko Bozsik, Zoltan Matrai, Miklos Kasler, Judit Franko, Maria Balogh, Gabriella Domokos, Judit Ferenczi, Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary) and the clinicians and patients for their contributions to this study; HVH (University Hospital Vall d’Hebron) the authors acknowledge the Oncogenetics Group (VHIO) and the High Risk and Cancer Prevention Unit of the University Hospital Vall d’Hebron, Miguel Servet Progam (CP10/00617), and the Cellex Foundation for providing research facilities and equipment; the ICO Hereditary Cancer Program team led by Dr. Gabriel Capella; the ICO Hereditary Cancer Program team led by Dr. Gabriel Capella; Dr Martine Dumont for sample management and skillful assistance; Catarina Santos and Pedro Pinto; members of the Center of Molecular Diagnosis, Oncogenetics Department and Molecular Oncology Research Center of Barretos Cancer Hospital; Heather Thorne, Eveline Niedermayr, all the kConFab investigators, research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study (which has received funding from the NHMRC, the National Breast Cancer Foundation, Cancer Australia, and the National Institute of Health (USA)) for their contributions to this resource, and the many families who contribute to kConFab; the investigators of the Australia New Zealand NRG Oncology group; members and participants in the Ontario Cancer Genetics Network; Kevin Sweet, Caroline Craven, Julia Cooper, Amber Aielts, and Michelle O’Conor; Christina Selkirk; Helena Jernström, Karin Henriksson, Katja Harbst, Maria Soller, Ulf Kristoffersson; from Gothenburg Sahlgrenska University Hospital: Anna Öfverholm, Margareta Nordling, Per Karlsson, Zakaria Einbeigi; from Stockholm and Karolinska University Hospital: Anna von Wachenfeldt, Annelie Liljegren, Annika Lindblom, Brita Arver, Gisela Barbany Bustinza; from Umeå University Hospital: Beatrice Melin, Christina Edwinsdotter Ardnor, Monica Emanuelsson; from Uppsala University: Hans Ehrencrona, Maritta Hellström Pigg, Richard Rosenquist; from Linköping University Hospital: Marie Stenmark-Askmalm, Sigrun Liedgren; Cecilia Zvocec, Qun Niu; Joyce Seldon and Lorna Kwan; Dr. Robert Nussbaum, Beth Crawford, Kate Loranger, Julie Mak, Nicola Stewart, Robin Lee, Amie Blanco and Peggy Conrad and Salina Chan; Carole Pye, Patricia Harrington and Eva Wozniak. OSUCCG thanks Kevin Sweet, Caroline Craven, Julia Cooper, Michelle O’Conor and Amber Aeilts. BCAC is funded by Cancer Research UK [C1287/A16563, C1287/A10118], the European Union’s Horizon 2020 Research and Innovation Programme (grant numbers 634935 and 633784 for BRIDGES and B-CAST respectively), and by the European Community´s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). The EU Horizon 2020 Research and Innovation Programme funding source had no role in study design, data collection, data analysis, data interpretation or writing of the report. Genotyping of the OncoArray was funded by the NIH Grant U19 CA148065, and Cancer UK Grant C1287/A16563 and the PERSPECTIVE project supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research (grant GPH-129344) and, the Ministère de l’Économie, Science et Innovation du Québec through Genome Québec and the PSRSIIRI-701 grant, and the Quebec Breast Cancer Foundation. The Australian Breast Cancer Family Study (ABCFS) was supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The ABCFS was also supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation (Australia) and the Victorian Breast Cancer Research Consortium. J.L.H. is a National Health and Medical Research Council (NHMRC) Senior Principal Research Fellow. M.C.S. is a NHMRC Senior Research Fellow. The ABCS study was supported by the Dutch Cancer Society [grants NKI 2007-3839; 2009 4363]. The Australian Breast Cancer Tissue Bank (ABCTB) was supported by the National Health and Medical Research Council of Australia, The Cancer Institute NSW and the National Breast Cancer Foundation. The AHS study is supported by the intramural research program of the National Institutes of Health, the National Cancer Institute (grant number Z01-CP010119), and the National Institute of Environmental Health Sciences (grant number Z01-ES049030). The work of the BBCC was partly funded by ELAN-Fond of the University Hospital of Erlangen. The BBCS is funded by Cancer Research UK and Breast Cancer Now and acknowledges NHS funding to the NIHR Biomedical Research Centre, and the National Cancer Research Network (NCRN). The BCEES was funded by the National Health and Medical Research Council, Australia and the Cancer Council Western Australia. For the BCFR-NY, BCFR-PA, BCFR-UT this work was supported by grant UM1 CA164920 from the National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. BCINIS study was funded by the BCRF (The Breast Cancer Research Foundation, USA). The BREast Oncology GAlician Network (BREOGAN) is funded by Acción Estratégica de Salud del Instituto de Salud Carlos III FIS PI12/02125/Cofinanciado FEDER; Acción Estratégica de Salud del Instituto de Salud Carlos III FIS Intrasalud (PI13/01136); Programa Grupos Emergentes, Cancer Genetics Unit, Instituto de Investigacion Biomedica Galicia Sur. Xerencia de Xestion Integrada de Vigo-SERGAS, Instituto de Salud Carlos III, Spain; Grant 10CSA012E, Consellería de Industria Programa Sectorial de Investigación Aplicada, PEME I + D e I + D Suma del Plan Gallego de Investigación, Desarrollo e Innovación Tecnológica de la Consellería de Industria de la Xunta de Galicia, Spain; Grant EC11-192. Fomento de la Investigación Clínica Independiente, Ministerio de Sanidad, Servicios Sociales e Igualdad, Spain; and Grant FEDER-Innterconecta. Ministerio de Economia y Competitividad, Xunta de Galicia, Spain. The BSUCH study was supported by the Dietmar-Hopp Foundation, the Helmholtz Society and the German Cancer Research Center (DKFZ). Sample collection and processing was funded in part by grants from the National Cancer Institute (NCI R01CA120120 and K24CA169004). CBCS is funded by the Canadian Cancer Society (grant # 313404) and the Canadian Institutes of Health Research. CCGP is supported by funding from the University of Crete. The CECILE study was supported by Fondation de France, Institut National du Cancer (INCa), Ligue Nationale contre le Cancer, Agence Nationale de Sécurité Sanitaire, de l’Alimentation, de l’Environnement et du Travail (ANSES), Agence Nationale de la Recherche (ANR). The CGPS was supported by the Chief Physician Johan Boserup and Lise Boserup Fund, the Danish Medical Research Council, and Herlev and Gentofte Hospital. The American Cancer Society funds the creation, maintenance, and updating of the CPS-II cohort. The CTS was initially supported by the California Breast Cancer Act of 1993 and the California Breast Cancer Research Fund (contract 97-10500) and is currently funded through the National Institutes of Health (R01 CA77398, K05 CA136967, UM1 CA164917, and U01 CA199277). Collection of cancer incidence data was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885. The University of Westminster curates the DietCompLyf database funded by Against Breast Cancer Registered Charity No. 1121258 and the NCRN. The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by: Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation, the Stavros Niarchos Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia and Navarra, ISCIII RETIC (RD06/0020) (Spain); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (United Kingdom). The ESTHER study was supported by a grant from the Baden Württemberg Ministry of Science, Research and Arts. Additional cases were recruited in the context of the VERDI study, which was supported by a grant from the German Cancer Aid (Deutsche Krebshilfe). FHRISK is funded from NIHR grant PGfAR 0707-10031. The GC-HBOC (German Consortium of Hereditary Breast and Ovarian Cancer) is supported by the German Cancer Aid (grant no 110837, coordinator: Rita K. Schmutzler, Cologne). This work was also funded by the European Regional Development Fund and Free State of Saxony, Germany (LIFE - Leipzig Research Centre for Civilization Diseases, project numbers 713-241202, 713-241202, 14505/2470, 14575/2470). The GENICA was funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0 and 01KW0114, the Robert Bosch Foundation, Stuttgart, Deutsches Krebsforschungszentrum (DKFZ), Heidelberg, the Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, as well as the Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, Germany. The GEPARSIXTO study was conducted by the German Breast Group GmbH. The GESBC was supported by the Deutsche Krebshilfe e. V. [70492] and the German Cancer Research Center (DKFZ). The HABCS study was supported by the Claudia von Schilling Foundation for Breast Cancer Research, by the Lower Saxonian Cancer Society, and by the Rudolf Bartling Foundation. The HEBCS was financially supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer Society, and the Sigrid Juselius Foundation. The HMBCS was supported by a grant from the German Research Foundation (Do 761/10-1). The HUBCS was supported by a grant from the German Federal Ministry of Research and Education (RUS08/017), and by the Russian Foundation for Basic Research and the Federal Agency for Scientific Organizations for support the Bioresource collections and RFBR grants 14-04-97088, 17-29-06014 and 17-44-020498. E.K was supported by the program for support the bioresource collections №007-030164/2 and study was performed as part of the assignment of the Ministry of Science and Higher Education of Russian Federation (№АААА-А16-116020350032-1). Financial support for KARBAC was provided through the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet, the Swedish Cancer Society, The Gustav V Jubilee foundation and Bert von Kantzows foundation. The KARMA study was supported by Märit and Hans Rausings Initiative Against Breast Cancer. The KBCP was financially supported by the special Government Funding (EVO) of Kuopio University Hospital grants, Cancer Fund of North Savo, the Finnish Cancer Organizations, and by the strategic funding of the University of Eastern Finland. LMBC is supported by the ‘Stichting tegen Kanker’. DL is supported by the FWO. The MABCS study is funded by the Research Centre for Genetic Engineering and Biotechnology “Georgi D. Efremov” and supported by the German Academic Exchange Program, DAAD. The MARIE study was supported by the Deutsche Krebshilfe e.V. [70-2892-BR I, 106332, 108253, 108419, 110826, 110828], the Hamburg Cancer Society, the German Cancer Research Center (DKFZ) and the Federal Ministry of Education and Research (BMBF) Germany [01KH0402]. MBCSG is supported by grants from the Italian Association for Cancer Research (AIRC) and by funds from the Italian citizens who allocated the 5/1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects “5 × 1000”). The MCBCS was supported by the NIH grants CA192393, CA116167, CA176785 an NIH Specialized Program of Research Excellence (SPORE) in Breast Cancer [CA116201], and the Breast Cancer Research Foundation and a generous gift from the David F. and Margaret T. Grohne Family Foundation. MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further supported by Australian NHMRC grants 209057 and 396414, and by infrastructure provided by Cancer Council Victoria. Cases and their vital status were ascertained through the Victorian Cancer Registry (VCR) and the Australian Institute of Health and Welfare (AIHW), including the National Death Index and the Australian Cancer Database. The MEC was support by NIH grants CA63464, CA54281, CA098758, CA132839 and CA164973. The MISS study is supported by funding from ERC-2011-294576 Advanced grant, Swedish Cancer Society, Swedish Research Council, Local hospital funds, Berta Kamprad Foundation, Gunnar Nilsson. The MMHS study was supported by NIH grants CA97396, CA128931, CA116201, CA140286 and CA177150. MSKCC is supported by grants from the Breast Cancer Research Foundation and Robert and Kate Niehaus Clinical Cancer Genetics Initiative. The work of MTLGEBCS was supported by the Quebec Breast Cancer Foundation, the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program – grant # CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade – grant # PSR-SIIRI-701. The NBHS was supported by NIH grant R01CA100374. Biological sample preparation was conducted the Survey and Biospecimen Shared Resource, which is supported by P30 CA68485. The Northern California Breast Cancer Family Registry (NC-BCFR) and Ontario Familial Breast Cancer Registry (OFBCR) were supported by grant UM1 CA164920 from the National Cancer Institute (USA). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the USA Government or the BCFR. The Carolina Breast Cancer Study was funded by Komen Foundation, the National Cancer Institute (P50 CA058223, U54 CA156733, U01 CA179715), and the North Carolina University Cancer Research Fund. The NHS was supported by NIH grants P01 CA87969, UM1 CA186107, and U19 CA148065. The NHS2 was supported by NIH grants UM1 CA176726 and U19 CA148065. The ORIGO study was supported by the Dutch Cancer Society (RUL 1997-1505) and the Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL CP16). The PBCS was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. Genotyping for PLCO was supported by the Intramural Research Program of the National Institutes of Health, NCI, Division of Cancer Epidemiology and Genetics. The PLCO is supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, National Institutes of Health. The POSH study is funded by Cancer Research UK (grants C1275/A11699, C1275/C22524, C1275/A19187, C1275/A15956 and Breast Cancer Campaign 2010PR62, 2013PR044. PROCAS is funded from NIHR grant PGfAR 0707-10031. The RBCS was funded by the Dutch Cancer Society (DDHK 2004-3124, DDHK 2009-4318). SEARCH is funded by Cancer Research UK [C490/A10124, C490/A16561] and supported by the UK National Institute for Health Research Biomedical Research Centre at the University of Cambridge. The University of Cambridge has received salary support for PDPP from the NHS in the East of England through the Clinical Academic Reserve. The Sister Study (SISTER) is supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES049033). The Two Sister Study (2SISTER) was supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES044005 and Z01-ES102245), and, also by a grant from Susan G. Komen for the Cure, grant FAS0703856. SKKDKFZS is supported by the DKFZ. The SMC is funded by the Swedish Cancer Foundation and the Swedish Research Council [grant 2017-00644 for the Swedish Infrastructure for Medical Population-based Life-course Environmental Research (SIMPLER)]. The SZBCS is financially supported under the program of Minister of Science and Higher Education “Regional Initiative of Excellence” in years 2019-2022, Grant No 002/RID/2018/19. The TNBCC was supported by: a Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), a grant from the Breast Cancer Research Foundation, a generous gift from the David F. and Margaret T. Grohne Family Foundation. The UCIBCS component of this research was supported by the NIH [CA58860, CA92044] and the Lon V Smith Foundation [LVS39420]. The UKBGS is funded by Breast Cancer Now and the Institute of Cancer Research (ICR), London. ICR acknowledges NHS funding to the NIHR Biomedical Research Centre. The UKOPS study was funded by The Eve Appeal (The Oak Foundation) and supported by the National Institute for Health Research University College London Hospitals Biomedical Research Centre. The USRT Study was funded by Intramural Research Funds of the National Cancer Institute, Department of Health and Human Services, USA. CIMBA CIMBA: The CIMBA data management and data analysis were supported by Cancer Research – UK grants C12292/A20861, C12292/A11174. ACA is a Cancer Research -UK Senior Cancer Research Fellow. GCT and ABS are NHMRC Research Fellows. The PERSPECTIVE project was supported by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministry of Economy, Science and Innovation through Genome Québec, and The Quebec Breast Cancer Foundation. BCFR: UM1 CA164920 from the National Cancer Institute. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. BFBOCC: Lithuania (BFBOCC-LT): Research Council of Lithuania grant SEN-18/2015 and Nr. P-MIP-19-164. BIDMC: Breast Cancer Research Foundation. BMBSA: Cancer Association of South Africa (PI Elizabeth J. van Rensburg). CNIO: Spanish Ministry of Health PI16/00440 supported by FEDER funds, the Spanish Ministry of Economy and Competitiveness (MINECO) SAF2014-57680-R and the Spanish Research Network on Rare diseases (CIBERER). COH-CCGCRN: Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under grant number R25CA112486, and RC4CA153828 (PI: J. Weitzel) from the National Cancer Institute and the Office of the Director, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. CONSIT TEAM: Associazione Italiana Ricerca sul Cancro (AIRC; IG2014 no.15547) to P. Radice. Funds from Italian citizens who allocated the 5 × 1000 share of their tax payment in support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects ‘5 × 1000’) to S. Manoukian. UNIROMA1: Italian Association for Cancer Research (AIRC; grant no. 21389) to L. Ottini. DFKZ: German Cancer Research Center. EMBRACE: Cancer Research UK Grants C1287/A10118 and C1287/A11990. D. Gareth Evans and Fiona Lalloo are supported by an NIHR grant to the Biomedical Research Centre, Manchester (IS-BRC-1215-20007). The Investigators at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust are supported by an NIHR grant to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. Ros Eeles and Elizabeth Bancroft are supported by Cancer Research UK Grant C5047/A8385. Ros Eeles is also supported by NIHR support to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. FCCC: NIH/NCI grant P30-CA006927. The University of Kansas Cancer Center (P30 CA168524) and the Kansas Bioscience Authority Eminent Scholar Program. A.K.G. was funded by R0 1CA140323, R01 CA214545, and by the Chancellors Distinguished Chair in Biomedical Sciences Professorship. Ana Vega is supported by the Spanish Health Research Foundation, Instituto de Salud Carlos III (ISCIII), partially supported by FEDER funds through Research Activity Intensification Program (contract grant numbers: INT15/00070, INT16/00154, INT17/00133), and through Centro de Investigación Biomédica en Red de Enferemdades Raras CIBERER (ACCI 2016: ER17P1AC7112/2018); Autonomous Government of Galicia (Consolidation and structuring program: IN607B), and by the Fundación Mutua Madrileña (call 2018). GC-HBOC: German Cancer Aid (grant no 110837, Rita K. Schmutzler) and the European Regional Development Fund and Free State of Saxony, Germany (LIFE - Leipzig Research Centre for Civilization Diseases, project numbers 713-241202, 713-241202, 14505/2470, 14575/2470). GEMO: Ligue Nationale Contre le Cancer; the Association “Le cancer du sein, parlons-en!” Award, the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program, the French National Institute of Cancer (INCa) (grants AOR 01 082, 2013-1-BCB-01-ICH-1 and SHS-E-SP 18-015) and the Fondation ARC pour la recherche sur le cancer (grant PJA 20151203365). GEORGETOWN: the Survey, Recruitment and Biospecimen Shared Resource at Georgetown University (NIH/NCI grant P30-CA051008) and the Fisher Center for Hereditary Cancer and Clinical Genomics Research. HCSC: Spanish Ministry of Health PI15/00059, PI16/01292, and CB-161200301 CIBERONC from ISCIII (Spain), partially supported by European Regional Development FEDER funds. HEBCS: Helsinki University Hospital Research Fund, Academy of Finland (266528), the Finnish Cancer Society and the Sigrid Juselius Foundation. HEBON: the Dutch Cancer Society grants NKI1998-1854, NKI2004-3088, NKI2007-3756, the Netherlands Organization of Scientific Research grant NWO 91109024, the Pink Ribbon grants 110005 and 2014-187.WO76, the BBMRI grant NWO 184.021.007/CP46 and the Transcan grant JTC 2012 Cancer 12-054. HUNBOCS: Hungarian Research Grants KTIA-OTKA CK-80745 and NKFI_OTKA K-112228. HVH (University Hospital Vall d’Hebron) This work was supported by Spanish Instituto de Salud Carlos III (ISCIII) funding, an initiative of the Spanish Ministry of Economy and Innovation partially supported by European Regional Development FEDER Funds: FIS PI12/02585 and PI15/00355. ICO: The authors would like to particularly acknowledge the support of the Asociación Española Contra el Cáncer (AECC), the Instituto de Salud Carlos III (organismo adscrito al Ministerio de Economía y Competitividad) and “Fondo Europeo de Desarrollo Regional (FEDER), una manera de hacer Europa” (PI10/01422, PI13/00285, PIE13/00022, PI15/00854, PI16/00563, P18/01029, and CIBERONC) and the Institut Català de la Salut and Autonomous Government of Catalonia (2009SGR290, 2014SGR338, 2017SGR449, and PERIS Project MedPerCan), and CERCA program. IHCC: PBZ_KBN_122/P05/2004. ILUH: Icelandic Association “Walking for Breast Cancer Research” and by the Landspitali University Hospital Research Fund. INHERIT: Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program – grant # CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade – grant # PSR-SIIRI-701. IOVHBOCS: Ministero della Salute and “5 × 1000” Istituto Oncologico Veneto grant. IPOBCS: Liga Portuguesa Contra o Cancro. kConFab: The National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. MAYO: NIH grants CA116167, CA192393 and CA176785, an NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), and a grant from the Breast Cancer Research Foundation. MCGILL: Jewish General Hospital Weekend to End Breast Cancer, Quebec Ministry of Economic Development, Innovation and Export Trade. Marc Tischkowitz is supported by the funded by the European Union Seventh Framework Program (2007Y2013)/European Research Council (Grant No. 310018). MSKCC: the Breast Cancer Research Foundation, the Robert and Kate Niehaus Clinical Cancer Genetics Initiative, the Andrew Sabin Research Fund and a Cancer Center Support Grant/Core Grant (P30 CA008748). NCI: the Intramural Research Program of the US National Cancer Institute, NIH, and by support services contracts NO2-CP-11019-50, N02-CP-21013-63 and N02-CP-65504 with Westat, Inc, Rockville, MD. NNPIO: the Russian Foundation for Basic Research (grants 17-54-12007, 17-00-00171 and 18-515-45012). NRG Oncology: U10 CA180868, NRG SDMC grant U10 CA180822, NRG Administrative Office and the NRG Tissue Bank (CA 27469), the NRG Statistical and Data Center (CA 37517) and the Intramural Research Program, NCI. OSUCCG: was funded by the Ohio State University Comprehensive Cancer Center. PBCS: Italian Association of Cancer Research (AIRC) [IG 2013 N.14477] and Tuscany Institute for Tumors (ITT) grant 2014-2015-2016. SMC: the Israeli Cancer Association. SWE-BRCA: the Swedish Cancer Society. UCHICAGO: NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA125183), R01 CA142996, 1U01CA161032 and by the Ralph and Marion Falk Medical Research Trust, the Entertainment Industry Fund National Women’s Cancer Research Alliance and the Breast Cancer research Foundation. UCSF: UCSF Cancer Risk Program and Helen Diller Family Comprehensive Cancer Center. UKFOCR: Cancer Researc h UK. UPENN: National Institutes of Health (NIH) (R01-CA102776 and R01-CA083855; Breast Cancer Research Foundation; Susan G. Komen Foundation for the cure, Basser Research Center for BRCA. UPITT/MWH: Hackers for Hope Pittsburgh. VFCTG: Victorian Cancer Agency, Cancer Australia, National Breast Cancer Foundation. WCP: Dr Karlan is funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), Grant UL1TR000124.

Background . Pulmonary embolism (PE) is clinically suspected in many patients who complain of shortness of breath or chest pain due to its nonspecific nature. The prevalence of PE, however, is low in this population. To assist physicians in diagnostic decision making, several clinical decision rules (CDR) have been developed. The appropriate use of these CDRs has been proven to decrease the need for expensive, time consuming, and invasive diagnostic imaging procedures. In this study, the appropriateness of D-dimer and CT usage was investigated to rule out pulmonary emboli based on the simplified Geneva score. Methods . A retrospective review was performed on 74 patients with a CT scan ordered through a pulmonary embolism (PE) protocol. Using clinical data, the patients were stratified into “unlikely” and “likely” groups for the presence of PE based on the simplification of the revised Geneva score. Scores of 0-2 were graded as “unlikely” and scores of 3 or greater were “likely.” Results . There were 45/74 (60.8%) patients in the “unlikely” group. Of these, 14/45 (31.1%) received a D-dimer; eight were normal and six elevated. Only one patient in the elevated group had evidence of a PE. Of the remaining 31(39.2%) patients in the “unlikely” group that did not receive a D-dimer, only one had a PE. The “likely” group consisted of 29 (39.2%) patients of whom six received a D-dimer. Three patients had a normal D-dimer and three had an elevated level. Neither of these two groups had a PE. Of the remaining 23 (60.8%) in the “likely” group who did not receive a D-dimer, six had a PE. Conclusions . Diagnosing pulmonary emboli using D-dimer levels and CT scans may be aided by clinical decision rules such as the simplified Geneva system. This process may lead to more effective use of medical resources. KJM 2011; 4(4):99-104.

The authors report the development of a new metric for distributing university funds to support faculty efforts in education in the department of internal medicine at the University of Kansas School of Medicine. In 2003, a committee defined the educational value unit (EVU), which describes and measures the specific types of educational work done by faculty members, such as core education, clinical teaching, and administration of educational programs. The specific work profile of each faculty member was delineated. A dollar value was calculated for each 0.1 EVU. The metric was prospectively applied and a faculty survey was performed to evaluate the faculty’s perception of the metric. Application of the metric resulted in a decrease in university support for 34 faculty and an increase in funding for 23 faculty. Total realignment of funding was US$1.6 million, or an absolute value of US$29,072 38,320.00 in average shift of university salary support per faculty member. Survey results showed that understanding of the purpose of university funding was enhanced, and that faculty members perceived a more equitable alignment of teaching effort with funding. The EVU metric resulted in a dramatic realignment of university funding for educational efforts in the department of internal medicine. The metric was easily understood, quickly implemented, and perceived to be fair by the faculty. By aligning specific salary support with faculty’s educational responsibilities, a foundation was created for applying mission-based incentive programs. The rapidly changing environment of academic medicine continues to pose challenges to its leaders. Those responsible for allocating funding within academic medical centers face the pressures of limitations in resources related to decreased government funding for medical education and increasing demands on faculty time, along with increased demand for public accountability. 1 Increasingly, leaders of academic medical centers are recognizing the importance of developing systems that specifically assign resources in support of all academic missions, but especially the mission of educating students and residents. 2,3

The Surveying and Mapping community now has the benefit of real-time 3-dimensional coordinates at the centimetre level, through the Global Positioning System (GPS). The reference frame, World Geodetic System of 1984 (WGS84), within which a user ascertains these coordinates is essentially geocentric. In Jamaica all coordinate data and mapping are based on a non-geocentric coordinate system known as the Jamaican Datum of 1969 (JAD69), which like many others around the world was realized by making basic assumptions about the geoid-ellipsoid separation at the origin. WGS84 coordinates are therefore not compatible with the JAD69.This paper presents the results of work carried out to define the relationship between the two coordinate systems, through three types of transformation parameters, namely Block Shifts, Molodensky and Seven Parameter Similarity. Three of the forty-two primary control stations together with a Continuously Operating Reference Station (CORS), previously tied to the island network,...

We examined the ability of radiologists to detect pulmonary nodules in computed radiographic (CR) chest images subjected to lossy image compression. Low-contrast 1-cm diameter targets simulating noncalcified pulmonary nodules were introduced into clinical images and presented to ten radiologists in a series of two-alternative forced-choice (2AFC) observer experiments. The percentages of correct observer responses obtained while viewing noncompressed images (1:1) were compared with those obtained for the same images compressed 7:1, 16:1, 44:1, and 127:1. The images were compressed using a standard full-frame discrete cosine transform (DCT) technique. The degree of compression was determined by quantizing Fourier components in various frequency channels and then Huffman encoding the result. The data show a measurable decline in performance for each compression ratio. Through signal-to-noise ratio (SNR) analysis, we found that the reduction in performance was due primarily to the compression algorithm that increased image noise in the frequency channels of the signals to be detected.

The average size of acoustic scatterers and the integrated backscatter coefficient of kidney cortex were measured in vivo from 2-4 MHz for a group of 50 normal adult volunteers. Our goal was to determine the sensitivity of the ultrasonic measurements under clinical conditions by identifying biologic sources of estimation uncertainty. Based on 10 measurements on each kidney of each volunteer, the average glomerular diameter for the group was found to be 216 +/- 27 microns (SD). Glomerular size was found to correlate with body surface area (r = 0.4), and the ratio of glomerular surface area to body surface area (GSA/BSA) was found to be constant throughout normal adult life with GSA/BSA = (8.24 +/- 1.35) x 10(-8) (SD). These results are consistent with histologic analyses found in the literature. Within an individual, 7% standard errors in GSA/BSA are typical. Biologic variability dominates the variance in scatterer size estimates in a group not matched for BSA, where it accounts for 47% of the variance. In a group of individuals matched for BSA, biologic variability accounts for only 21% of the variance; day-to-day variability accounts for 35% of the variance; and experimental parameters account for the remainder. If a deviation greater than 2 x SD is considered abnormal, then this technique can potentially detect changes in glomerular diameter as small as 30 microns within an individual. To detect abnormal GSA/BSA values for an individual, GSA/BSA would have to differ from the mean for that group by about 3.6 x 10(-8) or about 40%. Therefore, at this time scatterer size estimates appear most reliable for tracking the progression of disease and treatment for an individual over time.

In helical portal venous blood flow, the usual laminar flow in the portal vein is replaced by a spiral. This changes the color Doppler ultrasound (US) appearance to one of alternating or parallel red and blue bands. Duplex US may appear to show hepatopetal, hepatofugal, or simultaneous bidirectional flow depending on placement of the cursor within the helix. Helical portal venous flow is unusual in normal individuals (2.2% of 135 patients). Its presence should prompt further scrutiny for signs of liver disease, particularly portosystemic shunts, as in 20% of 41 patients who subsequently underwent liver transplantation. It is a normal finding immediately after liver transplantation (43% of 35 patients) and transjugular intrahepatic portosystemic shunt (TIPS) creation (28% of 36 patients). In both liver transplant and TIPS recipients, helical flow is usually transient. Its persistence long after transplantation in association with a prolonged increase in portal venous velocity is a useful sign of portal vein stenosis. Helical flow may also occur in cases of neoplastic invasion or displacement of the portal vein.

Renal vascular resistance is an important feature of kidney function and disease. To maintain adequate blood flow, renal vascular resistance varies in response to changes in systemic pressure. Vascular resistance is largely determined by arteriolar diameter, which is regulated by local and systemic factors. We used quantitative ultrasound techniques to follow renal vascular changes in anesthetized dogs during local intraarterial infusion of a potent vasoconstrictor, endothelin-1 (ET-1). Average arteriolar diameters were estimated by analyzing echo-signal spectra (5–15 MHz) obtained from renal cortex in vivo before, during, and after ET-1 infusion. At calculated arterial concentrations of 0.01 nM, 0.1 nM, and 1.0 nM, ET-1 reduced the average arteriolar diameter of 38 ± 2 μm by 2%, 63%, and 91%, respectively, without producing a significant change in systemic blood pressure. Changes in scatterer size were consistent with the observed changes in renal hemodynamics detected using Doppler techniques. In addition, acoustic attenuation was found to increase with ET-1 concentration. These data suggest that quantitative ultrasound methods are sensitive to changes in renal arteriolar diameter, and may be a new noninvasive method for continuously monitoring changes in vascular resistance.

Contrast-detail (CD) analysis was used to compare the low-contrast detectability of computed radiography (CR) and screen-film (SF) as applied to the task of adult chest radiography. A phantom was constructed and imaged using the same exposure factors throughout all experiments. Within-observer variance, between-observer variance, and image sample variance were calculated and used to estimate the standard error for each experiment. The results of these CD experiments agreed with the predictions of the Rose model. Observers performed equally well for low-contrast target detection using CR and SF.

In the landmark document Crossing the Quality Chasm, the Institute of Medicine lists 6 aims of healthcare, one of which is that healthcare has to be effective. One means of improving the effectiveness of healthcare includes the creation of evidence-based guidelines to help streamline processes, decrease variability in care, and improve outcomes. Postoperative infection constitutes one of the most common preventable complications for surgical patients. The practice of administering perioperative antibiotics is currently being examined to determine the most effective approach to decrease the incidence of surgical site infections, improve resource utilization, and meet Surgical Care Improvement Project (SCIP) mandates. We utilized a tailored antibiotic prophylaxis form to help standardize perioperative antimicrobial use. The form was modified by a multidisciplinary antibiotic committee as new published clinical evidence or new SCIP guidelines were produced. We demonstrated a more than 90% compliance with SCIP core measures and significantly decreased the variability of antibiotic-ordering practices within our institution. Pharmacy savings are estimated at $8500 per year on surgical prophylaxis using the most commonly prescribed antimicrobials. Compliance with timely (within 1 hour prior to incision) antimicrobial administration is more than 90% but remains with high variability. Improvement in documentation may decrease the perceived inconsistencies in timing. Our results demonstrate that a multidisciplinary approach to managing perioperative prophylactic antimicrobial can be effective in decreasing clinical variability and costs of perioperative care, while increasing compliance with national mandates for antibiotic prescribing.

We have used an intracranial 9L rat brain tumor model to determine whether a novel metalloporphyrin, Mn[III] uroporphyrin I (MnUROP-I), could function as an intravenous MRI contrast agent for brain tumors. In several experiments, 24 male Fischer 344 rats were inoculated intracranially with 9L brain tumor cells. On day 15 postinoculation, animals were anesthetized and the femoral vein exposed. Prior to the intravenous injection of the contrast agent, a precontrast scan (1 Tesla in a standard head coil) was performed. Thirty min after injection of the contrast agent, a postcontrast scan was performed. Although there was only a suggestion of abnormality on the precontrast scans, the presence of tumor was visibly enhanced in the postcontrast scans. In 3 animals scanned at 24 hr postinjection, persistent tumor enhancement was demonstrated. Measured tumor sizes on the MRI scans were consistent with sizes measured at autopsy and histologically. These results demonstrate that MnUROP-I is an effective MRI contrast agent for the detection of an intracranial brain tumor in the rat model.

A teleradiology system acquires radiographic images at one location and transmits them to one or more remote sites, where they are displayed and/or converted to hard copy. These systems often employ wide area networks. Their goal is to provide improved radiologic services at all sites on the network. Experience in the use of teleradiology systems has demonstrated the need for a laser film digitizer, an optical disk, and a high-quality display and/or laser film printer at each site. Single-site hardware purchase costs average $196,000, plus an additional 20% for yearly network services. Hardware purchased for a consultation or central referral facility approximates $344,000.

We conducted a preliminary evaluation of a digital fluoroscopy system for general applications, including gastrointestinal imaging, venography, myelography, and genitourinary fluoroscopy. We describe the system, present examples of images obtained in a variety of applications, and assess the performance of the system.

Properties derived from acoustic backscatter measurements are examined to disclose sources of acoustic scattering in normal kidneys. The backscatter intensity from kidney parenchyma may be modeled using a two-component Gaussian correlation function. These two components yield effective scatterer size estimates of 220+or-15 mu m at low frequencies and 55+or-10 mu m at high frequencies, which correspond to the average glomerular and renal tubule diameters, respectively. A separate study using test media verifies the ability of the method to distinguish between mixtures of two different scattering structures from backscatter measurements at different frequencies. >

The goal of the study was to compare a cathode-ray-tube (CRT) digital display with film by using task-dependent image quality assessment methods. Contrast-detail analysis was utilized. Human observers performed a simple detection task, specifically, detecting a pillbox target in a uniform Poisson field, using either film or a digital display that employed a CRT monitor. Observers performed equally well on both film and CRT when the window settings of the digital display were established subjectively by a radiologist. Changing the window settings of the digital display to match the average background luminance of a film-illuminator combination decreased the luminance contrast of the targets and observer performance was reduced, though these effects were probably not linked. The "gold standard" film had lower luminance contrast than the CRT displayed images, yet observer performance was never lower for film than for the CRT. Therefore we concluded that luminance contrast was not a limiting factor for observer performance in this study. The CRT monitor changed fairly rapidly after it was calibrated. During a period of six months the gamma of the display increased from 1.82 to 2.42 and the maximum luminance decreased from 319 to 228 cd/m2. Low luminance output demonstrated a larger percentage decrease (approximately equal to 85%) than high luminance output (approximately equal to 29%) over the same time period. These observations suggest that standard window settings should be reviewed from time to time to ensure that the display is used optimally. No special look-up table setup such as perceptual linearization was used.

Three compression algorithms were compared by using contrast-detail (CD) analysis. Two phantoms were designed to simulate computed tomography (CT) scans of the head. The first was based on CT scans of a plastic cylinder containing water. The second was formed by combining a CT scan of a head with a scan of the water phantom. The soft tissue of the brainwas replaced by a subimage containing only water. The compression algorithms studied were the full-frame discrete cosine (FDCT) algorithm, the Joint Photographic Experts Group (JPEG) algorithm, and a wavelet algorithm. Both the wavelet and JPEG algorithms affected regions of the image near the boundary of the skull. The FDCT algorithm propagated false edges throughout the region interior to the skull. The wavelet algorithm affected the images less than the other compression algorithms. The presence of the skull especially affected observer performance on the FDCT compressed images. All of the findings demonstrated a flattening of the CD curve for large lesions. The results of a compression study using lossy compression algorithms is dependent on the characteristics ofthe image and the nature of the diagnostic task. Because of the high density bone of the skull, head CT images present a much more difficult compression problem than chest x-rays. We found no significant differences among the CD curves for the tested compression algorithms. Key Words: Image compression, contrast-detail analysis.

Many kidney disease processes begin with changes in the microscopic tissue structure, particularly the vasculature. Ultrasonic analysis can detect the changes [8, 6] that lead to earlier treatment and improved patient outcome. To characterize the microstructure, we estimate the average size of tissue scatterers D by analyzing the change in the backscatter coefficient σ(u) versus frequency u. The expression σ(u) = σ0 (u)Γ(u,D) summarizes the measurement technique, assuming the tissue structure is random [7]. An acoustic form factor is estimated from the echo spectrum using \( \hat \Gamma (u,D) = \sigma (u)/\sigma _0 (u) \). This estimate is compared to model functions Γ(u, D) for a range of D values. The model function that produces the smallest mean-square error when compared to the estimate \( \hat \Gamma \) determines the scatterer size estimate. Form factors provide a link between measurement and theory that may be used to estimate scatterer sizes for random media in the range of 25 µm to 400µm using diagnostic frequencies between 1 and 15 MHz.

Using free-response methodology, we measured the comparative performance of trained observers for the task of detecting simulated pulmonary nodules in computed radiographic chest images that were compressed using the full-frame discrete cosine transform algorithm. six observers read fifty-one images containing a total of 372 simulated lesions of size ranging from 8 mm to 12 mm and with six different contrasts. The images were compressed to an average of 15:1 with the same parameters that were used in an earlier two-alternative forced- choice analysis. The results showed this level of compression did not increase the number of false=positive calls per image. also, observers tended to ignore the lowest contrast nodules in all images. At low contrast we expect compression to have the greatest effect. Therefore, overall performance was not degraded by the compression process, although performance was compromised at very low contrast.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The ability of human observers to detect low-contrast targets in screen-film (SF) images, computed radiographic (CR) images, and compressed CR images was measured using contrast detail (CD) analysis. The results of these studies were used to design a two- alternative forced-choice (2AFC) experiment to investigate the detectability of nodules in adult chest radiographs. CD curves for a common screen-film system were compared with CR images compressed up to 125:1. Data from clinical chest exams were used to define a CD region of clinical interest that sufficiently challenged the observer. From that data, simulated lesions were introduced into 100 normal CR chest films, and forced-choice observer performance studies were performed. CR images were compressed using a full-frame discrete cosine transform (FDCT) technique, where the 2D Fourier space was divided into four areas of different quantization depending on the cumulative power spectrum (energy) of each image. The characteristic curve of the CR images was adjusted so that optical densities matched those of the SF system. The CD curves for SF and uncompressed CR systems were statistically equivalent. The slope of the CD curve for each was - 1.0 as predicted by the Rose model. There was a significant degradation in detection found for CR images compressed to 125:1. Furthermore, contrast-detail analysis demonstrated that many pulmonary nodules encountered in clinical practice are significantly above the average observer threshold for detection. We designed a 2AFC observer study using simulated 1-cm lesions introduced into normal CR chest radiographs. Detectability was reduced for all compressed CR radiographs.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Although receiver operating characteristic (ROC) analysis has been widely used for the evaluation of medical imaging systems, traditional ROC analysis can strictly be applied only to binary decision systems. As yet, no fully generalized ROC analysis has been developed to deal with the multiple alternative decision systems that are commonly encountered in the clinical setting. In this paper, we have developed a general method of analysis based on a Bayes decision framework applied to a multiple alternative decision model. As a simplified implementation of the general method, a K-nearest neighbor pattern classification strategy can be used. The application of this alternative operating characteristic analysis for the evaluation of two display formats for pediatric chest radiographs is demonstrated.

The efficiencies for detecting low-contrast circular targets in acoustic speckle fields are measured for human observers. Cone-shaped targets of known contrast were scanned in cross section at 5 MHz to generate B-scan images. Target images were paired with uniform speckle fields and presented to observers who were asked to identify which of the two images contained the target. In these two-alternative forced-choice (2AFC) observer experiments, the image date were specified exactly. Signal-to-noise ratios (SNR) defined the average observer performance. SNR values were computed from the fraction of correct observer responses and compared with the corresponding SNR for the ideal observer to estimate detection efficiencies. The average human-observer detection efficiency is approximately 50% for both positive- and negative-contrast targets. These results using commercial imaging systems are in basic agreement with those obtained previously using simulated images, although the added experimental uncertainty, particularly uncertainty about the exact position of the target, marginally decreased relative performance and increased observer variability

This study was performed to compare the performances of observers using three display formats for chest radiography. The display formats were conventional radiographs, digitized radiographs (2,048 X 2,048 X 12 bits) printed on laser film, and digitized radiographs (2,048 X 2,048 X 12 bits) displayed on a high-resolution (2,560 X 2,048 X 12-bit) gray-scale display. The test set for the study consisted of 163 cases. Sixty-four of the cases were normal, whereas the 99 remaining cases demonstrated one or more common radiographic abnormalities. Nine abnormalities were selected for analysis: costophrenic angle blunting, interstitial disease, atelectasis, pneumothorax, parenchymal mass, consolidation, obstructive disease, hilar/mediastinal mass, and apical scarring. Six experienced general radiologists participated in the evaluation. Receiver operating characteristic curves were generated for each abnormality and display format. The results indicate that, while the three display formats are equivalent for the detection of some abnormalities, detectable differences in observer performance may be seen even at 2,048 X 2,048 X 12 bits for the detection of obstructive disease, pneumothorax, interstitial disease, and parenchymal masses.

High resolution gray scale displays are being evaluated for the display of 2K x 2K x 12 bit digital images. A comparison has been analyzed for conventional chest radiographs, digitized chest radiographs (2K x 2K x 12 bits) printed on laser film, and a high resolution (2K x 2K x 12 bits) gray scale display. An initial study has been conducted comparing computed radiography laser printed films and an interactive 1K x 1K x 12 bit display.© (1990) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

Ultrasonography has a primary role in the imaging of biliary disease. Most cases are straightforward, but the authors emphasize unusual manifestations, uncommon diseases, and artifacts that may present diagnostic challenges. Issues in differential diagnosis are discussed for the following findings: internal gallbladder echoes (calculi vs tumefactive sludge, air, hematobilia, parasitic infestation, cholecystosis, neoplasia, and artifacts), gallbladder wall thickening (acute cholecystitis vs acalculous cholecystitis, artifacts, ascites, hypoalbuminemia, hepatitis, and sclerosing cholangitis), pericholecystic fluid (cholecystitis vs ascites, perforated ulcer, and trauma), bile duct dilatation (biliary obstruction vs sclerosing cholangitis, biliary air, anomalous portal system, biliary atresia, Caroli disease, and cholangiocarcinoma), perinatal and neonatal biliary disease, and sclerosing cholangitis.

Photostimulable phosphor radiographic (computed radiographic) systems are being installed and evaluated by radiology departments. The use of interactive image-processing workstations are a major advantage for any computed radiography system. An interactive image-processing workstation enables rapid image retrieval, reduces the examination repeat rate, provides for image enhancement, and rapidly sets the desired display parameters for laser-printed images. The authors have conducted over 2,500 radiographic examinations using a computed radiographic system equipped with an interactive image-processing workstation. Their experience supports the necessity of such a workstation.

Conventional arteriography and intraarterial digital subtraction arteriography (IADSA) were compared in 36 patients with primary bone or soft-tissue tumors of the extremities. The sensitivity of IADSA was at least equal to conventional arteriography for demonstrating normal or abnormal major arteries and feeding arteries, equal to or superior for depicting tumor stains or draining veins, but slightly inferior for revealing minute tumor vessels. An increase of the matrix size from 256 X 256 to 512 X 512 improved these sensitivities. IADSA with 15% diatrizoate contrast material eliminated the contrast material-induced pain in all patients. With a computer-controlled iris setting, an average of 5 minutes of procedure time and 1.7 R of radiation (0.44 mC kg) per examination could be saved. IADSA reduced the cost of an examination by an average of $67. The results indicate that IADSA was diagnostic in all instances and can replace conventional arteriography for the evaluation of extremity tumors.

This article is a tutorial on local area networks (LAN) for radiology applications. LANs are being implemented in radiology departments for the management of text and images, replacing the inflexible point-to-point wiring between two devices (computer-to-terminal). These networks enable the sharing of computers and computer devices, reduce equipment costs, and provide improved reliability. Any LAN must include items from the following four categories: transmission medium, topology, data transmission mode, and access protocol. Media for local area networks are twisted pair, coaxial, and optical fiber cables. The topology of these networks include the star, ring, bus, tree, and circuit-switching. Data transmission modes are either analog signals or digital signals. Access protocol methods include the broadcast bus system and the ring system. A performance measurement for a LAN is the throughput rate as a function of the number of active computer nodes. Standards for LANs help to ensure that products purchased from multiple manufacturers will operate successfully.

The design and implementation of a digital radiology image management system requires the definition, evaluation, and comparison of appropriate measures of system performance. The mean throughput rate is an important measure of the actual performance of a finished system. The mean throughput rate identifies the transmission of digital information either in bits/second or tasks/second. It is dependent on software, database management, equipment interface designs, number of users and display stations, and communications media. The mean throughput rate can document resource allocation bottlenecks within a given system. A model for estimating the mean throughput rate and its application in helping us design our radiology digital image networks is described.

During the past several years, image acquisition in nuclear medicine, computed tomography, ultrasonography, subtraction angiography, and magnetic resonance has been by digitization. Despite these advances, research in the development of digital imaging in conventional radiography has lagged behind. Although studies with a variety of digital techniques have been carried out on several fronts, we still do not possess a method that has captured the imagination of the majority of radiologists and other physicians to a point where it could replace conventional screen-film imaging. This article reviews the current status and general principles of the technology, focusing on the four digital radiographic techniques that have shown the greatest promise - film digitization, an image intensifier - based system, photostimulable phosphor plates, and a scanned projection system. The physical aspects of each of the four systems and the clinical results that have been reported to date, as well as the advantages and disadvantages of each system, are presented.

This article describes a method for generating gray scale analog hard copy images on ordinary paper using a laser printer system. Operation of the computer-controlled laser printer is described. The cost of the laser printer/paper technology is estimated and compared with the cost of multiformat camera/conventional film systems. Results of an initial clinical evaluation of laser printed paper images are presented.

Presented as an exhibit at the annual meeting of the American Roentgen Ray Society. Washington DC, April 1986. I Department of Diagnostic Radiology. The University of Kansas Medical Center, Rainbow Blvd. at 39th St. , Kansas City. KS 661 03. Address repnnt requests to K. A. Lee. 2 Department of Orthopedic Surgery. The University of Kansas Medical Center, Rainbow Blvd. at 39th St. . Kansas City. KS 66103. 329

In our experience the mortality rate in 46 patients who underwent angioinfarction for renal cell carcinoma was 4 per cent. Fever, ileus and leukocytosis were noted in 86 to 90 per cent of our patients. The use of absolute ethanol as a medium for renal infarction was associated with a significant incidence of damage to other organs. A 30 per cent decrease in tumor volume following angioinfarction using absorbable gelatin sponge and Gianturco coils was noted in 75 per cent of the patients. There was no evidence of metastatic tumor reduction and we could not document any significant decrease in operative time or blood loss. It would appear that there is some increased survival rate in patients with metastasis who are given adjuvant immune ribonucleic acid therapy. However, the numbers in our series are not significant to draw any definite conclusion. It is apparent that patients treated with infarction, delayed nephrectomy and medroxyprogesterone acetate did not have any significant survival over those treated with palliative nephrectomy or chemotherapy. The macrophage maturation assay may be useful during clinical followup.

A high resolution digital radiography system has been implemented using a microcomputer system and a wide field of view 57cm x-ray image intensifier tube. The microcomputer system provides for acquisition, display and manipulation, and archiving of 1024 x 1024 x 8 bit digital radiography images. Details of the high resolution digital radiography system are presented.

Description d'un reseau informatise pour l'acquisition, la transmission et l'archivage des images mis en œuvre dans un service hospitalier qui genere 1 gigaoctets d'images numeriquement formatees. Une image conventionnelle de 36×43 cm peut se remplacer par une matrice numerisee de 2048×2048 pixels

The term stroke denotes acute vascular and brain changes leading to rapid development of neurologic deficits. This condition was first described by Hippocrates as apoplexy, a term still in use today. The original Greek word, apoplexia, means to strike down —hence, the term stroke [1]. Hippocrates thought that the reason for apoplexy was hot blood vessels filled with white phlegm and black bile. Since Hip-pocrates’s time, a large body of knowledge about brain circulation, metabolism, and pathology has been acquired, especially over the last 30 years, and it is now well recognized that stroke may be caused by both intracranial and extracranial disease.

The development of image management systems for radiology departments raises many questions regarding the archiving of digitally formatted data. A study was conducted in our department to determine the short-term and long-term archiving requirements. This study was based upon the retrieval rates of patient film jackets archived in the departments film library.

Currently ultrasonic B-scan images combine many acoustic properties and imaging system parameters to form the image. It may, however, be advantageous to image acoustic properties individually or in select groups to obtain a more direct interpretation of the results. This report describes two methods of quantitative ultrasonic imaging which we are pursuing. The two methods are: single-feature parametric imaging and multi-feature tissue-type imaging. Trade-offs among contrast, noise, and spatial resolution using computer simulations and phantom measurements are discussed.© (1988) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

We have successfully interfaced an advanced microcomputer system to a 47-cm image intensifier for direct digital radiology. Our development effort has included the design and construction of hardware and the implementation of software. The system matrix (spatial resolution) is 1024 X 1024 and contrast resolution is 8 bits deep. A receiver-operator-characteristic analysis comparing conventional and digital laser chest radiographs for the detection of lung nodules demonstrated no statistical difference. Dosimetry measurements identified decreased patient dose. The intensifier-based digital imaging system is being increasingly used for a variety of examinations including IV pyelograms, all kinds of barium studies, and skeletal, trauma, and chest studies. Hard-copy laser-printed digital images with "bones black" are preferred by the radiology staff and have been well accepted by referring clinicians.

Atherosclerosis is by far the most common cause of stenosis and occlusion of the extracranial arteries. However, other pathological conditions can cause stenosis and occlusion of these vessels. These include: 1. Fibromuscular dysplasia 2. Dissecting aneurysms 3. Takayasu’s arteritis.

We are developing methods for imaging acoustic parameters individually to obtain a more direct interpretation of the scattering medium. Two properties of the medium that describe microscopic scattering structure have been accurately measured: the average scattering particle size and the product of the number density and the scattering strength. Analysis of quantitative images show increased image contrast by as much as 6 dB between regions that vary in these acoustic properties over that of conventional B-mode imaging. It is also possible to separate the effects of scatterer size from the effects of the number density and scattering strength. The motivation for developing these techniques for diagnostic ultrasound is to improve low-contrast detectability.

The requirements for implementing a radiology imaging network are described. Desirable features of such a network include: the ability to acquire approximately one gigabyte of digitally formatted data per day; data transmission rates of over 2 megabits per second; high resolution display systems with matrix sizes of at least 1280 x 1024 x 12 bits and screen display time of one-half second; archiving capacity for a data base totaling one terabyte; rapid generation of hard copy images upon demand; and compatability of the radiologic imaging network with the hospital information management system.

A digital 33-cm fluoroscopic system equipped with conventional spot-film and digital or video hard-copy capabilities was evaluated for its usefulness in diagnosing deep venous thrombosis of the lower extremities. The impact of different fluoroscopic field sizes, spatial resolution, and contrast variance was measured by using phantoms. The results indicate that the physical characteristics of the digital system are acceptable for lower-extremity venography. Digital fluoroscopic hard copy was compared with conventional spot films in 22 examinations. The digital examinations were as accurate as the conventional examinations. Procedure time, exposure to radiation, film costs, and repeated injections of contrast medium because of errors in exposure were reduced with the digital method. The need for extra technologists was eliminated. The advantages of digital radiographic displays, postprocessing, storage, and transmission were maximized. Digital fluoroscopic examinations were as accurate as conventional spot films and were found to have many advantages.