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8,155 results on '"Otto, S."'

2. Pandemi og gjennomføring av videregående opplæring

Author

Otto S. Lillebø, Asgeir Skålholt, and Marianne Takvam Kindt

Subjects
covid-19, videregående opplæring, frafall, overgang til høyere utdanning, Covid-19, upper secondary, Social sciences (General), H1-99
Abstract

Karaktergjennomsnitt og gjennomføringsgrad i videregående skole har økt under koronapandemien. Samtidig viser internasjonale studier at læringstapet under pandemien har vært stort, særlig for elever med lav sosioøkonomisk bakgrunn. Betyr det at vi har en situasjon der elever fullfører videregående opplæring uten egentlig å være studieforberedt? I denne artikkelen analyserer vi registerdata for å undersøke endringer i gjennomføring av studieforberedende utdanningsprogram på videregående skole for ulike grupper av elever under pandemien. Vi ser også på hvordan overgangen til arbeid og utdanning har utviklet seg for disse gruppene. Våre funn tyder på to sentrale ting. For det første ser vi at elever med svake karakterer i større grad klarte å fullføre og bestå videregående opplæring under pandemien. For det andre virker det som at disse elevene faktisk omsetter vitnemålet sitt til deltagelse i høyere utdanning. Hvorvidt denne deltagelsen resulterer i positive utdannings- og arbeidsmarkedsutfall på lengre sikt, er det for tidlig å si noe om.

Published
2024
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3. A multi-Physics Experiment for Low-Yield Nuclear Explosion Monitoring

Author

Myers, S, primary, Abbott, G, additional, Alexander, T, additional, Alger, E, additional, Alvarez, A, additional, Annabelle, N, additional, Antoun, T, additional, Auld, G, additional, Malach, A, additional, Banuelos, H, additional, Barela, M, additional, Barnhart, T, additional, Barrow, P, additional, Bartlett, T, additional, Bockman, A, additional, Bodmer, M, additional, Bogolub, K, additional, Bonner, J, additional, Borden, R, additional, Boukhalfa, H, additional, Bowman, D, additional, Britt, C, additional, Broman, B, additional, Broome, S, additional, Brown, B, additional, Burghardt, J, additional, Chester, D, additional, Choens, C, additional, Chojnicki, K, additional, Churby, A, additional, Cole, J, additional, Coleman, T, additional, Collard, J, additional, Couture, A, additional, Crosby, G, additional, Cruz-Cabrera, A, additional, D'Saint Angelo, D, additional, Dea, M, additional, Dekin, W, additional, DeVisser, B, additional, Dietel, M, additional, Downs, C, additional, Downs, N, additional, Dzenitis, E, additional, Eckert, E, additional, Eras, S, additional, Euler, G, additional, Ezzedine, S, additional, Fast, J, additional, Feldman, J, additional, Featherston, K, additional, Foxe, M, additional, Freimuth, C, additional, Fritz, B, additional, Galvin, G, additional, Gamboa, S, additional, Garner, L, additional, Gascoigne, T, additional, Gastelum, J, additional, Gaylord, J, additional, Gessey, D, additional, Glasgow, B, additional, Glavin, G, additional, Glomski, A, additional, Goodwin, M, additional, Green, D, additional, Griego, J, additional, Grover, S, additional, Gutierrez, J, additional, Haas, D, additional, Hall, R, additional, Hall, A, additional, Hardy, D, additional, Hauk, D, additional, Heath, J, additional, Holand, A, additional, Holdcroft, J, additional, Holland, A, additional, Honjas, W, additional, Howard, K, additional, Hudson, C, additional, Ingraham, M, additional, Jaramillo, J, additional, Jenkins, A, additional, Johnson, C, additional, Jones, K, additional, Falliner, F, additional, Junor, W, additional, Keillor, M, additional, Kent, G, additional, Keogh, M, additional, Kibikas, W, additional, Kleadbeater, K, additional, Knox, H, additional, Knox, J, additional, Kuhlman, K, additional, Kwiatkowski, C, additional, Laintz, K, additional, Lapka, J, additional, Larotonda, J, additional, Layne, J, additional, Ledoux, N, additional, Li, S, additional, Linneman, D, additional, Lipkowitz, P, additional, MacLeod, G, additional, McCann, E, additional, McCombe, R, additional, Meierbachtol, C, additional, Mellors, R, additional, Memmott, B, additional, Mendenhall, W, additional, Mendez, J, additional, Miller, X, additional, Miller, A, additional, Miranda, F, additional, Montano, M, additional, Moore, M, additional, Morris, J, additional, Munley, W, additional, Murillo, E, additional, Myers, T, additional, Navarro, A, additional, Nippress, S, additional, Otto, S, additional, Peacock, S, additional, Pemberton, S, additional, Perea, R, additional, Peterson, J, additional, Pierre-Yves, L, additional, Plank, G, additional, Podrasky, A, additional, Podrasky, D, additional, Pope, J, additional, Poskey, M, additional, Powell, M, additional, Price, A, additional, Puyleart, A, additional, Quintana, B, additional, Rahn, T, additional, Rendon, C, additional, Reppart, J, additional, Rico, H, additional, Roberts, B, additional, Robey, E, additional, Rodd, R, additional, Rodriguez, M, additional, Rogall, A, additional, Romanczuk, A, additional, Roth, M, additional, Salyer, G, additional, Savran, B, additional, Schalk, W, additional, Seifert, C, additional, Seitz, D, additional, Shao, X, additional, Sirota, D, additional, Slack, J, additional, Slater, D, additional, Smith, K, additional, Smith, D, additional, Spears, B, additional, Sprinkle, D, additional, Stead, R, additional, Stephens, M, additional, Strickland, C, additional, Tafoya, A, additional, Tafoya, J, additional, Tagoe, M, additional, Taguba, C, additional, Tarnecki, L, additional, Tatge, R, additional, Teich-McGoldrick, S, additional, Terry, B, additional, Thompson, R, additional, Townsend, M, additional, Tubbs, G, additional, Turley, R, additional, Valdez, N, additional, Van Morris, A, additional, Vergara, S, additional, Vigil, J, additional, Villanueva, J, additional, Vorobiev, O, additional, Wallace, D, additional, Walrath, T, additional, Wharton, S, additional, White, R, additional, White, H, additional, Whitehill, A, additional, Williams, M, additional, Wilson, J, additional, Wood, L, additional, Wright, C, additional, Wright, A, additional, Xu, G, additional, Yang, X, additional, Yost, R, additional, and Zeiler, C, additional

Published
2024
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5. Spatial concordance of DNA methylation classification in diffuse glioma

Author

Verburg, Niels, Barthel, Floris P, Anderson, Kevin J, Johnson, Kevin C, Koopman, Thomas, Yaqub, Maqsood M, Hoekstra, Otto S, Lammertsma, Adriaan A, Barkhof, Frederik, Pouwels, Petra JW, Reijneveld, Jaap C, Rozemuller, Annemieke JM, Beliën, Jeroen AM, Boellaard, Ronald, Taylor, Michael D, Das, Sunit, Costello, Joseph F, Vandertop, William Peter, Wesseling, Pieter, de Witt Hamer, Philip C, and Verhaak, Roel GW

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Rare Diseases, Brain Cancer, Clinical Research, Neurosciences, Cancer, Orphan Drug, Genetics, Human Genome, Biomedical Imaging, Brain Disorders, Adult, Brain Neoplasms, DNA Methylation, Glioma, Humans, Isocitrate Dehydrogenase, Mutation, Oligodendroglioma, DNA methylation classification, epigenetics, glioma, imaging, intratumoral heterogeneity, Oncology & Carcinogenesis, Oncology and carcinogenesis
Abstract

BackgroundIntratumoral heterogeneity is a hallmark of diffuse gliomas. DNA methylation profiling is an emerging approach in the clinical classification of brain tumors. The goal of this study is to investigate the effects of intratumoral heterogeneity on classification confidence.MethodsWe used neuronavigation to acquire 133 image-guided and spatially separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma (7 IDH-wildtype and 2 IDH-mutant glioblastoma, 6 diffuse astrocytoma, IDH-mutant and 1 oligodendroglioma, IDH-mutant and 1p19q codeleted), which we characterized using DNA methylation arrays. Samples were obtained from regions with and without abnormalities on contrast-enhanced T1-weighted and fluid-attenuated inversion recovery MRI. Methylation profiles were analyzed to devise a 3-dimensional reconstruction of (epi)genetic heterogeneity. Tumor purity was assessed from clonal methylation sites.ResultsMolecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and explains a substantial part of apparent epigenetic spatial heterogeneity. We observed that DNA methylation subtypes are often, but not always, conserved in space taking tumor purity and prediction accuracy into account.ConclusionOur results underscore the infiltrative nature of diffuse gliomas and suggest that DNA methylation subtypes are relatively concordant in this tumor type, although some heterogeneity exists.

Published
2021

9. Surgical approach had minor association with femoral stem migration in total hip arthroplasty: radiostereometric analysis of 61 patients after 5-year follow-up

Author

Kristin Haugan, Olav A Foss, Otto S Husby, Vigdis S Husby, Svein Svenningsen, and Siri B Winther

Subjects
Anterior approach, Arthroplasty, Direct lateral approach, Gladiator femoral stem, Hip, Implants, Orthopedic surgery, RD701-811
Abstract

Background and purpose: Total hip arthroplasty (THA) is usually performed using 1 of 3 surgical approaches: direct lateral (DLA), posterior (PA), or anterior (AA). AA is different from DLA and PA owing to limited intraoperative visibility of the femoral canal. This could affect stem positioning and therefore migration. We aimed to perform an exploratory radiostereometric analysis (RSA) study with 3 groups for surgical approach assessing stem migration up to 5 years postoperatively. Patients and methods: 61 patients with unilateral osteoarthritis of the hip were included. 21 patients were allocated to the DLA, 20 to the PA, and 20 to the AA group. All patients received an uncemented, collarless, double-tapered, fully hydroxyapatite-coated Profemur Gladiator stem. Migration was measured with model-based RSA. Baseline RSA was on day 1 postoperatively. The follow-ups were at day 8, at 5 weeks, and at 3, 6, 12, 24, and 60 months after surgery. Generalized linear mixed models were used to analyze maximum total point motion (MTPM) migrations. Results: Group mean differences in MTPM were 0.4 mm (95% confidence interval [CI] –1.5 to 2.4) for DLA vs. PA, 1.1 mm (CI –1.0 to 3.3) for AA vs. DLA, and 1.6 mm (CI –0.8 to 3.9) for AA vs. PA, when adjusted for sex and age as covariates. 2 stems in the AA group had excessive early migration. For all stems the migrations occurred mainly within 5-week follow-up and then stabilized. Conclusion: At 5-year follow-up, there were no statistically significant differences in stem migration associated with the 3 surgical approaches used in this study.

Published
2023
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10. The extent of first-time THA revision is not associated with patient-reported outcomes at 1-year follow-up: a study of 426 aseptic revisions

Author

Siri B Winther, Jomar Klaksvik, Olav A Foss, Tina Strømdal Wik, Tarjei Egeberg, and Otto S Husby

Subjects
Arthroplasty, Hip, PROMs, Revision, Orthopedic surgery, RD701-811
Abstract

Background and purpose: Studies evaluating pain and patient-reported outcome measures (PROMs) related to type of revision total hip arthroplasty (rTHA) are sparse. Our aim was to compare pain, physical function, quality of life, and patient satisfaction among different types of aseptic rTHA at 1-year follow-up. Patients and methods: We performed a retrospective study from an institutional registry with 426 primary THAs scheduled for rTHA in a fast-track setting between 2012 and 2021. Revisions were grouped by 4 types of surgery: head and/or liner exchange, cup revision, stem revision, and cup and stem revision. Pain during mobilization and at rest (NRS 0–10), physical function (HOOS-PS and HHS) and health-related quality of life (EQ-5D) were registered preoperatively, at 3 months, and 1 year postoperatively. Patient satisfaction was surveyed at the 1-year follow-up by 2 questions related to hip function and willingness to undergo the same surgery. Results: With a response rate of 85%, all outcomes improved in the 4 groups but there were neither statistical nor clinical differences between types of rTHA at 1-year follow-up. NRS pain during mobilization improved overall by 2.7 (95% confidence interval 2.3–3.1) until 1-year follow-up, both being statistically significant and clinically relevant. The improvements were mainly seen at the 3-month follow-up, with minor progress observed at 1 year. About 80% reported improved hip function and willingness to undergo the surgery again at the 1-year follow-up. Conclusion: Significant improvements in NRS pain and PROMS were found in all groups after rTHA, with no group differences at 1 year. This is relevant preoperative information for both clinicians and patients eligible for rTHA.

Published
2023
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12. Baseline radiomics features and MYC rearrangement status predict progression in aggressive B-cell lymphoma

Author

Eertink, Jakoba J., Zwezerijnen, Gerben J. C., Wiegers, Sanne E., Pieplenbosch, Simone, Chamuleau, Martine E. D., Lugtenburg, Pieternella J., de Jong, Daphne, Ylstra, Bauke, Mendeville, Matias, Dührsen, Ulrich, Hanoun, Christine, Hüttmann, Andreas, Richter, Julia, Klapper, Wolfram, Jauw, Yvonne W. S., Hoekstra, Otto S., de Vet, Henrica C. W., Boellaard, Ronald, and Zijlstra, Josée M.

Published
2023
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13. Convolutional neural networks for automatic image quality control and EARL compliance of PET images

Author

Elisabeth Pfaehler, Daniela Euba, Andreas Rinscheid, Otto S. Hoekstra, Josee Zijlstra, Joyce van Sluis, Adrienne H. Brouwers, Constantin Lapa, and Ronald Boellaard

Subjects
PET, Image quality, Convolutional neural network, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Background Machine learning studies require a large number of images often obtained on different PET scanners. When merging these images, the use of harmonized images following EARL-standards is essential. However, when including retrospective images, EARL accreditation might not have been in place. The aim of this study was to develop a convolutional neural network (CNN) that can identify retrospectively if an image is EARL compliant and if it is meeting older or newer EARL-standards. Materials and methods 96 PET images acquired on three PET/CT systems were included in the study. All images were reconstructed with the locally clinically preferred, EARL1, and EARL2 compliant reconstruction protocols. After image pre-processing, one CNN was trained to separate clinical and EARL compliant reconstructions. A second CNN was optimized to identify EARL1 and EARL2 compliant images. The accuracy of both CNNs was assessed using fivefold cross-validation. The CNNs were validated on 24 images acquired on a PET scanner not included in the training data. To assess the impact of image noise on the CNN decision, the 24 images were reconstructed with different scan durations. Results In the cross-validation, the first CNN classified all images correctly. When identifying EARL1 and EARL2 compliant images, the second CNN identified 100% EARL1 compliant and 85% EARL2 compliant images correctly. The accuracy in the independent dataset was comparable to the cross-validation accuracy. The scan duration had almost no impact on the results. Conclusion The two CNNs trained in this study can be used to retrospectively include images in a multi-center setting by, e.g., adding additional smoothing. This method is especially important for machine learning studies where the harmonization of images from different PET systems is essential.

Published
2022
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16. Dual time point imaging in locally advanced head and neck cancer to assess residual nodal disease after chemoradiotherapy

Author

Frederik Soffers, Nils Helsen, Tim Van den Wyngaert, Laurens Carp, Otto S. Hoekstra, Laurence Goethals, Michel Martens, Kristof Deben, Karoline Spaepen, Remco De Bree, Frank De Geeter, G. J. C. Zwezerijnen, Carl Van Laer, Alex Maes, Olivier Lenssen, Sigrid Stroobants, and the ECLYPS Investigators

Subjects
FDG-PET/CT, Locally advanced squamous cell head and neck cancer, LAHNSCC, Chemoradiotherapy, HPV, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Background FDG-PET/CT has a high negative predictive value to detect residual nodal disease in patients with locally advanced squamous cell head and neck cancer after completing concurrent chemoradiotherapy (CCRT). However, the positive predictive value remains suboptimal due to inflammation after radiotherapy, generating unnecessary further investigations and possibly even surgery. We report the results of a preplanned secondary end point of the ECLYPS study regarding the potential advantages of dual time point FDG-PET/CT imaging (DTPI) in this setting. Standardized dedicated head and neck FDG-PET/CT images were obtained 12 weeks after CCRT at 60 and 120 min after tracer administration. We performed a semiquantitative assessment of lymph nodes, and the retention index (RI) was explored to optimize diagnostic performance. The reference standard was histology, negative FDG-PET/CT at 1 year, or > 2 years of clinical follow-up. The time-dependent area under the receiver operator characteristics (AUROC) curves was calculated. Results In total, 102 subjects were eligible for analysis. SUV values increased in malignant nodes (median SUV1 = 2.6 vs. SUV2 = 2.7; P = 0.04) but not in benign nodes (median SUV1 = 1.8 vs. SUV2 = 1.7; P = 0.28). In benign nodes, RI was negative although highly variable (median RI = − 2.6; IQR 21.2), while in malignant nodes RI was positive (median RI = 12.3; IQR 37.2) and significantly higher (P = 0.018) compared to benign nodes. A combined threshold (SUV1 ≥ 2.2 + RI ≥ 3%) significantly reduced the amount of false-positive cases by 53% (P = 0.02) resulting in an increased specificity (90.8% vs. 80.5%) and PPV (52.9% vs. 37.0%), while sensitivity (60.0% vs. 66.7%) and NPV remained comparably high (92.9% vs. 93.3%). However, AUROC, as overall measure of benefit in diagnostic accuracy, did not significantly improve (P = 0.62). In HPV-related disease (n = 32), there was no significant difference between SUV1, SUV2, and RI in malignant and benign nodes, yet this subgroup was small. Conclusions DTPI did not improve the overall diagnostic accuracy of FDG-PET/CT to detect residual disease 12 weeks after chemoradiation. Due to differences in tracer kinetics between malignant and benign nodes, DTPI improved the specificity, but at the expense of a loss in sensitivity, albeit minimal. Since false negatives at the 12 weeks PET/CT are mainly due to minimal residual disease, DTPI is not able to significantly improve sensitivity, but repeat scanning at a later time (e.g. after 12 months) could possibly solve this problem. Further study is required in HPV-associated disease.

Published
2022
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20. The tourniquet's effects on skeletal muscle during total knee arthroplasty.

Author

Johnsen, Magnus, Mousavizadeh, Rouhollah, Scott, Alex, Havik, Steinar, Husby, Vigdis S., Winther, Siri B., Husby, Otto S., and Lian, Øystein

Abstract

This study investigates the impact of perioperative tourniquet on skeletal muscle cells during total knee arthroplasty (TKA) and its effects on the gene expression of apoptotic, inflammatory, and angiogenic pathways. The randomized controlled trial included 44 patients undergoing TKA. The patients were randomized to undergo surgery with (n = 23) or without (n = 21) tourniquet. The tourniquet was inflated before skin incision and deflated before wound closure in the tourniquet group. Biopsies from the lateral vastus muscle were obtained from both groups before wound closure and 8 weeks after surgery. The messenger ribonucleic acid (mRNA) expression and protein levels of angiopoietin‐like 4 (ANGPTL4), Hypoxia‐inducible Factor 1α, and Vascular Endothelial Growth Factor Alpha (VEGF‐A) in the biopsies were examined by reverse transcription‐quantitative polymerase chain reaction and tissue microarray, respectively. Differences in mean values (ΔCt for mRNA expression and staining positivity for protein expression) were compared with t‐tests. The apoptotic marker BID and the angiogenic marker VEGF‐A were significantly lower in the tourniquet group compared to the control group (p = 0.03, p = 0.047). However, there was a significant upregulation of VEGF‐A 8 weeks after surgery in the tourniquet group compared to perioperative biopsies (p = 0.002), indicating persistent changes. A significant upregulation in protein expression of the angiogenic marker ANGPTL4 was found perioperatively in the tourniquet group (p = 0.02). Our results demonstrate that the angiogenic gene expression is significantly altered by the tourniquet, the effects of which might contribute to postoperative interstitial edema, increased pain, and decreased muscle strength. These effects could lead to delayed rehabilitation and ultimately reduced patient satisfaction after TKA. [ABSTRACT FROM AUTHOR]

Published
2024
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21. The indication for aseptic revision TKA does not influence 1-year outcomes: an analysis of 178 full TKA revisions from a prospective institutional registry

Author

Siri B Winther, Gøril Lund Snorroeggen, Jomar Klaksvik, Olav A Foss, Tarjei Egeberg, Tina Strømdal Wik, and Otto S Husby

Subjects
Arthroplasty, Knee, Orthopedic surgery, RD701-811
Abstract

Background and purpose: Outcomes following revision total knee arthroplasty (TKA) may depend on the indication for revision surgery. We compared pain, patient-reported outcome measures (PROMs), and patient satisfaction among different indications for an aseptic TKA revision. Patients and methods: This was a retrospective study of prospective data from an institutional registry of 178 primary TKAs revised between 2012 and 2020. Patients were grouped by the main reason for their revision: loosening, malposition, instability, or stiffness. Pain during mobilization and at rest (NRS 0–10), physical function (KOOS-PS and KSS), and quality of life (EQ-5D) were surveyed preoperatively and at 2 months and 1 year postoperatively. Patient satisfaction was evaluated through questions related to knee function and their willingness to undergo the same surgery again at 1-year follow-up. Results: Pain and PROMs improved in all groups and did not differ statistically significantly between the 4 groups at 1-year follow-up, but equivalence for pain was not confirmed between groups. Overall, pain during mobilization improved by 2.4 (95% CI 1.9–3.0) at 1-year follow-up, which was both clinically and statistically significant. Improvements were seen within 2 months of surgery, with no further improvements seen 1 year postoperatively. Approximately 2/3 of patients reported that their knee function had improved and would undergo the same surgery again, at 1-year follow-up. Conclusion: Statistically significant and clinically relevant improvements in pain and PROMs were seen in all 4 revision groups 1 year after revision TKA. These results may assist clinicians and patients during preoperative counselling.

Published
2022
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23. Textural Feature Based Segmentation: A Repeatable and Accurate Segmentation Approach for Tumors in PET Images

Author

Pfaehler, Elisabeth, Mesotten, Liesbet, Kramer, Gem, Thomeer, Michiel, Vanhove, Karolien, de Jong, Johan, Adriaensens, Peter, Hoekstra, Otto S., Boellaard, Ronald, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Papież, Bartłomiej W., editor, Namburete, Ana I. L., editor, Yaqub, Mohammad, editor, and Noble, J. Alison, editor

Published
2020
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24. Potential and pitfalls of 89Zr-immuno-PET to assess target status: 89Zr-trastuzumab as an example

Author

Marc C. Huisman, C. Willemien Menke-van der Houven van Oordt, Josée M. Zijlstra, Otto S. Hoekstra, Ronald Boellaard, Guus A. M. S. van Dongen, Dhaval K. Shah, and Yvonne W. S. Jauw

Subjects
89Zr-immuno-PET, Modelling, Molecular imaging, Monoclonal antibody, Target expression, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Background 89Zirconium-immuno-positron emission tomography (89Zr-immuno-PET) is used for assessment of target status to guide antibody-based therapy. We aim to determine the relation between antibody tumor uptake and target concentration to improve future study design and interpretation. Methods The relation between tumor uptake and target concentration was predicted by mathematical modeling of 89Zr-labeled antibody disposition in the tumor. Literature values for trastuzumab kinetics were used to provide an example. Results 89Zr-trastuzumab uptake initially increases with increasing target concentration, until it levels off to a constant value. This is determined by the total administered mass dose of trastuzumab. For a commonly used imaging dose of 50 mg 89Zr-trastuzumab, uptake can discriminate between immunohistochemistry score (IHC) 0 versus 1–2–3. Conclusion The example for 89Zr-trastuzumab illustrates the potential to assess target expression. The pitfall of false-positive findings depends on the cut-off to define clinical target positivity (i.e., IHC 3) and the administered mass dose.

Published
2021
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27. Repeatability of two semi-automatic artificial intelligence approaches for tumor segmentation in PET

Author

Elisabeth Pfaehler, Liesbet Mesotten, Gem Kramer, Michiel Thomeer, Karolien Vanhove, Johan de Jong, Peter Adriaensens, Otto S. Hoekstra, and Ronald Boellaard

Subjects
Repeatability, Textural segmentation, Convolutional neural network, Tumor segmentation PET, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Background Positron emission tomography (PET) is routinely used for cancer staging and treatment follow-up. Metabolic active tumor volume (MATV) as well as total MATV (TMATV—including primary tumor, lymph nodes and metastasis) and/or total lesion glycolysis derived from PET images have been identified as prognostic factor or for the evaluation of treatment efficacy in cancer patients. To this end, a segmentation approach with high precision and repeatability is important. However, the implementation of a repeatable and accurate segmentation algorithm remains an ongoing challenge. Methods In this study, we compare two semi-automatic artificial intelligence (AI)-based segmentation methods with conventional semi-automatic segmentation approaches in terms of repeatability. One segmentation approach is based on a textural feature (TF) segmentation approach designed for accurate and repeatable segmentation of primary tumors and metastasis. Moreover, a convolutional neural network (CNN) is trained. The algorithms are trained, validated and tested using a lung cancer PET dataset. The segmentation accuracy of both segmentation approaches is compared using the Jaccard coefficient (JC). Additionally, the approaches are externally tested on a fully independent test–retest dataset. The repeatability of the methods is compared with those of two majority vote (MV2, MV3) approaches, 41%SUVMAX, and a SUV > 4 segmentation (SUV4). Repeatability is assessed with test–retest coefficients (TRT%) and intraclass correlation coefficient (ICC). An ICC > 0.9 was regarded as representing excellent repeatability. Results The accuracy of the segmentations with the reference segmentation was good (JC median TF: 0.7, CNN: 0.73). Both segmentation approaches outperformed most other conventional segmentation methods in terms of test–retest coefficient (TRT% mean: TF: 13.0%, CNN: 13.9%, MV2: 14.1%, MV3: 28.1%, 41%SUVMAX: 28.1%, SUV4: 18.1%) and ICC (TF: 0.98, MV2: 0.97, CNN: 0.99, MV3: 0.73, SUV4: 0.81, and 41%SUVMAX: 0.68). Conclusion The semi-automatic AI-based segmentation approaches used in this study provided better repeatability than conventional segmentation approaches. Moreover, both algorithms lead to accurate segmentations for both primary tumors as well as metastasis and are therefore good candidates for PET tumor segmentation.

Published
2021
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30. Response of the meso- and macro-zooplankton community to long-term environmental changes in the southern North Sea.

Author

Marques, R, Otto, S A, Di Pane, J, Boersma, M, Meunier, C L, Wiltshire, K H, Möllmann, C, and Renz, J

Subjects
*HYDROZOA, *UNIVARIATE analysis, *MULTIVARIATE analysis, *CLIMATE change, *ECOLOGICAL regime shifts, *COMMUNITY change, *EUTROPHICATION
Abstract

The North Sea (NS) is changing rapidly. Temporal variations in fishing intensity and eutrophic conditions, along with the ongoing impact of climate change, act in synergy resulting in modifications in marine communities. Although zooplankton has been extensively investigated, studies often ignore the large-sized meso- and macro-zooplankton (>500 µm), including holoplankton and meroplankton taxa. Here, we examined changes in abundances and community structure of these organisms between 1975 and 2018, using univariate and multivariate analysis, at different taxonomic levels. Abrupt changes in the abundances of (sub)communities occurred during different time periods and resulted in a significant restructuration of the entire community in 2006. These changes were consistent with the regime shifts reported in the NS and were a consequence of the environmental pressures on the whole community or on specific subcommunities. In the long term, the community shifted from higher abundances of hydrozoans and holoplankton taxa to an increasing abundance of decapods. Furthermore, we reveal the environmental variables that most explain the variability in the community dynamics, highlighting the importance of temperature and top-down processes. Our study underlines the relevance of investigations at different taxonomic levels, which elucidates how distinct responses to environmental changes ultimately shape the entire community structure. [ABSTRACT FROM AUTHOR]

Published
2024
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31. Molecular detection of blaTEM gene for encoding extended spectrum beta-lactamase (ESBL) on Escherichia coli isolated from deer feces in Indonesia.

Author

Riwu, Katty H. P., Effendi, Mustofa H., Rantam, Fedik A., Khairullah, Aswin R., Kurniawan, Shendy C., Kurniawan, Ahmad, Moses, Ikechukwu B., Hasib, Abdullah, Widodo, Agus, Yanestria, Sheila M., Silaen, Otto S. M., and Shehzad, Amir

Subjects
ESCHERICHIA coli, DEER, FECES, DRUG resistance in bacteria, GENES, WORLD health
Abstract

Antibiotic resistance is a serious global health threat and broad-spectrum beta-lactamase-producing Enterobactericeae (ESBL) are major contributors. This research focuses on the presence of Escherichia coli as a producer of ESBL in the fresh feces of deer. This study aimed to gain deeper insight into ESBL sourced from deer. 129 fresh stool samples were collected. A total of 89 samples came from the East Java region and 40 samples came from the East Nusa Tenggara region. Identification was carried out which was then followed by PCR. We found 9 positive samples of ESBL-producing E. coli containing the blaTEM gene as the ESBL encoding gene. 33 samples (25.28%) were positive for E. coli. 8 isolates (24.24%) were multidrug-resistant, East Java (6 isolates) and East Nusa Tenggara (2 isolates). All isolates of multidrug-resistant E. coli 7 isolates were ESBL positive (87.5%) and contained the blaTEM gene. The presence of MDR and ESBL-producing E. coli isolates have been confirmed in deer. Deer should be considered as a source of MDR and ESBL transmission for public health. [ABSTRACT FROM AUTHOR]

Published
2024

33. Patient-reported outcome after primary and aseptic revision hip arthroplasty: 1-year follow-up of 3,559 primary and 406 revision THAs in an institutional registry

Author

Tina S Wik, Jomar Klaksvik, Otto S Husby, Astrid Rasch, and Siri B Winther

Subjects
Arthroplasty, Fast track, Hip, patient reported outcome, Orthopedic surgery, RD701-811
Abstract

Background and purpose — Patient-reported outcomes (PROMs) after primary total hip arthroplasty (THA) and revision THA are important information in the preoperative shared decision-making process. We present 1-year results on pain, function, and quality of life following primary and revision THA. Patients and methods — From 2010 to 2018, 3,559 primary THA and 406 revision THAs were included in our institutional quality registry. PROMs were registered preoperatively, 3 months, and 1 year after surgery, numeric rating scale (0–10) for pain during mobilization and at rest, healthrelated quality of life (EQ-5D), and a hip-specific physical function score (HOOS-PS). 2 anchor questions were asked 1 year after surgery concerning joint function and willingness to go through surgery again. Results — There were statistically significant improvements in all PROMs at the 3-month follow-up in both groups. All PROMs improved more in the primary group relative to the revision group. 1 year after surgery, pain during mobilization was reduced with a mean change of 5.1 (SD 2.6) for primary THA and 2.9 (SD 3.0) for revision THA. 93% of primary THA patients reported both better function 1 year after surgery and that they would have gone through surgery again, compared with 78% and 79% in the revision THA group. Interpretation — Primary THA patients reported better function and more pain relief than the revision THA group 1 year after surgery. Pain during mobilization shows the most marked improvement in both groups, which is important preoperative information for patients.

Published
2022
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36. The Physics of the B Factories

Author

Bevan, A. J., Golob, B., Mannel, Th., Prell, S., Yabsley, B. D., Abe, K., Aihara, H., Anulli, F., Arnaud, N., Aushev, T., Beneke, M., Beringer, J., Bianchi, F., Bigi, I. I., Bona, M., Brambilla, N., rodzicka, J. B, Chang, P., Charles, M. J., Cheng, C. H., Cheng, H. -Y., Chistov, R., Colangelo, P., Coleman, J. P., Drutskoy, A., Druzhinin, V. P., Eidelman, S., Eigen, G., Eisner, A. M., Faccini, R., Flood, K. T ., Gambino, P., Gaz, A., Gradl, W., Hayashii, H., Higuchi, T., Hulsbergen, W. D., Hurth, T., Iijima, T., Itoh, R., Jackson, P. D., Kass, R., Kolomensky, Yu. G., Kou, E., Križan, P., Kronfeld, A., Kumano, S., Kwon, Y. J., Latham, T. E., Leith, D. W. G. S., Lüth, V., Martinez-Vidal, F., Meadows, B. T., Mussa, R., Nakao, M., Nishida, S., Ocariz, J., Olsen, S. L., Pakhlov, P., Pakhlova, G., Palano, A., Pich, A., Playfer, S., Poluektov, A., Porter, F. C., Robertson, S. H., Roney, J. M., Roodman, A., Sakai, Y., Schwanda, C., Schwartz, A. J., Seidl, R., Sekula, S. J., Steinhauser, M., Sumisawa, K., Swanson, E. S., Tackmann, F., Trabelsi, K., Uehara, S., Uno, S., van der Water, R., Vasseur, G., Verkerke, W., Waldi, R., Wang, M. Z., Wilson, F. F., Zupan, J., Zupanc, A., Adachi, I., Albert, J., Banerjee, Sw., Bellis, M., Ben-Haim, E., Biassoni, P., Cahn, R. N., Cartaro, C., Chauveau, J., Chen, C., Chiang, C. C., Cowan, R., Dalseno, J., Davier, M., Davies, C., Dingfelder, J. C., nard, B. Eche, Epifanov, D., Fulsom, B. G., Gabareen, A. M., Gary, J. W., Godang, R., Graham, M. T., Hafner, A., Hamilton, B., Hartmann, T., Hayasaka, K., Hearty, C., Iwasaki, Y., Khodjamirian, A., Kusaka, A., Kuzmin, A., Lafferty, G. D., Lazzaro, A., Li, J., Lindemann, D., Long, O., Lusiani, A., Marchiori, G., Martinelli, M., Miyabayashi, K., Mizuk, R., Mohanty, G. B., Muller, D. R., Nakazawa, H., Ongmongkolkul, P., Pacetti, S., Palombo, F., Pedlar, T. K., Piilonen, L. E., Pilloni, A., Poireau, V., Prothmann, K., Pulliam, T., Rama, M., Ratcliff, B. N., Roudeau, P., Schrenk, S., Schroeder, T., Schubert, K. R., Shen, C. P., Shwartz, B., Soffer, A., Solodov, E. P., Somov, A., Starič, M., Stracka, S., Telnov, A. V., Todyshev, K. Yu., Tsuboyama, T., Uglov, T., Vinokurova, A., Walsh, J. J., Watanabe, Y., Won, E., Wormser, G., Wright, D. H., Ye, S., Zhang, C. C., Abachi, S., Abashian, A., Abe, N., Abe, R., Abe, T., Abrams, G. S., Adam, I., Adamczyk, K., Adametz, A., Adye, T., Agarwal, A., Ahmed, H., Ahmed, M., Ahmed, S., Ahn, B. S., Ahn, H. S., Aitchison, I. J. R., Akai, K., Akar, S., Akatsu, M., Akemoto, M., Akhmetshin, R., Akre, R., Alam, M. S., Albert, J. N., Aleksan, R., Alexander, J. P., Alimonti, G., Allen, M. T., Allison, J., Allmendinger, T., Alsmiller, J. R. G., Altenburg, D., Alwyn, K. E., An, Q., Anderson, J., Andreassen, R., Andreotti, D., Andreotti, M., Andress, J. C., Angelini, C., Anipko, D., Anjomshoaa, A., Anthony, P. L., Antillon, E. A., Antonioli, E., Aoki, K., Arguin, J. F., Arinstein, K., Arisaka, K., Asai, K., Asai, M., Asano, Y., Asgeirsson, D. J., Asner, D. M., Aso, T., Aspinwall, M. L., Aston, D., Atmacan, H., Aubert, B., Aulchenko, V., Ayad, R., Azemoon, T., Aziz, T., Azzolini, V., Azzopardi, D. E., Baak, M. A., Back, J. J., Bagnasco, S., Bahinipati, S., Bailey, D. S., Bailey, S., Bailly, P., van Bakel, N., Bakich, A. M., Bala, A., Balagura, V., Baldini-Ferroli, R., Ban, Y., Banas, E., Band, H. R., Banerjee, S., Baracchini, E., Barate, R., Barberio, E., Barbero, M., Bard, D. J., Barillari, T., Barlow, N. R., Barlow, R. J., Barrett, M., Bartel, W., Bartelt, J., Bartoldus, R., Batignani, G., Battaglia, M., Bauer, J. M., Bay, A., Beaulieu, M., Bechtle, P., Beck, T. W., Becker, J., Becla, J., Bedny, I., Behari, S., Behera, P. K., Behn, E., Behr, L., Beigbeder, C., Beiline, D., Bell, R., Bellini, F., Bellodi, G., Belous, K., Benayoun, M., Benelli, G., Benitez, J. F., Benkebil, M., Berger, N., Bernabeu, J., Bernard, D., Bernet, R., Bernlochner, F. U., Berryhill, J. W., Bertsche, K., Besson, P., Best, D. S., Bettarini, S., Bettoni, D., Bhardwaj, V., Bhimji, W., Bhuyan, B., Biagini, M. E., Biasini, M., van Bibber, K., Biesiada, J., Bingham, I., Bionta, R. M., Bischofberger, M., Bitenc, U., Bizjak, I., Blanc, F., Blaylock, G., Blinov, V. E., Bloom, E., Bloom, P. C., Blount, N. L., Blouw, J., Bly, M., Blyth, S., Boeheim, C. T., Bomben, M., Bondar, A., Bondioli, M., Bonneaud, G. R., Bonvicini, G., Booke, M., Booth, J., Borean, C., Borgland, A. W., Borsato, E., Bosi, F., Bosisio, L., Botov, A. A., Bougher, J., Bouldin, K., Bourgeois, P., Boutigny, D., Bowerman, D. A., Boyarski, A. M., Boyce, R. F., Boyd, J. T., Bozek, A., Bozzi, C., Bračko, M., Brandenburg, G., Brandt, T., Brau, B., Brau, J., Breon, A. B., Breton, D., Brew, C., Briand, H., Bright-Thomas, P. G., Brigljević, V., Britton, D. I., Brochard, F., Broomer, B., Brose, J., Browder, T. E., Brown, C. L., Brown, C. M., Brown, D. N., Browne, M., Bruinsma, M., Brunet, S., Bucci, F., Buchanan, C., Buchmueller, O. L., Bünger, C., Bugg, W., Bukin, A. D., Bula, R., Bulten, H., Burchat, P. R., Burgess, W., Burke, J. P., Button-Shafer, J., Buzykaev, A. R., Buzzo, A., Cai, Y., Calabrese, R., Calcaterra, A., Calderini, G., Camanzi, B., Campagna, E., Campagnari, C., Capra, R., Carassiti, V., Carpinelli, M., Carroll, M., Casarosa, G., Casey, B. C. K., Cason, N. M., Castelli, G., Cavallo, N., Cavoto, G., Cecchi, A., Cenci, R., Cerizza, G., Cervelli, A., Ceseracciu, A., Chai, X., Chaisanguanthum, K. S., Chang, M. C., Chang, Y. H., Chang, Y. W., Chao, D. S., Chao, M., Chao, Y., Charles, E., Chavez, C. A., Cheaib, R., Chekelian, V., Chen, A., Chen, E., Chen, G. P., Chen, H. F., Chen, J. -H., Chen, J. C., Chen, K. F., Chen, P., Chen, S., Chen, W. T., Chen, X., Chen, X. R., Chen, Y. Q., Cheng, B., Cheon, B. G., Chevalier, N., Chia, Y. M., Chidzik, S., Chilikin, K., Chistiakova, M. V., Cizeron, R., Cho, I. S., Cho, K., Chobanova, V., Choi, H. H. F., Choi, K. S., Choi, S. K., Choi, Y., Choi, Y. K., Christ, S., Chu, P. H., Chun, S., Chuvikov, A., Cibinetto, G., Cinabro, D., Clark, A. R., Clark, P. J., Clarke, C. K., Claus, R., Claxton, B., Clifton, Z. C., Cochran, J., Cohen-Tanugi, J., Cohn, H., Colberg, T., Cole, S., Colecchia, F., Condurache, C., Contri, R., Convert, P., Convery, M. R., Cooke, P., Copty, N., Cormack, C. M., Corso, F. Dal, Corwin, L. A., Cossutti, F., Cote, D., Ramusino, A. Cotta, Cottingham, W. N., Couderc, F., Coupal, D. P., Covarelli, R., Cowan, G., Craddock, W. W., Crane, G., Crawley, H. B., Cremaldi, L., Crescente, A., Cristinziani, M., Crnkovic, J., Crosetti, G., Cuhadar-Donszelmann, T., Cunha, A., Curry, S., D'Orazio, A., Dû, S., Dahlinger, G., Dahmes, B., Dallapiccola, C., Danielson, N., Danilov, M., Das, A., Dash, M., Dasu, S., Datta, M., Daudo, F., Dauncey, P. D., David, P., Davis, C. L., Day, C. T., De Mori, F., De Domenico, G., De Groot, N., De la Vaissière, C., de la Vaissière, Ch., de Lesquen, A., De Nardo, G., de Sangro, R., De Silva, A., DeBarger, S., Decker, F. J., Sanchez, P. del Amo, Del Buono, L., Del Gamba, V., del Re, D., Della Ricca, G., Denig, A. G., Derkach, D., Derrington, I. M., DeStaebler, H., Destree, J., Devmal, S., Dey, B., Di Girolamo, B., Di Marco, E., Dickopp, M., Dima, M. O., Dittrich, S., Dittongo, S., Dixon, P., Dneprovsky, L., Dohou, F., Doi, Y., Doležal, Z., Doll, D. A., Donald, M., Dong, L., Dong, L. Y., Dorfan, J., Dorigo, A., Dorsten, M. P., Dowd, R., Dowdell, J., Drásal, Z., Dragic, J., Drummond, B. W., Dubitzky, R. S., Dubois-Felsmann, G. P., Dubrovin, M. S., Duh, Y. C., Duh, Y. T., Dujmic, D., Dungel, W., Dunwoodie, W., Dutta, D., Dvoretskii, A., Dyce, N., Ebert, M., Eckhart, E. A., Ecklund, S., Eckmann, R., Eckstein, P., Edgar, C. L., Edwards, A. J., Egede, U., Eichenbaum, A. M., Elmer, P., Emery, S., Enari, Y., Enomoto, R., Erdos, E., Erickson, R., Ernst, J. A., Erwin, R. J., Escalier, M., Eschenburg, V., Eschrich, I., Esen, S., Esteve, L., Evangelisti, F., Everton, C. W., Eyges, V., Fabby, C., Fabozzi, F., Fahey, S., Falbo, M., Fan, S., Fang, F., Fanin, C., Farbin, A., Farhat, H., Fast, J. E., Feindt, M., Fella, A., Feltresi, E., Ferber, T., Fernholz, R. E., Ferrag, S., Ferrarotto, F., Ferroni, F., Field, R. C., Filippi, A., Finocchiaro, G., Fioravanti, E., da Costa, J. Firmino, Fischer, P. -A., Fisher, A., Fisher, P. H., Flacco, C. J., Flack, R. L., Flaecher, H. U., Flanagan, J., Flanigan, J. M., Ford, K. E., Ford, W. T., Forster, I. J., Forti, A. C., Forti, F., Fortin, D., Foster, B., Foulkes, S. D., Fouque, G., Fox, J., Franchini, P., Sevilla, M. Franco, Franek, B., Frank, E. D., Fransham, K. B., Fratina, S., Fratini, K., Frey, A., Frey, R., Friedl, M., Fritsch, M., Fry, J. R., Fujii, H., Fujikawa, M., Fujita, Y., Fujiyama, Y., Fukunaga, C., Fukushima, M., Fullwood, J., Funahashi, Y., Funakoshi, Y., Furano, F., Furman, M., Furukawa, K., Futterschneider, H., Gabathuler, E., Gabriel, T. A., Gabyshev, N., Gaede, F., Gagliardi, N., Gaidot, A., Gaillard, J. -M., Gaillard, J. R., Galagedera, S., Galeazzi, F., Gallo, F., Gamba, D., Gamet, R., Gan, K. K., Gandini, P., Ganguly, S., Ganzhur, S. F., Gao, Y. Y., Gaponenko, I., Garmash, A., Tico, J. Garra, Garzia, I., Gaspero, M., Gastaldi, F., Gatto, C., Gaur, V., Geddes, N. I., Geld, T. L., Genat, J. -F., George, K. A., George, M., George, S., Georgette, Z., Gershon, T. J., Gill, M. S., Gillard, R., Gilman, J. D., Giordano, F., Giorgi, M. A., Giraud, P. -F., Gladney, L., Glanzman, T., Glattauer, R., Go, A., Goetzen, K., Goh, Y. M., Gokhroo, G., Goldenzweig, P., Golubev, V. B., Gopal, G. P., Gordon, A., Gorišek, A., Goriletsky, V. I., Gorodeisky, R., Gosset, L., Gotow, K., Gowdy, S. J., Graffin, P., Grancagnolo, S., Grauges, E., Graziani, G., Green, M. G., Greene, M. G., Grenier, G. J., Grenier, P., Griessinger, K., Grillo, A. A., Grinyov, B. V., Gritsan, A. V., Grosdidier, G., Perdekamp, M. Grosse, Grosso, P., Grothe, M., Groysman, Y., Grünberg, O., Guido, E., Guler, H., Gunawardane, N. J. W., Guo, Q. H., Guo, R. S., Guo, Z. J., Guttman, N., Ha, H., Ha, H. C., Haas, T., Haba, J., Hachtel, J., Hadavand, H. K., Hadig, T., Hagner, C., Haire, M., Haitani, F., Haji, T., Haller, G., Halyo, V., Hamano, K., Hamasaki, H., de Monchenault, G. Hamel, Hamilton, J., Hamilton, R., Hamon, O., Han, B. Y., Han, Y. L., Hanada, H., Hanagaki, K., Handa, F., Hanson, J. E., Hanushevsky, A., Hara, K., Hara, T., Harada, Y., Harrison, P. F., Harrison, T. J., Harrop, B., Hart, A. J., Hart, P. A., Hartfiel, B. L., Harton, J. L., Haruyama, T., Hasan, A., Hasegawa, Y., Hast, C., Hastings, N. C., Hasuko, K., Hauke, A., Hawkes, C. M., Hayashi, K., Hazumi, M., Hee, C., Heenan, E. M., Heffernan, D., Held, T., Henderson, R., Henderson, S. W., Hertzbach, S. S., Hervé, S., Heß, M., Heusch, C. A., Hicheur, A., Higashi, Y., Higasino, Y., Higuchi, I., Hikita, S., Hill, E. J., Himel, T., Hinz, L., Hirai, T., Hirano, H., Hirschauer, J. F., Hitlin, D. G., Hitomi, N., Hodgkinson, M. C., Höcker, A., Hoi, C. T., Hojo, T., Hokuue, T., Hollar, J. J., Hong, T. M., Honscheid, K., Hooberman, B., Hopkins, D. A., Horii, Y., Hoshi, Y., Hoshina, K., Hou, S., Hou, W. S., Hryn'ova, T., Hsiung, Y. B., Hsu, C. L., Hsu, S. C., Hu, H., Hu, T., Huang, H. C., Huang, T. J., Huang, Y. C., Huard, Z., Huffer, M. E., Hufnagel, D., Hung, T., Hutchcroft, D. E., Hyun, H. J., Ichizawa, S., Igaki, T., Igarashi, A., Igarashi, S., Igarashi, Y., Igonkina, O., Ikado, K., Ikeda, H., Ikeda, K., Ilic, J., Inami, K., Innes, W. R., Inoue, Y., Ishikawa, A., Ishino, H., Itagaki, K., Itami, S., Itoh, K., Ivanchenko, V. N., Iverson, R., Iwabuchi, M., Iwai, G., Iwai, M., Iwaida, S., Iwamoto, M., Iwasaki, H., Iwasaki, M., Iwashita, T., Izen, J. M., Jackson, D. J., Jackson, F., Jackson, G., Jackson, P. S., Jacobsen, R. G., Jacoby, C., Jaegle, I., Jain, V., Jalocha, P., Jang, H. K., Jasper, H., Jawahery, A., Jayatilleke, S., Jen, C. M., Jensen, F., Jessop, C. P., Ji, X. B., John, M. J. J., Johnson, D. R., Johnson, J. R., Jolly, S., Jones, M., Joo, K. K., Joshi, N., Joshi, N. J., Judd, D., Julius, T., Kadel, R. W., Kadyk, J. A., Kagan, H., Kagan, R., Kah, D. H., Kaiser, S., Kaji, H., Kajiwara, S., Kakuno, H., Kameshima, T., Kaminski, J., Kamitani, T., Kaneko, J., Kang, J. H., Kang, J. S., Kani, T., Kapusta, P., Karbach, T. M., Karolak, M., Karyotakis, Y., Kasami, K., Katano, G., Kataoka, S. U., Katayama, N., Kato, E., Kato, Y., Kawai, H., Kawai, M., Kawamura, N., Kawasaki, T., Kay, J., Kay, M., Kelly, M. P., Kelsey, M. H., Kent, N., Kerth, L. T., Khan, A., Khan, H. R., Kharakh, D., Kibayashi, A., Kichimi, H., Kiesling, C., Kikuchi, M., Kikutani, E., Kim, B. H., Kim, C. H., Kim, D. W., Kim, H., Kim, H. J., Kim, H. O., Kim, H. W., Kim, J. B., Kim, J. H., Kim, K. T., Kim, M. J., Kim, P., Kim, S. K., Kim, S. M., Kim, T. H., Kim, Y. I., Kim, Y. J., King, G. J., Kinoshita, K., Kirk, A., Kirkby, D., Kitayama, I., Klemetti, M., Klose, V., Klucar, J., Knecht, N. S., Knoepfel, K. J., Knowles, D. J., Ko, B. R., Kobayashi, N., Kobayashi, S., Kobayashi, T., Kobel, M. J., Koblitz, S., Koch, H., Kocian, M. L., Kodyš, P., Koeneke, K., Kofler, R., Koike, S., Koishi, S., Koiso, H., Kolb, J. A., Kolya, S. D., Kondo, Y., Konishi, H., Koppenburg, P., Koptchev, V. B., Kordich, T. M. B., Korol, A. A., Korotushenko, K., Korpar, S., Kouzes, R. T., Kovalskyi, D., Kowalewski, R., Kozakai, Y., Kozanecki, W., Kral, J. F., Krasnykh, A., Krause, R., Kravchenko, E. A., Krebs, J., Kreisel, A., Kreps, M., Krishnamurthy, M., Kroeger, R., Kroeger, W., Krokovny, P., Kronenbitter, B., Kroseberg, J., Kubo, T., Kuhr, T., Kukartsev, G., Kulasiri, R., Kulikov, A., Kumar, R., Kumar, S., Kumita, T., Kuniya, T., Kunze, M., Kuo, C. C., Kuo, T. -L., Kurashiro, H., Kurihara, E., Kurita, N., Kuroki, Y., Kurup, A., Kutter, P. E., Kuznetsova, N., Kvasnička, P., Kyberd, P., Kyeong, S. H., Lacker, H. M., Lae, C. K., Lamanna, E., Lamsa, J., Lanceri, L., Landi, L., Lang, M. I., Lange, D. J., Lange, J. S., Langenegger, U., Langer, M., Lankford, A. J., Lanni, F., Laplace, S., Latour, E., Lau, Y. P., Lavin, D. R., Layter, J., Lebbolo, H., LeClerc, C., Leddig, T., Leder, G., Diberder, F. Le, Lee, C. L., Lee, J., Lee, J. S., Lee, M. C., Lee, M. H., Lee, M. J., Lee, S. -J., Lee, S. E., Lee, S. H., Lee, Y. J., Lees, J. P., Legendre, M., Leitgab, M., Leitner, R., Leonardi, E., Leonidopoulos, C., Lepeltier, V., Leruste, Ph., Lesiak, T., Levi, M. E., Levy, S. L., Lewandowski, B., Lewczuk, M. J., Lewis, P., Li, H., Li, H. B., Li, S., Li, X., Li, Y., Gioi, L. Li, Libby, J., Lidbury, J., Lillard, V., Lim, C. L., Limosani, A., Lin, C. S., Lin, J. Y., Lin, S. W., Lin, Y. S., Lindquist, B., Lindsay, C., Lista, L., Liu, C., Liu, F., Liu, H., Liu, H. M., Liu, J., Liu, R., Liu, T., Liu, Y., Liu, Z. Q., Liventsev, D., Vetere, M. Lo, Locke, C. B., Lockman, W. S., Di Lodovico, F., Lombardo, V., London, G. W., Pegna, D. Lopes, Lopez, L., Lopez-March, N., Lory, J., LoSecco, J. M., Lou, X. C., Louvot, R., Lu, A., Lu, C., Lu, M., Lu, R. S., Lueck, T., Luitz, S., Lukin, P., Lund, P., Luppi, E., Lutz, A. M., Lutz, O., Lynch, G., Lynch, H. L., Lyon, A. J., Lyubinsky, V. R., MacFarlane, D. B., Mackay, C., MacNaughton, J., Macri, M. M., Madani, S., Mader, W. F., Majewski, S. A., Majumder, G., Makida, Y., Malaescu, B., Malaguti, R., Malclès, J., Mallik, U., Maly, E., Mamada, H., Manabe, A., Mancinelli, G., Mandelkern, M., Mandl, F., Manfredi, P. F., Mangeol, D. J. J., Manoni, E., Mao, Z. P., Margoni, M., Marker, C. E., Markey, G., Marks, J., Marlow, D., Marques, V., Marsiske, H., Martellotti, S., Martin, E. C., Martin, J. P., Martin, L., Martinez, A. J., Marzolla, M., Mass, A., Masuzawa, M., Mathieu, A., Matricon, P., Matsubara, T., Matsuda, T., Matsumoto, H., Matsumoto, S., Matsumoto, T., Matsuo, H., Mattison, T. S., Matvienko, D., Matyja, A., Mayer, B., Mazur, M. A., Mazzoni, M. A., McCulloch, M., McDonald, J., McFall, J. D., McGrath, P., McKemey, A. K., McKenna, J. A., Mclachlin, S. E., McMahon, S., McMahon, T. R., McOnie, S., Medvedeva, T., Melen, R., Mellado, B., Menges, W., Menke, S., Merchant, A. M., Merkel, J., Messner, R., Metcalfe, S., Metzler, S., Meyer, N. T., Meyer, T. I., Meyer, W. T., Michael, A. K., Michelon, G., Michizono, S., Micout, P., Miftakov, V., Mihalyi, A., Mikami, Y., Milanes, D. A., Milek, M., Mimashi, T., Minamora, J. S., Mindas, C., Minutoli, S., Mir, L. M., Mishra, K., Mitaroff, W., Miyake, H., Miyashita, T. S., Miyata, H., Miyazaki, Y., Moffitt, L. C., Mohapatra, A., Mohapatra, A. K., Mohapatra, D., Moll, A., Moloney, G. R., Mols, J. P., Mommsen, R. K., Monge, M. R., Monorchio, D., Moore, T. B., Moorhead, G. F., de Freitas, P. Mora, Morandin, M., Morgan, N., Morgan, S. E., Morganti, M., Morganti, S., Mori, S., Mori, T., Morii, M., Morris, J. P., Morsani, F., Morton, G. W., Moss, L. J., Mouly, J. P., Mount, R., Mueller, J., Müller-Pfefferkorn, R., Mugge, M., Muheim, F., Muir, A., Mullin, E., Munerato, M., Murakami, A., Murakami, T., Muramatsu, N., Musico, P., Nagai, I., Nagamine, T., Nagasaka, Y., Nagashima, Y., Nagayama, S., Nagel, M., Naisbit, M. T., Nakadaira, T., Nakahama, Y., Nakajima, M., Nakajima, T., Nakamura, I., Nakamura, T., Nakamura, T. T., Nakano, E., Nakayama, H., Nam, J. W., Narita, S., Narsky, I., Nash, J . A., Natkaniec, Z., Nauenberg, U., Nayak, M., Neal, H., Nedelkovska, E., Negrini, M., Neichi, K., Nelson, D., Nelson, S., Neri, N., Nesom, G., Neubauer, S., Newman-Coburn, D., Ng, C., Nguyen, X., Nicholson, H., Niebuhr, C., Nief, J. Y., Niiyama, M., Nikolich, M. B., Nisar, N. K., Nishimura, K., Nishio, Y., Nitoh, O., Nogowski, R., Noguchi, S., Nomura, T., Nordby, M., Nosochkov, Y., Novokhatski, A., Nozaki, S., Nozaki, T., Nugent, I. M., O'Grady, C. P., O'Neale, S. W., O'Neill, F. G., Oberhof, B., Oddone, P. J., Ofte, I., Ogawa, A., Ogawa, K., Ogawa, S., Ogawa, Y., Ohkubo, R., Ohmi, K., Ohnishi, Y., Ohno, F., Ohshima, T., Ohshima, Y., Ohuchi, N., Oide, K., Oishi, N., Okabe, T., Okazaki, N., Okazaki, T., Okuno, S., Olaiya, E. O., Olivas, A., Olley, P., Olsen, J., Ono, S., Onorato, G., Onuchin, A. P., Onuki, Y., Ooba, T., Orimoto, T. J., Oshima, T., Osipenkov, I. L., Ostrowicz, W., Oswald, C., Otto, S., Oyang, J., Oyanguren, A., Ozaki, H., Ozcan, V. E., Paar, H. P., Padoan, C., Paick, K., Palka, H., Pan, B., Pan, Y., Vazquez, W. Panduro, Panetta, J., Panova, A. I., Panvini, R. S., Panzenböck, E., Paoloni, E., Paolucci, P., Pappagallo, M., Paramesvaran, S., Park, C. S., Park, C. W., Park, H., Park, H. K., Park, K. S., Park, W., Parry, R. J., Parslow, N., Passaggio, S., Pastore, F. C., Patel, P. M., Patrignani, C., Patteri, P., Pavel, T., Pavlovich, J., Payne, D. J., Peak, L. S., Peimer, D. R., Pelizaeus, M., Pellegrini, R., Pelliccioni, M., Peng, C. C., Peng, J. C., Peng, K. C., Peng, T., Penichot, Y., Pennazzi, S., Pennington, M. R., Penny, R. C., Penzkofer, A., Perazzo, A., Perez, A., Perl, M., Pernicka, M., Perroud, J. -P., Peruzzi, I. M., Pestotnik, R., Peters, K., Peters, M., Petersen, B. A., Petersen, T. C., Petigura, E., Petrak, S., Petrella, A., Petrič, M., Petzold, A., Pia, M. G., Piatenko, T., Piccolo, D., Piccolo, M., Piemontese, L., Piemontese, M., Pierini, M., Pierson, S., Pioppi, M., Piredda, G., Pivk, M., Plaszczynski, S., Polci, F., Pompili, A., Poropat, P., Posocco, M., Potter, C. T., Potter, R. J. L., Prasad, V., Prebys, E., Prencipe, E., Prendki, J., Prepost, R., Prest, M., Prim, M., Pripstein, M., Prudent, X., Pruvot, S., Puccio, E. M. T., Purohit, M. V., Qi, N. D., Quinn, H., Raaf, J., Rabberman, R., Raffaelli, F., Ragghianti, G., Rahatlou, S., Rahimi, A. M., Rahmat, R., Rakitin, A. Y., Randle-Conde, A., Rankin, P., Rashevskaya, I., Ratkovsky, S., Raven, G., Re, V., Reep, M., Regensburger, J. J., Reidy, J., Reif, R., Reisert, B., Renard, C., Renga, F., Ricciardi, S., Richman, J. D., Ritchie, J. L., Ritter, M., Rivetta, C., Rizzo, G., Roat, C., Robbe, P., Roberts, D. A., Robertson, A. I., Robutti, E., Rodier, S., Rodriguez, D. M., Rodriguez, J. L., Rodriguez, R., Roe, N. A., Röhrken, M., Roethel, W., Rolquin, J., Romanov, L., Romosan, A., Ronan, M. T., Rong, G., Ronga, F. J., Roos, L., Root, N., Rosen, M., Rosenberg, E. I., Rossi, A., Rostomyan, A., Rotondo, M., Roussot, E., Roy, J., Rozanska, M., Rozen, Y., Rubin, A. E., Ruddick, W. O., Ruland, A. M., Rybicki, K., Ryd, A., Ryu, S., Ryuko, J., Sabik, S., Sacco, R., Saeed, M. A., Tehrani, F. Safai, Sagawa, H., Sahoo, H., Sahu, S., Saigo, M., Saito, T., Saitoh, S., Sakai, K., Sakamoto, H., Sakaue, H., Saleem, M., Salnikov, A. A., Salvati, E., Salvatore, F., Samuel, A., Sanders, D. A., Sanders, P., Sandilya, S., Sandrelli, F., Sands, W., Sands, W. R., Sanpei, M., Santel, D., Santelj, L., Santoro, V., Santroni, A., Sanuki, T., Sarangi, T. R., Saremi, S., Sarti, A., Sasaki, T., Sasao, N., Satapathy, M., Sato, Nobuhiko, Sato, Noriaki, Sato, Y., Satoyama, N., Satpathy, A., Savinov, V., Savvas, N., Saxton, O. H., Sayeed, K., Schaffner, S. F., Schalk, T., Schenk, S., Schieck, J. R., Schietinger, T., Schilling, C. J., Schindler, R. H., Schmid, S., Schmitz, R. E., Schmuecker, H., Schneider, O., Schnell, G., Schönmeier, P., Schofield, K. C., Schott, G., Schröder, H., Schram, M., Schubert, J., Schümann, J., Schultz, J., Schumm, B. A., Schune, M. H., Schwanke, U., Schwarz, H., Schwiening, J., Schwierz, R., Schwitters, R. F., Sciacca, C., Sciolla, G., Scott, I. J., Seeman, J., Seiden, A., Seitz, R., Seki, T., Sekiya, A. I., Semenov, S., Semmler, D., Sen, S., Senyo, K., Seon, O., Serbo, V. V., Serednyakov, S. I., Serfass, B., Serra, M., Serrano, J., Settai, Y., Seuster, R., Sevior, M. E., Shakhova, K. V., Shang, L., Shapkin, M., Sharma, V., Shebalin, V., Shelkov, V. G., Shen, B. C., Shen, D. Z., Shen, Y. T., Sherwood, D. J., Shibata, T., Shibata, T. A., Shibuya, H., Shidara, T., Shimada, K., Shimoyama, M., Shinomiya, S., Shiu, J. G., Shorthouse, H. W., Shpilinskaya, L. I., Sibidanov, A., Sicard, E., Sidorov, A., Sidorov, V., Siegle, V., Sigamani, M., Simani, M. C., Simard, M., Simi, G., Simon, F., Simonetto, F., Sinev, N. B., Singh, H., Singh, J. B., Sinha, R., Sitt, S., Skovpen, Yu. I., Sloane, R. J., Smerkol, P., Smith, A. J. S., Smith, D., Smith, D. S., Smith, J. G., Smol, A., Snoek, H. L., Snyder, A., So, R. Y., Sobie, R. J., Soderstrom, E., Soha, A., Sohn, Y. S., Sokoloff, M. D., Sokolov, A., Solagna, P., Solovieva, E., Soni, N., Sonnek, P., Sordini, V., Spaan, B., Spanier, S. M., Spencer, E., Speziali, V., Spitznagel, M., Spradlin, P., Staengle, H., Stamen, R., Stanek, M., Stanič, S., Stark, J., Steder, M., Steininger, H., Steinke, M., Stelzer, J., Stevanato, E., Stocchi, A., Stock, R., Stoeck, H., Stoker, D. P., Stroili, R., Strom, D., Strother, P., Strube, J., Stugu, B., Stypula, J., Su, D., Suda, R., Sugahara, R., Sugi, A., Sugimura, T., Sugiyama, A., Suitoh, S., Sullivan, M. K., Sumihama, M., Sumiyoshi, T., Summers, D. J., Sun, L., Sun, S., Sundermann, J. E., Sung, H. F., Susaki, Y., Sutcliffe, P., Suzuki, A., Suzuki, J., Suzuki, J. I., Suzuki, K., Suzuki, S., Suzuki, S. Y., Swain, J. E., Swain, S. K., T'Jampens, S., Tabata, M., Tackmann, K., Tajima, H., Tajima, O., Takahashi, K., Takahashi, S., Takahashi, T., Takasaki, F., Takayama, T., Takita, M., Tamai, K., Tamponi, U., Tamura, N., Tan, N., Tan, P., Tanabe, K., Tanabe, T., Tanaka, H. A., Tanaka, J., Tanaka, M., Tanaka, S., Tanaka, Y., Tanida, K., Taniguchi, N., Taras, P., Tasneem, N., Tatishvili, G., Tatomi, T., Tawada, M., Taylor, F., Taylor, G. N., Taylor, G. P., Telnov, V. I., Teodorescu, L., Ter-Antonyan, R., Teramoto, Y., Teytelman, D., Thérin, G., Thiebaux, Ch., Thiessen, D., Thomas, E. W., Thompson, J. M., Thorne, F., Tian, X. C., Tibbetts, M., Tikhomirov, I., Tinslay, J. S., Tiozzo, G., Tisserand, V., Tocut, V., Toki, W. H., Tomassini, E. W., Tomoto, M., Tomura, T., Torassa, E., Torrence, E., Tosi, S., Touramanis, C., Toussaint, J. C., Tovey, S. N., Trapani, P. P., Treadwell, E., Triggiani, G., Trincaz-Duvoid, S., Trischuk, W., Troost, D., Trunov, A., Tsai, K. L., Tsai, Y. T., Tsujita, Y., Tsukada, K., Tsukamoto, T., Tuggle, J. M., Tumanov, A., Tung, Y. W., Turnbull, L., Turner, J., Turri, M., Uchida, K., Uchida, M., Uchida, Y., Ueki, M., Ueno, K., Ujiie, N., Ulmer, K. A., Unno, Y., Urquijo, P., Ushiroda, Y., Usov, Y., Usseglio, M., Usuki, Y., Uwer, U., Va'vra, J., Vahsen, S. E., Vaitsas, G., Valassi, A., Vallazza, E., Vallereau, A., Vanhoefer, P., van Hoek, W. C., Van Hulse, C., van Winkle, D., Varner, G., Varnes, E. W., Varvell, K. E., Vasileiadis, G., Velikzhanin, Y. S., Verderi, M., Versillé, S., Vervink, K., Viaud, B., Vidal, P. B., Villa, S., Villanueva-Perez, P., Vinograd, E. L., Vitale, L., Vitug, G. M., Voß, C., Voci, C., Voena, C., Volk, A., von Wimmersperg-Toeller, J. H., Vorobyev, V., Vossen, A., Vuagnin, G., Vuosalo, C. O., Wacker, K., Wagner, A. P., Wagner, D. L., Wagner, G., Wagner, M. N., Wagner, S. R., Wagoner, D. E., Walker, D., Walkowiak, W., Wallom, D., Wang, C. C., Wang, C. H., Wang, J., Wang, J. G., Wang, K., Wang, L., Wang, L. L., Wang, P., Wang, T. J., Wang, W. F., Wang, X. L., Wang, Y. F., Wappler, F. R., Watanabe, M., Watson, A. T., Watson, J. E., Watson, N. K., Watt, M., Weatherall, J. H., Weaver, M., Weber, T., Wedd, R., Wei, J. T., Weidemann, A. W., Weinstein, A. J. R., Wenzel, W. A., West, C. A., West, C. G., West, T. J., White, E., White, R. M., Wicht, J., Widhalm, L., Wiechczynski, J., Wienands, U., Wilden, L., Wilder, M., Williams, D. C., Williams, G., Williams, J. C., Williams, K. M., Williams, M. I., Willocq, S. Y., Wilson, J. R., Wilson, M. G., Wilson, R. J., Winklmeier, F., Winstrom, L. O., Winter, M. A., Wisniewski, W. J., Wittgen, M., Wittlin, J., Wittmer, W., Wixted, R., Woch, A., Wogsland, B. J., Wong, Q. K., Wray, B. C., Wren, A. C., Wright, D. M., Wu, C. H., Wu, J., Wu, S. L., Wulsin, H. W., Xella, S. M., Xie, Q. L., Xie, Y., Xu, Z. Z., Yèche, Ch., Yamada, Y., Yamaga, M., Yamaguchi, A., Yamaguchi, H., Yamaki, T., Yamamoto, H., Yamamoto, N., Yamamoto, R. K., Yamamoto, S., Yamanaka, T., Yamaoka, H., Yamaoka, J., Yamaoka, Y., Yamashita, Y., Yamauchi, M., Yan, D. S., Yan, Y., Yanai, H., Yanaka, S., Yang, H., Yang, R., Yang, S., Yarritu, A. K., Yashchenko, S., Yashima, J., Yasin, Z., Yasu, Y., Ye, S. W., Yeh, P., Yi, J. I., Yi, K., Yi, M., Yin, Z. W., Ying, J., Yocky, G., Yokoyama, K., Yokoyama, M., Yokoyama, T., Yoshida, K., Yoshida, M., Yoshimura, Y., Young, C. C., Yu, C. X., Yu, Z., Yuan, C. Z., Yuan, Y., Yumiceva, F. X., Yusa, Y., Yushkov, A. N., Yuta, H., Zacek, V., Zain, S. B., Zallo, A., Zambito, S., Zander, D., Zang, S. L., Zanin, D., Zaslavsky, B. G., Zeng, Q. L., Zghiche, A., Zhang, B., Zhang, J., Zhang, L., Zhang, L. M., Zhang, S. Q., Zhang, Z. P., Zhao, H. W., Zhao, M., Zhao, Z. G., Zheng, Y., Zheng, Y. H., Zheng, Z. P., Zhilich, V., Zhou, P., Zhu, R. Y., Zhu, Y. S., Zhu, Z. M., Zhulanov, V., Ziegler, T., Ziegler, V., Zioulas, G., Zisman, M., Zito, M., Zürcher, D., Zwahlen, N., Zyukova, O., Živko, T., and Žontar, D.

Subjects
High Energy Physics - Experiment, High Energy Physics - Phenomenology
Abstract

This work is on the Physics of the B Factories. Part A of this book contains a brief description of the SLAC and KEK B Factories as well as their detectors, BaBar and Belle, and data taking related issues. Part B discusses tools and methods used by the experiments in order to obtain results. The results themselves can be found in Part C. Please note that version 3 on the archive is the auxiliary version of the Physics of the B Factories book. This uses the notation alpha, beta, gamma for the angles of the Unitarity Triangle. The nominal version uses the notation phi_1, phi_2 and phi_3. Please cite this work as Eur. Phys. J. C74 (2014) 3026., Comment: 928 pages, version 3 (arXiv:1406.6311v3) corresponds to the alpha, beta, gamma version of the book, the other versions use the phi1, phi2, phi3 notation

Published
2014
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37. Predictive value of quantitative 18F-FDG-PET radiomics analysis in patients with head and neck squamous cell carcinoma

Author

Roland M. Martens, Thomas Koopman, Daniel P. Noij, Elisabeth Pfaehler, Caroline Übelhör, Sughandi Sharma, Marije R. Vergeer, C. René Leemans, Otto S. Hoekstra, Maqsood Yaqub, Gerben J. Zwezerijnen, Martijn W. Heymans, Carel F. W. Peeters, Remco de Bree, Pim de Graaf, Jonas A. Castelijns, and Ronald Boellaard

Subjects
Head and Neck Neoplasms, Positron Emission Tomography Computed Tomography, Radiomics, Prognosis, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Background Radiomics is aimed at image-based tumor phenotyping, enabling application within clinical-decision-support-systems to improve diagnostic accuracy and allow for personalized treatment. The purpose was to identify predictive 18-fluor-fluoro-2-deoxyglucose (18F-FDG) positron-emission tomography (PET) radiomic features to predict recurrence, distant metastasis, and overall survival in patients with head and neck squamous cell carcinoma treated with chemoradiotherapy. Methods Between 2012 and 2018, 103 retrospectively (training cohort) and 71 consecutively included patients (validation cohort) underwent 18F-FDG-PET/CT imaging. The 434 extracted radiomic features were subjected, after redundancy filtering, to a projection resulting in outcome-independent meta-features (factors). Correlations between clinical, first-order 18F-FDG-PET parameters (e.g., SUVmean), and factors were assessed. Factors were combined with 18F-FDG-PET and clinical parameters in a multivariable survival regression and validated. A clinically applicable risk-stratification was constructed for patients’ outcome. Results Based on 124 retained radiomic features from 103 patients, 8 factors were constructed. Recurrence prediction was significantly most accurate by combining HPV-status, SUVmean, SUVpeak, factor 3 (histogram gradient and long-run-low-grey-level-emphasis), factor 4 (volume-difference, coarseness, and grey-level-non-uniformity), and factor 6 (histogram variation coefficient) (CI = 0.645). Distant metastasis prediction was most accurate assessing metabolic-active tumor volume (MATV)(CI = 0.627). Overall survival prediction was most accurate using HPV-status, SUVmean, SUVmax, factor 1 (least-axis-length, non-uniformity, high-dependence-of-high grey-levels), and factor 5 (aspherity, major-axis-length, inversed-compactness and, inversed-flatness) (CI = 0.764). Conclusions Combining HPV-status, first-order 18F-FDG-PET parameters, and complementary radiomic factors was most accurate for time-to-event prediction. Predictive phenotype-specific tumor characteristics and interactions might be captured and retained using radiomic factors, which allows for personalized risk stratification and optimizing personalized cancer care. Trial registration Trial NL3946 (NTR4111), local ethics commission reference: Prediction 2013.191 and 2016.498. Registered 7 August 2013, https://www.trialregister.nl/trial/3946

Published
2020
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38. Visual and quantitative evaluation of [18F]FES and [18F]FDHT PET in patients with metastatic breast cancer: an interobserver variability study

Author

Lemonitsa H. Mammatas, Clasina M. Venema, Carolina P. Schröder, Henrica C. W. de Vet, Michel van Kruchten, Andor W. J. M. Glaudemans, Maqsood M. Yaqub, Henk M. W. Verheul, Epie Boven, Bert van der Vegt, Erik F. J. de Vries, Elisabeth G. E. de Vries, Otto S. Hoekstra, Geke A. P. Hospers, and C. Willemien Menke-van der Houven van Oordt

Subjects
FES PET, FDHT PET, Breast cancer, Oestrogen receptor, Androgen receptor, Interobserver variability, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Purpose Correct identification of tumour receptor status is important for treatment decisions in breast cancer. [18F]FES PET and [18F]FDHT PET allow non-invasive assessment of the oestrogen (ER) and androgen receptor (AR) status of individual lesions within a patient. Despite standardised analysis techniques, interobserver variability can significantly affect the interpretation of PET results and thus clinical applicability. The purpose of this study was to determine visual and quantitative interobserver variability of [18F]FES PET and [18F]FDHT PET interpretation in patients with metastatic breast cancer. Methods In this prospective, two-centre study, patients with ER-positive metastatic breast cancer underwent both [18F]FES and [18F]FDHT PET/CT. In total, 120 lesions were identified in 10 patients with either conventional imaging (bone scan or lesions > 1 cm on high-resolution CT, n = 69) or only with [18F]FES and [18F]FDHT PET (n = 51). All lesions were scored visually and quantitatively by two independent observers. A visually PET-positive lesion was defined as uptake above background. For quantification, we used standardised uptake values (SUV): SUVmax, SUVpeak and SUVmean. Results Visual analysis showed an absolute positive and negative interobserver agreement for [18F]FES PET of 84% and 83%, respectively (kappa = 0.67, 95% CI 0.48–0.87), and 49% and 74% for [18F]FDHT PET, respectively (kappa = 0.23, 95% CI − 0.04–0.49). Intraclass correlation coefficients (ICC) for quantification of SUVmax, SUVpeak and SUVmean were 0.98 (95% CI 0.96–0.98), 0.97 (95% CI 0.96–0.98) and 0.89 (95% CI 0.83–0.92) for [18F]FES, and 0.78 (95% CI 0.66–0.85), 0.76 (95% CI 0.63–0.84) and 0.75 (95% CI 0.62–0.84) for [18F]FDHT, respectively. Conclusion Visual and quantitative evaluation of [18F]FES PET showed high interobserver agreement. These results support the use of [18F]FES PET in clinical practice. In contrast, visual agreement for [18F]FDHT PET was relatively low due to low tumour-background ratios, but quantitative agreement was good. This underscores the relevance of quantitative analysis of [18F]FDHT PET in breast cancer. Trial registration ClinicalTrials.gov , NCT01988324. Registered 20 November 2013, https://clinicaltrials.gov/ct2/show/NCT01988324?term=FDHT+PET&draw=1&rank=2 .

Published
2020
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41. Quantitative implications of the updated EARL 2019 PET–CT performance standards

Author

Andres Kaalep, Coreline N. Burggraaff, Simone Pieplenbosch, Eline E. Verwer, Terez Sera, Josee Zijlstra, Otto S. Hoekstra, Daniela E. Oprea-Lager, and Ronald Boellaard

Subjects
Performance, Harmonisation, PET, CT, Quantification, EARL accreditation, Medical physics. Medical radiology. Nuclear medicine, R895-920
Abstract

Abstract Purpose Recently, updated EARL specifications (EARL2) have been developed and announced. This study aims at investigating the impact of the EARL2 specifications on the quantitative reads of clinical PET–CT studies and testing a method to enable the use of the EARL2 standards whilst still generating quantitative reads compliant with current EARL standards (EARL1). Methods Thirteen non-small cell lung cancer (NSCLC) and seventeen lymphoma PET–CT studies were used to derive four image datasets—the first dataset complying with EARL1 specifications and the second reconstructed using parameters as described in EARL2. For the third (EARL2F6) and fourth (EARL2F7) dataset in EARL2, respectively, 6 mm and 7 mm Gaussian post-filtering was applied. We compared the results of quantitative metrics (MATV, SUVmax, SUVpeak, SUVmean, TLG, and tumor-to-liver and tumor-to-blood pool ratios) obtained with these 4 datasets in 55 suspected malignant lesions using three commonly used segmentation/volume of interest (VOI) methods (MAX41, A50P, SUV4). Results We found that with EARL2 MAX41 VOI method, MATV decreases by 22%, TLG remains unchanged and SUV values increase by 23–30% depending on the specific metric used. The EARL2F7 dataset produced quantitative metrics best aligning with EARL1, with no significant differences between most of the datasets (p>0.05). Different VOI methods performed similarly with regard to SUV metrics but differences in MATV as well as TLG were observed. No significant difference between NSCLC and lymphoma cancer types was observed. Conclusions Application of EARL2 standards can result in higher SUVs, reduced MATV and slightly changed TLG values relative to EARL1. Applying a Gaussian filter to PET images reconstructed using EARL2 parameters successfully yielded EARL1 compliant data.

Published
2019
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