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2. SPADnet: Embedded coincidence in a smart sensor network for PET applications

Author

Bruschini, C., Charbon, E., Veerappan, C., Braga, L.H.C., Massari, N., Perenzoni, M., Gasparini, L., Stoppa, D., Walker, R., Erdogan, A., Henderson, R.K., East, S., Grant, L., Jatekos, B., Ujhelyi, F., Erdei, G., Lörincz, E., André, L., Maingault, L., Reboud, V., Verger, L., Gros d'Aillon, E., Major, P., Papp, Z., and Németh, G.

Published
2014
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4. Use of early corticosteroid therapy on ICU admission in patients affected by severe pandemic (H1N1)v influenza A infection

Author

Martin Loeches, I, Lisboa, T, Rhodes, A, Moreno, Rp, Silva, E, Sprung, C, Chiche, Jd, Barahona, D, Villabon, M, Balasini, C, Pearse, Rm, Matos, R, Rello, J, Rodriguez, A, Capuzzo, M, Reina, R, Marsh, B, Flaaten, H, Sigurdsson, G, Ivana, Z, Cerny, V, Quintel, M, Welte, T, Mayorga, M, Offenstadt, G, Guidet, B, Levin, P, Rothen, Hu, Gomersall, C, Hashemian, Sm, Katsanoulas, C, Mouloudi, H, Kapadia, F, Valentin, A, Hedenstierna, G, Perner, A, Bugedo, G, Ruokonen, E, Soriano Arandes, A, Montejo, Jc, Peñíscola, R, Hermosa, C, Gordo, F, Latour, J, Vidaur, L, Alvarez Gonzalez, M, Alvarez Rocha, L, De Pablo, A, Ferri, C, Lopez De Arbina Martinez, Cânones, C, Insausti, J, Cambronero, J, Galvan, B, Luna, J, Blancas, R, Garcia, C, Sierra, R, Fernández Dorado, F, Monedero, P, Llagunes, J, Cobo, P, Socias, A, Leon Lopez, R, Esteban, E, Lacueva, M, Magret, M, Del Nogal, F, Dinis, A, Bártolo, A, Ramos, A, Franca, C, Estevens, C, Granja, C, Fidalgo, C, Almeida, E, Lafuente, E, Rua, F, Esteves, F, Clemente, J, Nóbrega, Jj, Pereira, Jm, Moura, Jp, Silva LP, Trindade E., Telo, L, Santos, L, Pedrosa, Mj, Oliveira, M, Resende, M, Catorze, N, Coutinho, P, Ribeiro, R, Miranda, I, Cardoso, T, Branco, V, Bellani, G, Urbino, R, Peris, A, Amatu, A, Berlot, G, Marzani, Fc, Corbanese, U, David, Antonio, Chiarandini, P, Della Corte, F, Caspani, Ml, Conio, A, Mangani, V, Tetamo, R, Wolfler, A, Tappatà, G, Vivaldi, N, Bertolini, G, Pelagalli, L, Molin, A, Girardis, M, Gristin, G, Lam, A, Crabb, I, Cusack, R, Jackson, R, Veerappan, C, Whiteley, C, Ware, T, Krueper, S, Mckinstry, C, Ferguson, A, Rubulotta, F, Valencia, E, Gonzalez, S, Cevallos, V, Zazu, A, Chaparro Fresco JN, Galindez, G, Barrios, C, Lovesio, C, Villamagua, B, Cadena, M, Salgado, E, García, Mf, Paredes, G, Donnelly, M, O'Croinin, D, Bates, J, Kavanagh, N, O'Brien, B, Plant, R, Scully, M, Farragher, R, Oliveira, L, Mataloun, S, Dantas, Vs, Simvoulidis, L, Duarte, P, Grion, C, Germano, A, Laake, Jh, Helset, E, Klausen, D, Flaatten, H, Bruheim, K, Kristinsson, B, Sigurdsson, Se, Hrubý, J, Valkova, R, Janda, R, Zykova, I, Kernchen, A, Bloos, F, Rosseau, S, Krassler, J, Fischer, F, Arroyo Sanchez, A, Barrionuevo Poquet, A, Ramos Palomino, I, Rafael, F, Salasfoch, J, Dubar, G, Tonnelier, Jm, Barbar, S, Dobrzynski, M, Mignon, A, Jakobson, D, Klein, M, Segal, E, Barlavie, Y, Hersch, M, Salomón, Zs, Zender, H, Chan, K, Buckley, T, Batranovic, U, Schaffer, I, Sretkovic, J, Koulenti, D, Mouloudi, E, Clouva Molyvdas PM, Gurjar, M, Vijayan, D, Hinterholzer, G, Kulier, A, Verlaat, C, Ebel, D, Persson, J, Walther, S, Petersen, P, Swinnen, W, Collin, V, Olsen, H, Gutierrez, P, Thiery, G, Laine, H, Rumba, A, Maiyalagan, S, Bui, T., Martin-Loeches, I., Lisboa, T., Rhodes, A., Moreno, R. P., Silva, E., Sprung, C., Chiche, J. -D., Barahona, D., Villabon, M., Balasini, C., Pearse, R., Matos, R., Rello, J., Rodriguez, A., Capuzzo, M., Reina, R., Marsh, B., Flaaten, H., Sigurdsson, G., Ivana, Z., Cerny, V., Quintel, M., Welte, T., Mayorga, M., Offenstadt, G., Guidet, B., Levin, P., Rothen, H. -U., Gomersall, C., Hashemian, S. M., Katsanoulas, C., Mouloudi, H., Kapadia, F., Valentin, A., Hedenstierna, G., Perner, A., Bugedo, G., Ruokonen, E., Arandes, A. S., Montejo, J. C., Peniscola, R., Hermosa, C., Gordo, F., Latour, J., Vidaur, L., Alvarez-Gonzalez, M., Alvarez-Rocha, L., De Pablo, A., Ferri, C., De Arbina Martinez, L., Canones, C., Insausti, J., Cambronero, J., Galvan, B., Luna, J., Blancas, R., Garcia, C., Sierra, R., Dorado, F. F., Monedero, P., Llagunes, J., Cobo, P., Socias, A., Leon-Lopez, R., Esteban, E., Lacueva, M., Magret, M., Del Nogal, F., Dinis, A., Bartolo, A., Ramos, A., Franca, C., Estevens, C., Granja, C., Fidalgo, C., Almeida, E., Lafuente, E., Rua, F., Esteves, F., Clemente, J., Nobrega, J. J., Pereira, J. M., Moura, J. P., Trindade E Silva, L. P., Telo, L., Santos, L., Pedrosa, M. J., Oliveira, M., Resende, M., Catorze, N., Coutinho, P., Ribeiro, R., Moreno, R., Miranda, I., Cardoso, T., Branco, V., Bellani, G., Urbino, R., Peris, A., Amatu, A., Berlot, G., Marzani, F. C., Corbanese, U., David, A., Chiarandini, P., Corte, F. D., Caspani, M. L., Alessandra, C., Mangani, V., Tetamo, R., Wolfler, A., Tappata, G., Nicoletta, V., Bertolini, G., Pelagalli, L., Molin, A., Girardis, M., Gristin, G., Lam, A., Crabb, I., Cusack, R., Jackson, R., Veerappan, C., Whiteley, C., Ware, T., Krueper, S., Mckinstry, C., Ferguson, A., Rubulotta, F., Valencia, E., Gonzalez, S., Cevallos, V., Zazu, A., Fresco, J. N. C., Galindez, G., Barrios, C., Lovesio, C., Villamagua, B., Cadena, M., Salgado, E., Garcia, M. F., Paredes, G., Donnelly, M., O'Croinin, D., Bates, J., Kavanagh, N., O'Brien, B., Plant, R., Scully, M., Farragher, R., Oliveira, L., Mataloun, S., Dantas, V. S., Simvoulidis, L., Duarte, P., Grion, C., Germano, A., Laake, J. H., Helset, E., Klausen, D., Flaatten, H., Bruheim, K., Kristinsson, B., Sigurdsson, S. E., Hruby, J., Valkova, R., Janda, R., Zykova, I., Kernchen, A., Bloos, F., Rosseau, S., Krassler, J., Fischer, F., Arroyo-Sanchez, A., Poquet, A. B., Palomino, I. R., Rafael, F., Salasfoch, J., Dubar, G., Tonnelier, J. -M., Barbar, S., Dobrzynski, M., Mignon, A., Jakobson, D., Klein, M., Segal, E., Barlavie, Y., Hersch, M., Salomon, Z. S., Zender, H., Rothen, H. U., Chan, K., Buckley, T., Batranovic, U., Schaffer, I., Sretkovic, J., Koulenti, D., Mouloudi, E., Clouva-Molyvdas, P. -M., Gurjar, M., Vijayan, D., Hinterholzer, G., Kulier, A., Verlaat, C., Ebel, D., Persson, J., Walther, S., Petersen, P., Swinnen, W., Collin, V., Olsen, H., Gutierrez, P., Thiery, G., Laine, H., Rumba, A., Maiyalagan, S., Bui, T., Martin Loeches, I, Lisboa, T, Rhodes, A, Moreno, R, Silva, E, Sprung, C, Chiche, J, Barahona, D, Villabon, M, Balasini, C, Pearse, R, Matos, R, Rello, J, and Pesenti, A

Subjects
Registrie, Male, Original, H1N1 Influenza, Adrenal Cortex Hormone, Critical Care and Intensive Care Medicine, Severity of Illness Index, law.invention, Influenza A Virus, H1N1 Subtype, Community-acquired pneumonia, Adrenal Cortex Hormones, law, Prospective Studies, Registries, 610 Medicine & health, Prospective cohort study, H1N1 Subtype, Influenza, Acute Respiratory Distress Syndrome, Cross Infection, Likelihood Functions, COPD, Acinetobacter, Hazard ratio, Middle Aged, Likelihood Function, Intensive care unit, Europe, Intensive Care Units, Community acquired pneumonia, Corticosteroid therapy, Pandemic (H1N1)v influenza A infection, Female, Survival Analysi, Human, Adult, medicine.medical_specialty, Chronic Obstructive Pulmonary Disease, ARDS, Community acquired pneumonia, Corticosteroid therapy, Pandemic (H1N1)v influenza A infection, Intensive Care Unit, Internal medicine, Correspondence, Influenza, Human, Severity of illness, medicine, Humans, H1N1 Subtype, Intensive care medicine, Pandemics, Pandemic, business.industry, Pneumonia, Odds ratio, medicine.disease, Survival Analysis, Influenza, Asthma, Prospective Studie, business
Abstract

Introduction: Early use of corticosteroids in patients affected by pandemic (H1N1)v influenza A infection, although relatively common, remains controversial. Methods: Prospective, observational, multicenter study from 23 June 2009 through 11 February 2010, reported in the European Society of Intensive Care Medicine (ESICM) H1N1 registry. Results: Two hundred twenty patients admitted to an intensive care unit (ICU) with completed outcome data were analyzed. Invasive mechanical ventilation was used in 155 (70.5%). Sixty-seven (30.5%) of the patients died in ICU and 75 (34.1%) whilst in hospital. One hundred twenty-six (57.3%) patients received corticosteroid therapy on admission to ICU. Patients who received corticosteroids were significantly older and were more likely to have coexisting asthma, chronic obstructive pulmonary disease (COPD), and chronic steroid use. These patients receiving corticosteroids had increased likelihood of developing hospital-acquired pneumonia (HAP) [26.2% versus 13.8%, p < 0.05; odds ratio (OR) 2.2, confidence interval (CI) 1.1-4.5]. Patients who received corticosteroids had significantly higher ICU mortality than patients who did not (46.0% versus 18.1%, p < 0.01; OR 3.8, CI 2.1-7.2). Cox regression analysis adjusted for severity and potential confounding factors identified that early use of corticosteroids was not significantly associated with mortality [hazard ratio (HR) 1.3, 95% CI 0.7-2.4, p = 0.4] but was still associated with an increased rate of HAP (OR 2.2, 95% CI 1.0-4.8, p < 0.05). When only patients developing acute respiratory distress syndrome (ARDS) were analyzed, similar results were observed. Conclusions: Early use of corticosteroids in patients affected by pandemic (H1N1)v influenza A infection did not result in better outcomes and was associated with increased risk of superinfections. associated with mortality [hazard ratio (HR) 1.3, 95% CI 0.7-2.4, p = 0.4] but was still associated with an increased rate of HAP (OR 2.2, 95% CI 1.0-4.8, p < 0.05). When only patients developing acute respiratory distress syndrome (ARDS) were analyzed, similar results were observed. Conclusions: Early use of corticosteroids in patients affected by pandemic (H1N1)v influenza A infection did not result in better outcomes and was associated with increased risk of superinfections. © Copyright jointly held by Springer and ESICM 2010.

Published
2011
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7. Updates from the SPADnet project (fully digital, scalable and networked photonic component for Time-of-Flight PET applications)

Author

Charbon, E. (author), Bruschini, C. (author), Veerappan, C. (author), Braga, L.H.C. (author), Massari, N. (author), Perenzoni, M. (author), Gasparini, L. (author), Stoppa, D. (author), Walker, R. (author), Charbon, E. (author), Bruschini, C. (author), Veerappan, C. (author), Braga, L.H.C. (author), Massari, N. (author), Perenzoni, M. (author), Gasparini, L. (author), Stoppa, D. (author), and Walker, R. (author)

Abstract

Microelectronics, Electrical Engineering, Mathematics and Computer Science

Published
2014

8. Data Acquisition System Design for a 160x128 Single-photon Image Sensor with On-pixel 55 ps Time-to-digital Converter

Author

Veerappan, C. (author) and Veerappan, C. (author)

Abstract

Time-resolved image sensors enabling picosecond resolutions over large formats are needed in many advanced imaging fields, from fluorescence lifetime imaging microscopy (FLIM) to positron emission tomography (PET). Integrated single-photon avalanche diode (SPAD) technology embodies the new frontiers of time-resolved imaging, namely better instrument response function, increased throughput and lower costs. SPADs have recently developed onto large arrays with increasing on-chip functionality. With larger array sizes however, the data generation rate has become a throughput bottleneck and thus necessitating an efficient data acquisition system. In this thesis a data acquisition system was developed, for one of the largest single-photon imager ever devised with 160x128 pixels capable of detecting the time-of-arrival of single photons with picosecond resolution. To handle the gigabytes of data generated every second, techniques such as a column based event-driven system for photon-starved applications was implemented. The thesis presents a test strategy and characterization methodology. Using the developed data acquisition system, the imager was tested and characterized successfully. To conclude, an example of a biological sample imaged with FLIM is shown as a demonstration of the potentialities of our system., MSc Microelectronics, Microelectronics & Computer Engineering, Electrical Engineering, Mathematics and Computer Science

Published
2010

9. First characterization of the SPADnet sensor: a digital silicon photomultiplier for PET applications

Author

Gros-Daillon, E, primary, Maingault, L, additional, André, L, additional, Reboud, V, additional, Verger, L, additional, Charbon, E, additional, Bruschini, C, additional, Veerappan, C, additional, Stoppa, D, additional, Massari, N, additional, Perenzoni, M, additional, Braga, L H C, additional, Gasparini, L, additional, Henderson, R K, additional, Walker, R, additional, East, S, additional, Grant, L, additional, Jatekos, B, additional, Lorincz, E, additional, Ujhelyi, F, additional, Erdei, G, additional, Major, P, additional, Papp, Z, additional, and Nemeth, G, additional

Published
2013
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17. A 5x5 SPADnet Digital SiPM Tile for PET Applications

Author

Gasparini, L., Braga, L. H. C., Massari, N., Perenzoni, M., Stoppa, D., Bruschini, Claudio, Charbon, Edoardo, Veerappan, C., Papp, Z., Major, P., Németh, G., Walker, R., Henderson, R. K., East, S., Gallagher, J., Grant, L., André, L., Gros d’Aillon, E., Lörincz, E., and Játékos, B.

Abstract

SPADnet is a sensor platform for the detection and processing of gamma photons generated in a PET system. SPADnet uses the novel technique of deferred coincidence detection, whereas timestamps associated with gamma events and their energy are routed at high speed (up to 3.3 million events per second) over a 2Gbps network, along with synchronization information. In this work, we describe SPADnet's key building block, a tile of SPADnet-I chips. SPADnet-I is a 50 mm2, 8x16 pixel digital SiPM where each pixel includes an array of 720 SPADs and the logic to count photons and record their arrival time. A fill factor of 42.9% is achieved. A distributed adder provides the number of photons detected throughout the whole array every 10 ns. On-chip triggering logic monitors this value in real time to discriminate gamma events from dark counts. The chip features a 10.8% energy resolution and a CRT of 288ps when coupled to a 3x3x10 mm3 LYSO crystal. High spatial resolution is obtained by combining the data generated by each pixel to efficiently locate the gamma absorption in the 2D space even when coupled to large arrays of crystal needles as small as 1.12x1.12mm2. The tile is built on a 5x5 array of SPADnet-I sensors. A Xilinx Spartan6 FPGA controls the whole module and monitors the gamma activity across the 25 sensors. Here, the large amount of data generated for each detected gamma is processed in real time to extract energy, position and time-of-arrival. Pile-up detection and energy windowing are applied to the events, which are then fed to a network of tiles for coincidence detection. A centralized snooper recognizes coincidence pairs while thermal, Compton, and single events are discarded. The system is inherently scalable, as it enables single- or multi-rings of photonic modules for potentially large PET systems.

20. SPADnet: Embedded coincidence in a smart sensor network for PET applications

Author

Bruschini, C., Charbon, E., Veerappan, C., Braga, L. H. C., Massari, N., Perenzoni, M., Gasparini, L., Stoppa, D., Walker, R., Erdogan, A., Henderson, R. K., East, S., Grant, L., Jatekos, B., Ujhelyi, F., Erdei, G., Lörincz, E., André, L., Maingault, L., Reboud, V., Verger, L., Gros D'Aillon, E., Major, P., Papp, Z., and Németh, G.

Subjects
Networking, CMOS, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, Single-Photon Avalanche Diodes (SPADs), TSV, Digital PET
Abstract

n this paper we illustrate the core technologies at the basis of the European SPADnet project (www.spadnet.eu), and present the corresponding first results. SPADnet is aimed at a new generation of MRI-compatible, scalable large area image sensors, based on CMOS technology, that are networked to perform gamma-ray detection and coincidence to be used primarily in (Time-of-Flight) Positron Emission Tomography (PET). The project innovates in several areas of PET systems, from optical coupling to single-photon sensor architectures, from intelligent ring networks to reconstruction algorithms. In addition, SPADnet introduced the first computational model enabling study of the full chain from gamma photons to network coincidence detection through scintillation events, optical coupling, etc.

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