Onderzoeksreis naar Indonesië: Stichting International Contract Research 1996

In november 1996 jongsleden ben ik met de Stichting International Contract Research naar Jakarta geweest. Aldaar hebben we met zeventien studenten voor verschillende Nederlandse bedrijven en overheidsorganisaties onderzoeken gedaan. Het was een enerverende ervaring

Delayed Effects of Radiofrequency Energy on Accessory Atrioventricular Connections

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74618/1/j.1540-8159.1993.tb04574.x.pd

Titration of Power Output During Radiofrequency Catheter Ablation of Atrioventricular Nodal Reentrant Tachycardia

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/75088/1/j.1540-8159.1993.tb01609.x.pd

How coagulation zone size is underestimated in computer modeling of RF ablation by ignoring the cooling phase just after RF power is switched off

[EN] All the numerical models developed for radiofrequency ablation so far have ignored the possible effect of the cooling phase (just after radiofrequency power is switched off) on the dimensions of the coagulation zone. Our objective was thus to quantify the differences in the minor radius of the coagulation zone computed by including and ignoring the cooling phase. We built models of RF tumor ablation with 2 needle-like electrodes: a dry electrode (5mm long and 17G in diameter) with a constant temperature protocol (70 degrees C) and a cooled electrode (30mm long and 17G in diameter) with a protocol of impedance control. We observed that the computed coagulation zone dimensions were always underestimated when the cooling phase was ignored. The mean values of the differences computed along the electrode axis were always lower than 0.15mm for the dry electrode and 1.5mm for the cooled electrode, which implied a value lower than 5% of the minor radius of the coagulation zone (which was 3mm for the dry electrode and 30mm for the cooled electrode). The underestimation was found to be dependent on the tissue characteristics: being more marked for higher values of specific heat and blood perfusion and less marked for higher values of thermal conductivity.Agencia Nacional de Promocion Cientifica y Tecnologica de Argentina, Grant/Award Number: PICT-2012-1201; Programa Estatal de Investigacion, Desarrollo e Innovacion Orientada a los Retos de la Sociedad, Grant/Award Number: TEC2014-52383-C3-R (TEC2014-52383-C3-1-R).Irastorza, RM.; Trujillo Guillen, M.; Berjano, E. (2017). How coagulation zone size is underestimated in computer modeling of RF ablation by ignoring the cooling phase just after RF power is switched off. International Journal for Numerical Methods in Biomedical Engineering. 33(11):2869-2877. doi:10.1002/cnm.2869S286928773311Berjano, E. J. (2006). BioMedical Engineering OnLine, 5(1), 24. doi:10.1186/1475-925x-5-24Pearce, J. A. (2013). Comparative analysis of mathematical models of cell death and thermal damage processes. International Journal of Hyperthermia, 29(4), 262-280. doi:10.3109/02656736.2013.786140Wittkampf, F. H. M., Nakagawa, H., Yamanashi, W. S., Imai, S., & Jackman, W. M. (1996). Thermal Latency in Radiofrequency Ablation. Circulation, 93(6), 1083-1086. doi:10.1161/01.cir.93.6.1083Pinto, C. H., Taminiau, A. H. M., Vanderschueren, G. M., Hogendoorn, P. C. W., Bloem, J. L., & Obermann, W. R. (2002). Technical Considerations in CT-Guided Radiofrequency Thermal Ablation of Osteoid Osteoma: Tricks of the Trade. American Journal of Roentgenology, 179(6), 1633-1642. doi:10.2214/ajr.179.6.1791633Fukushima, T., Ikeda, K., Kawamura, Y., Sorin, Y., Hosaka, T., Kobayashi, M., … Kumada, H. (2015). Randomized Controlled Trial Comparing the Efficacy of Impedance Control and Temperature Control of Radiofrequency Interstitial Thermal Ablation for Treating Small Hepatocellular Carcinoma. Oncology, 89(1), 47-52. doi:10.1159/000375166Abraham, J. P., & Sparrow, E. M. (2007). A thermal-ablation bioheat model including liquid-to-vapor phase change, pressure- and necrosis-dependent perfusion, and moisture-dependent properties. International Journal of Heat and Mass Transfer, 50(13-14), 2537-2544. doi:10.1016/j.ijheatmasstransfer.2006.11.045Pätz, T., Kröger, T., & Preusser, T. (2009). Simulation of Radiofrequency Ablation Including Water Evaporation. World Congress on Medical Physics and Biomedical Engineering, September 7 - 12, 2009, Munich, Germany, 1287-1290. doi:10.1007/978-3-642-03882-2_341Hall, S. K., Ooi, E. H., & Payne, S. J. (2015). Cell death, perfusion and electrical parameters are critical in models of hepatic radiofrequency ablation. International Journal of Hyperthermia, 31(5), 538-550. doi:10.3109/02656736.2015.1032370Chang, I. A. (2010). Considerations for Thermal Injury Analysis for RF Ablation Devices~!2009-09-09~!2009-12-19~!2010-02-04~! The Open Biomedical Engineering Journal, 4(2), 3-12. doi:10.2174/1874120701004020003Beop-Min Kim, Jacques, S. L., Rastegar, S., Thomsen, S., & Motamedi, M. (1996). Nonlinear finite-element analysis of the role of dynamic changes in blood perfusion and optical properties in laser coagulation of tissue. IEEE Journal of Selected Topics in Quantum Electronics, 2(4), 922-933. doi:10.1109/2944.577317Chang, I. A., & Nguyen, U. D. (2004). BioMedical Engineering OnLine, 3(1), 27. doi:10.1186/1475-925x-3-27Schutt, D. J., & Haemmerich, D. (2008). Effects of variation in perfusion rates and of perfusion models in computational models of radio frequency tumor ablation. Medical Physics, 35(8), 3462-3470. doi:10.1118/1.2948388Doss, J. D. (1982). Calculation of electric fields in conductive media. Medical Physics, 9(4), 566-573. doi:10.1118/1.595107Hasgall PA Di Gennaro F Baumgartner C IT'IS Database for thermal and electromagnetic parameters of biological tissues 10.13099/VIP21000-03-0 www.itis.ethz.ch/databasePandharipande, P. V., Krinsky, G. A., Rusinek, H., & Lee, V. S. (2005). Perfusion Imaging of the Liver: Current Challenges and Future Goals. Radiology, 234(3), 661-673. doi:10.1148/radiol.2343031362Tsushima, Y., Funabasama, S., Aoki, J., Sanada, S., & Endo, K. (2004). Quantitative perfusion map of malignant liver tumors, created from dynamic computed tomography data1. Academic Radiology, 11(2), 215-223. doi:10.1016/s1076-6332(03)00578-6Irastorza, R. M., Trujillo, M., Martel Villagrán, J., & Berjano, E. (2016). Computer modelling of RF ablation in cortical osteoid osteoma: Assessment of the insulating effect of the reactive zone. International Journal of Hyperthermia, 32(3), 221-230. doi:10.3109/02656736.2015.1135998Goldberg, S. N., Stein, M. C., Gazelle, G. S., Sheiman, R. G., Kruskal, J. B., & Clouse, M. E. (1999). Percutaneous Radiofrequency Tissue Ablation: Optimization of Pulsed-Radiofrequency Technique to Increase Coagulation Necrosis. Journal of Vascular and Interventional Radiology, 10(7), 907-916. doi:10.1016/s1051-0443(99)70136-3Trujillo, M., Bon, J., José Rivera, M., Burdío, F., & Berjano, E. (2016). Computer modelling of an impedance-controlled pulsing protocol for RF tumour ablation with a cooled electrode. International Journal of Hyperthermia, 32(8), 931-939. doi:10.1080/02656736.2016.1190868Venkatesan, A. M., Kadoury, S., Abi-Jaoudeh, N., Levy, E. B., Maass-Moreno, R., Krücker, J., … Wood, B. J. (2011). Real-time FDG PET Guidance during Biopsies and Radiofrequency Ablation Using Multimodality Fusion with Electromagnetic Navigation. Radiology, 260(3), 848-856. doi:10.1148/radiol.11101985Ertürk, M. A., Sathyanarayana Hegde, S., & Bottomley, P. A. (2016). Radiofrequency Ablation, MR Thermometry, and High-Spatial-Resolution MR Parametric Imaging with a Single, Minimally Invasive Device. Radiology, 281(3), 927-932. doi:10.1148/radiol.2016151447Bishop, M., Rajani, R., Plank, G., Gaddum, N., Carr-White, G., Wright, M., … Niederer, S. (2015). Three-dimensional atrial wall thickness maps to inform catheter ablation procedures for atrial fibrillation. Europace, 18(3), 376-383. doi:10.1093/europace/euv073Wang, H., Kang, W., Carrigan, T., Bishop, A., Rosenthal, N., Arruda, M., & Rollins, A. M. (2011). In vivo intracardiac optical coherence tomography imaging through percutaneous access: toward image-guided radio-frequency ablation. Journal of Biomedical Optics, 16(11), 110505. doi:10.1117/1.365696

Impedance Monitoring During Radiofrequency Catheter Ablation in Humans

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73768/1/j.1540-8159.1992.tb02897.x.pd

Comparison of the CES-D and PHQ-9 depression scales in people with type 2 diabetes in Tehran, Iran

<p>Abstract</p> <p>Background</p> <p>The quality of life in patients with various chronic disorders, including diabetes has been directly affected by depression. Depression makes patients less likely to manage their self-care regimens. Accurate assessment of depression in diabetic populations is important to the treatment of depression in this group and may improve diabetes management. To our best knowledge, there are few studies that have looked for utilizing questionnaires in screening for depression among patients with diabetes in Iran. Therefore the aim of this study was to assess the efficacy and accuracy of the Center for Epidemiological Studies Depression (CES-D) scale and the Patient Health Questionnaire-9 (PHQ-9), in comparison with clinical interview in people with type 2 diabetes.</p> <p>Methods</p> <p>Outpatients who attended diabetes clinics at IEM were recruited on a consecutive basis between February 2009 and July 2009. Inclusion criteria included patients with type 2 diabetes who could fluently read and speak Persian, had no severe diabetes complications and no history of psychological disorders. The history of psychological disorders was ascertained through patients' medical files, taking history of any medications in this regard. The study design was explained to all patients and informed consent was obtained. Volunteer patients completed the Persian version of the questionnaires (CES-D and PHQ-9) and a psychiatrist interviewed them based on Structured Clinical Interview (SCID) for DSM-IV criteria.</p> <p>Results</p> <p>Of the 185 patients, 43.2% were diagnosed as having Major Depressive Disorder (MDD) based on the clinical interview, 47.6% with PHQ-9 and 61.62% with CES-D. The Area Under the Curve (AUC) for the total score of PHQ-9 was 0.829 ± 0.30. A cut-off score for PHQ-9 of ≥ 13 provided an optimal balance between sensitivity (73.80%) and specificity (76.20%). For CES-D the AUC for the total score was 0.861 ± 0.029. Optimal balance between sensitivity (78.80%) and specificity (77.1%) was provided at cut-off score of ≥ 23.</p> <p>Conclusions</p> <p>It could be concluded that the PHQ-9 and CES-D perform well as screening instruments, but in diagnosing major depressive disorder, a formal diagnostic process following the PHQ-9 and also the CES-D remains essential.</p