Comparison of T2 and FLAIR imaging for target delineation in high grade gliomas

<p>Abstract</p> <p>Background</p> <p>FLAIR and T2 weighted MRIs are used based on institutional preference to delineate high grade gliomas and surrounding edema for radiation treatment planning. Although these sequences have inherent physical differences there is limited data on the clinical and dosimetric impact of using either or both sequences.</p> <p>Methods</p> <p>40 patients with high grade gliomas consecutively treated between 2002 and 2008 of which 32 had pretreatment MRIs with T1, T2 and FLAIR available for review were selected for this study. These MRIs were fused with the treatment planning CT. Normal structures, clinical tumor volume (CTV) and planning tumor volume (PTV) were then defined on the T2 and FLAIR sequences. A Venn diagram analysis was performed for each pair of tumor volumes as well as a fractional component analysis to assess the contribution of each sequence to the union volume. For each patient the tumor volumes were compared in terms of total volume in cubic centimeters as well as anatomic location using a discordance index. The overlap of the tumor volumes with critical structures was calculated as a measure of predicted toxicity. For patients with MRI documented failures, the tumor volumes obtained using the different sequences were compared with the recurrent gross tumor volume (rGTV).</p> <p>Results</p> <p>The FLAIR CTVs and PTVs were significantly larger than the T2 CTVs and PTVs (p < 0.0001 and p = 0.0001 respectively). Based on the discordance index, the abnormality identified using the different sequences also differed in location. Fractional component analysis showed that the intersection of the tumor volumes as defined on both T2 and FLAIR defined the majority of the union volume contributing 63.6% to the CTV union and 82.1% to the PTV union. T2 alone uniquely identified 12.9% and 5.2% of the CTV and PTV unions respectively while FLAIR alone uniquely identified 25.7% and 12% of the CTV and PTV unions respectively. There was no difference in predicted toxicity to normal structures using T2 or FLAIR. At the time of analysis, 26 failures had occurred of which 19 patients had MRIs documenting the recurrence. The rGTV correlated best with the FLAIR CTV but the percentage overlap was not significantly different from that with T2. There was no statistical difference in the percentage overlap with the rGTV and the PTVs generated using either T2 or FLAIR.</p> <p>Conclusions</p> <p>Although both T2 and FLAIR MRI sequences are used to define high grade glial neoplasm and surrounding edema, our results show that the volumes generated using these techniques are different and not interchangeable. These differences have bearing on the use of intensity modulated radiation therapy (IMRT) and highly conformal treatment as well as on future clinical trials where the bias of using one technique over the other may influence the study outcome.</p

Intra- and inter-radiation therapist reproducibility of daily isocenter verification using prostatic fiducial markers

BACKGROUND: We sought to determine the intra- and inter-radiation therapist reproducibility of a previously established matching technique for daily verification and correction of isocenter position relative to intraprostatic fiducial markers (FM). MATERIALS AND METHODS: With the patient in the treatment position, anterior-posterior and left lateral electronic images are acquired on an amorphous silicon flat panel electronic portal imaging device. After each portal image is acquired, the therapist manually translates and aligns the fiducial markers in the image to the marker contours on the digitally reconstructed radiograph. The distances between the planned and actual isocenter location is displayed. In order to determine the reproducibility of this technique, four therapists repeated and recorded this operation two separate times on 20 previously acquired portal image datasets from two patients. The data were analyzed to obtain the mean variability in the distances measured between and within observers. RESULTS: The mean and median intra-observer variability ranged from 0.4 to 0.7 mm and 0.3 to 0.6 mm respectively with a standard deviation of 0.4 to 1.0 mm. Inter-observer results were similar with a mean variability of 0.9 mm, a median of 0.6 mm, and a standard deviation of 0.7 mm. When using a 5 mm threshold, only 0.5% of treatments will undergo a table shift due to intra or inter-observer error, increasing to an error rate of 2.4% if this threshold were reduced to 3 mm. CONCLUSION: We have found high reproducibility with a previously established method for daily verification and correction of isocenter position relative to prostatic fiducial markers using electronic portal imaging

Early observed transient prostate-specific antigen elevations on a pilot study of external beam radiation therapy and fractionated MRI guided High Dose Rate brachytherapy boost

PURPOSE: To report early observation of transient PSA elevations on this pilot study of external beam radiation therapy and magnetic resonance imaging (MRI) guided high dose rate (HDR) brachytherapy boost. MATERIALS AND METHODS: Eleven patients with intermediate-risk and high-risk localized prostate cancer received MRI guided HDR brachytherapy (10.5 Gy each fraction) before and after a course of external beam radiotherapy (46 Gy). Two patients continued on hormones during follow-up and were censored for this analysis. Four patients discontinued hormone therapy after RT. Five patients did not receive hormones. PSA bounce is defined as a rise in PSA values with a subsequent fall below the nadir value or to below 20% of the maximum PSA level. Six previously published definitions of biochemical failure to distinguish true failure from were tested: definition 1, rise >0.2 ng/mL; definition 2, rise >0.4 ng/mL; definition 3, rise >35% of previous value; definition 4, ASTRO defined guidelines, definition 5 nadir + 2 ng/ml, and definition 6, nadir + 3 ng/ml. RESULTS: Median follow-up was 24 months (range 18–36 mo). During follow-up, the incidence of transient PSA elevation was: 55% for definition 1, 44% for definition 2, 55% for definition 3, 33% for definition 4, 11% for definition 5, and 11% for definition 6. CONCLUSION: We observed a substantial incidence of transient elevations in PSA following combined external beam radiation and HDR brachytherapy for prostate cancer. Such elevations seem to be self-limited and should not trigger initiation of salvage therapies. No definition of failure was completely predictive

Optimal Lifestyle Components in Young Adulthood Are Associated With Maintaining the Ideal Cardiovascular Health Profile Into Middle Age

BACKGROUND: Middle-aged adults with ideal blood pressure, cholesterol, and glucose levels exhibit substantially lower cardiovascular mortality than those with unfavorable levels. Four healthy lifestyle components-optimal body weight, diet, physical activity, and not smoking-are recommended for cardiovascular health (CVH). This study quantified associations between combinations of healthy lifestyle components measured in young adulthood and loss of the ideal CVH profile into middle age. METHODS AND RESULTS: Analyses included 2164 young adults in the Coronary Artery Risk Development in Young Adults study with the ideal CVH profile (defined as untreated blood pressure <120/80 mm Hg, total cholesterol <200 mg/dL, fasting blood glucose <100 mg/dL, and absence of cardiovascular disease) at baseline. Cox proportional hazards regression models estimated hazard ratios for loss of the ideal CVH profile over 25 years according to 4 individual and 16 combinations of optimal healthy lifestyle components measured in young adulthood: body mass index, physical activity, nonsmoking status, and diet quality. Models were adjusted for age, sex, race, education, study center, and baseline blood pressure, cholesterol, and glucose. Eighty percent (n=1737) of participants lost the ideal CVH profile by middle age; loss was greatest for young adults with no optimal healthy lifestyle components at baseline. Relative to young adults with no optimal healthy lifestyle components, those with all 4 were less likely to lose the ideal CVH profile (hazard ratio 0.59, 95% CI 0.44-0.80). Combinations that included optimal body mass index and nonsmoking status were each associated with lower risk. CONCLUSIONS: Optimal body mass index and not smoking in young adulthood were protective against loss of the ideal CVH profile through middle age. Importance of diet and physical activity may be included through their effects on healthy weight

Distinct 'Immuno-Allertypes' of Disease and High Frequencies of Sensitisation in Non-Cystic-Fibrosis Bronchiectasis

Rationale: Allergic sensitization is associated with poor clinical outcomes in asthma, chronic obstructive pulmonary disease, and cystic fibrosis; however, its presence, frequency, and clinical significance in non–cystic fibrosis bronchiectasis remain unclear. Objectives: To determine the frequency and geographic variability that exists in a sensitization pattern to common and specific allergens, including house dust mite and fungi, and to correlate such patterns to airway immune-inflammatory status and clinical outcomes in bronchiectasis. Methods: Patients with bronchiectasis were recruited in Asia (Singapore and Malaysia) and the United Kingdom (Scotland) (n = 238), forming the Cohort of Asian and Matched European Bronchiectasis, which matched recruited patients on age, sex, and bronchiectasis severity. Specific IgE response against a range of common allergens was determined, combined with airway immune-inflammatory status and correlated to clinical outcomes. Clinically relevant patient clusters, based on sensitization pattern and airway immune profiles (“immunoallertypes”), were determined. Measurements and Main Results: A high frequency of sensitization to multiple allergens was detected in bronchiectasis, exceeding that in a comparator cohort with allergic rhinitis (n = 149). Sensitization was associated with poor clinical outcomes, including decreased pulmonary function and more severe disease. “Sensitized bronchiectasis” was classified into two immunoallertypes: one fungal driven and proinflammatory, the other house dust mite driven and chemokine dominant, with the former demonstrating poorer clinical outcome. Conclusions: Allergic sensitization occurs at high frequency in patients with bronchiectasis recruited from different global centers. Improving endophenotyping of sensitized bronchiectasis, a clinically significant state, and a “treatable trait” permits therapeutic intervention in appropriate patients, and may allow improved stratification in future bronchiectasis research and clinical trials.Ministry of Education (MOE)Ministry of Health (MOH)National Medical Research Council (NMRC)Published versionSupported by the Singapore Ministry of Health’s National Medical Research Council under its Transition Award NMRC/TA/0048/2016 (S.H.C.) and Changi General Hospital Research grant CHF2016.03-P (T.B.L.). The work performed at NUS was supported by the Singapore Ministry of Education Academic Research Fund, SIgN, and National Medical Research Council grants N-154-000-038-001, R-154-000-404-112, R-154-000-553-112, R-154-000-565-112, R-154-000-630-112, R-154-000-A08-592, R-154-000-A27-597, SIgN-06-006, SIgN-08-020, and NMRC/1150/2008 (F.T.C.); J.D.C. is supported by the GSK/British Lung Foundation Chair of Respiratory Research

Genome of the Netherlands population-specific imputations identify an ABCA6 variant associated with cholesterol levels

This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. Acknowledgements: We especially thank all volunteers who participated in our study. This study made use of data generated by the ‘Genome of the Netherlands’ project, which is funded by the Netherlands Organization for Scientific Research (grant no. 184021007). The data were made available as a Rainbow Project of BBMRI-NL. Samples were contributed by LifeLines (http://lifelines.nl/lifelines-research/general), the Leiden Longevity Study (http://www.healthy-ageing.nl; http://www.langleven.net), the Netherlands Twin Registry (NTR: http://www.tweelingenregister.org), the Rotterdam studies (http://www.erasmus-epidemiology.nl/rotterdamstudy) and the Genetic Research in Isolated Populations programme (http://www.epib.nl/research/geneticepi/research.html#gip). The sequencing was carried out in collaboration with the Beijing Institute for Genomics (BGI). Cardiovascular Health Study: This CHS research was supported by NHLBI contracts HHSN268201200036C, HHSN268200800007C, HHSN268200960009C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086; and NHLBI grants HL080295, HL087652, HL105756 and HL103612 with additional contribution from the National Institute of Neurological Disorders and Stroke (NINDS). Additional support was provided through AG023629 from the National Institute on Aging (NIA). A full list of CHS investigators and institutions can be found at http://www.chs-nhlbi.org/pi.htm. The CROATIA cohorts would like to acknowledge the invaluable contributions of the recruitment teams in Vis, Korcula and Split (including those from the Institute of Anthropological Research in Zagreb and the Croatian Centre for Global Health at the University of Split), the administrative teams in Croatia and Edinburgh and the people of Vis, Korcula and Split. SNP genotyping was performed at the Wellcome Trust Clinical Research Facility in Edinburgh for CROATIA-Vis, by Helmholtz Zentrum München, GmbH, Neuherberg, Germany for CROATIA-Korcula and by AROS Applied Biotechnology, Aarhus, Denmark for CROATIA-Split. They would also like to thank Jared O’Connell for performing the pre-phasing for all cohorts before imputation. The ERF study as a part of EuroSPAN (European Special Populations Research Network) was supported by European Commission FP-6 STRP grant number 018947 (LSHG-CT-2006-01947) and also received funding from the European Community's Seventh Framework Programme (FP7/2007-2013)/grant agreement HEALTH-F4-2007-201413 by the European Commission under the programme ‘Quality of Life and Management of the Living Resources’ of 5th Framework Programme (no. QLG2-CT-2002-01254). High-throughput analysis of the ERF data was supported by joint grant from the Netherlands Organisation for Scientific Research and the Russian Foundation for Basic Research (NWO-RFBR 047.017.043). This research was financially supported by BBMRI-NL, a Research Infrastructure financed by the Dutch government (NWO 184.021.007). Statistical analyses for the ERF study were carried out on the Genetic Cluster Computer (http://www.geneticcluster.org), which is financially supported by the Netherlands Scientific Organization (NWO 480-05-003 PI: Posthuma) along with a supplement from the Dutch Brain Foundation and the VU University Amsterdam. We are grateful to all study participants and their relatives, general practitioners and neurologists for their contributions and to P. Veraart for her help in genealogy, J. Vergeer for the supervision of the laboratory work and P. Snijders for his help in data collection. The FamHS is funded by a NHLBI grant 5R01HL08770003, and NIDDK grants 5R01DK06833603 and 5R01DK07568102. The Framingham Heart Study SHARe Project for GWAS scan was supported by the NHLBI Framingham Heart Study (Contract No. N01-HC-25195) and its contract with Affymetrix Inc for genotyping services (Contract No. N02-HL-6-4278). DNA isolation and biochemistry were partly supported by NHLBI HL-54776. A portion of this research utilized the Linux Cluster for Genetic Analysis (LinGA-II) funded by the Robert Dawson Evans Endowment of the Department of Medicine at the Boston University School of Medicine and Boston Medical Center. We are grateful to Han Chen for conducting the 1000G imputation. The Family Heart Study was supported by the by grants R01-HL-087700 and R01-HL-088215 from the National Heart, Lung, and Blood Institute (NHLBI). We would like to acknowledge the invaluable contributions of the families who took part in the Generation Scotland: Scottish Family Health Study, the general practitioners and Scottish School of Primary Care for their help in recruiting them, and the whole Generation Scotland team, which includes academic researchers, IT staff, laboratory technicians, statisticians and research managers. SNP genotyping was performed at the Wellcome Trust Clinical Research Facility in Edinburgh. GS:SFHS is funded by the Scottish Executive Health Department, Chief Scientist Office, grant number CZD/16/6. SNP genotyping was funded by the Medical Research Council, United Kingdom. We wish to acknowledge the services of the LifeLines Cohort Study, the contributing research centres delivering data to LifeLines and all the study participants. MESA Whites and the MESA SHARe project are conducted and supported by contracts N01-HC-95159 through N01-HC-95169 and RR-024156 from the NHLBI. Funding for MESA SHARe genotyping was provided by NHLBI Contract N02.HL.6.4278. MESA Family is conducted and supported in collaboration with MESA investigators; support is provided by grants and contracts R01HL071051, R01HL071205, R01HL071250, R01HL071251, R01HL071252, R01HL071258 and R01HL071259. We thank the participants of the MESA study, the Coordinating Center, MESA investigators and study staff for their valuable contributions. A full list of participating MESA investigators and institutions can be found at http://www.mesa-nhlbi.org. Netherland Twin Register (NTR) and Netherlands Study of Depression and Anxiety (NESDA): Funding was obtained from the Netherlands Organization for Scientific Research (NWO) and MagW/ZonMW grants Middelgroot-911-09-032, Spinozapremie 56-464-14192, Geestkracht programme of the Netherlands Organization for Health Research and Development (Zon-MW, grant number 10-000-1002), Center for Medical Systems Biology (CSMB, NWO Genomics), NBIC/BioAssist/RK(2008.024), Biobanking and Biomolecular Resources Research Infrastructure (BBMRI-NL, 184.021.007), VU University’s Institute for Health and Care Research (EMGO+) and Neuroscience Campus Amsterdam (NCA); the European Science Foundation (ESF, EU/QLRT-2001-01254), the European Community’s Seventh Framework Program (FP7/2007-2013), ENGAGE (HEALTH-F4-2007-201413); the European Science Council (ERC Advanced, 230374); and the European Research Council (ERC-284167). Part of the genotyping and analyses were funded by the Genetic Association Information Network (GAIN) of the Foundation for the National Institutes of Health, Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06), the Avera Institute, Sioux Falls, South Dakota (USA) and the National Institutes of Health (NIH R01 HD042157-01A1, MH081802, Grand Opportunity grants 1RC2 MH089951 and 1RC2 MH089995). PREVEND genetics is supported by the Dutch Kidney Foundation (Grant E033), the EU project grant GENECURE (FP-6 LSHM CT 2006 037697), the National Institutes of Health (grant 2R01LM010098), The Netherlands Organisation for Health Research and Development (NWO-Groot grant 175.010.2007.006, NWO VENI grant 916.761.70, ZonMw grant 90.700.441) and the Dutch Inter University Cardiology Institute Netherlands (ICIN). The PROSPER study was supported by an investigator-initiated grant obtained from Bristol-Myers Squibb. J.W.J is an Established Clinical Investigator of the Netherlands Heart Foundation (grant 2001 D 032). Genotyping was supported by the seventh framework programme of the European commission (grant 223004) and by the Netherlands Genomics Initiative (Netherlands Consortium for Healthy Aging grant 050-060-810). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, Netherlands Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII) and the Municipality of Rotterdam. We are grateful to the study participants, the staff from the Rotterdam Study and the participating general practitioners and pharmacists. The generation and management of GWAS genotype data for the Rotterdam Study is supported by the Netherlands Organisation of Scientific Research NWO Investments (nr. 175.010.2005.011, 911-03-012). This study is funded by the Research Institute for Diseases in the Elderly (014-93-015; RIDE2), the Netherlands Genomics Initiative (NGI)/Netherlands Organisation for Scientific Research (NWO) project no. 050-060-810. We thank Pascal Arp, Mila Jhamai, Marijn Verkerk, Lizbeth Herrera and Marjolein Peters for their help in creating the GWAS database.Peer reviewedPublisher PD

Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies

Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria

Publisher Copyright: © 2019, The Author(s).Increased levels of the urinary albumin-to-creatinine ratio (UACR) are associated with higher risk of kidney disease progression and cardiovascular events, but underlying mechanisms are incompletely understood. Here, we conduct trans-ethnic (n = 564,257) and European-ancestry specific meta-analyses of genome-wide association studies of UACR, including ancestry- and diabetes-specific analyses, and identify 68 UACR-associated loci. Genetic correlation analyses and risk score associations in an independent electronic medical records database (n = 192,868) reveal connections with proteinuria, hyperlipidemia, gout, and hypertension. Fine-mapping and trans-Omics analyses with gene expression in 47 tissues and plasma protein levels implicate genes potentially operating through differential expression in kidney (including TGFB1, MUC1, PRKCI, and OAF), and allow coupling of UACR associations to altered plasma OAF concentrations. Knockdown of OAF and PRKCI orthologs in Drosophila nephrocytes reduces albumin endocytosis. Silencing fly PRKCI further impairs slit diaphragm formation. These results generate a priority list of genes and pathways for translational research to reduce albuminuria.Peer reviewe