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39 results on '"Collins-Fekete, Charles-Antoine"'

1. Immunocto: a massive immune cell database auto-generated for histopathology

Author

Simard, Mikaël, Shen, Zhuoyan, Hawkins, Maria A., and Collins-Fekete, Charles-Antoine

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

With the advent of novel cancer treatment options such as immunotherapy, studying the tumour immune micro-environment is crucial to inform on prognosis and understand response to therapeutic agents. A key approach to characterising the tumour immune micro-environment may be through combining (1) digitised microscopic high-resolution optical images of hematoxylin and eosin (H&E) stained tissue sections obtained in routine histopathology examinations with (2) automated immune cell detection and classification methods. However, current individual immune cell classification models for digital pathology present relatively poor performance. This is mainly due to the limited size of currently available datasets of individual immune cells, a consequence of the time-consuming and difficult problem of manually annotating immune cells on digitised H&E whole slide images. In that context, we introduce Immunocto, a massive, multi-million automatically generated database of 6,848,454 human cells, including 2,282,818 immune cells distributed across 4 subtypes: CD4$^+$ T cell lymphocytes, CD8$^+$ T cell lymphocytes, B cell lymphocytes, and macrophages. For each cell, we provide a 64$\times$64 pixels H&E image at $\mathbf{40}\times$ magnification, along with a binary mask of the nucleus and a label. To create Immunocto, we combined open-source models and data to automatically generate the majority of contours and labels. The cells are obtained from a matched H&E and immunofluorescence colorectal dataset from the Orion platform, while contours are obtained using the Segment Anything Model. A classifier trained on H&E images from Immunocto produces an average F1 score of 0.74 to differentiate the 4 immune cell subtypes and other cells. Immunocto can be downloaded at: https://zenodo.org/uploads/11073373.

Published
2024

2. Optimal particle type and projection number in multi-modality relative stopping power acquisition

Author

Dias, Marta F., Collins-Fekete, Charles-Antoine, Volz, Lennart, Baroni, Guido, Riboldi, Marco, and Seco, Joao

Subjects
Physics - Medical Physics
Abstract

Proton radiography combined with X-ray computed tomography (CT) has been proposed to obtain a patient-specific calibration curve and reduce range uncertainties in cancer treatment with charged particles. The main aim of this study was to identify the optimal charged particle for the generation of the radiographies and to determine the optimal number of projections necessary to obtain minimal range errors. Three charged particles were considered to generate the radiographies: proton (p-rad), helium ions ({\alpha}-rad) and carbon ions (c-rad). The problem formulation was viewed as a least square optimization, argmin_x (||Ax -b||_2^2 ), where the projection matrix A represents the cumulative path crossed by each particle in each material, b is the charged particle list-mode radiography expressed as the crossed water equivalent thickness (WET) and x is the relative stopping power (RSP) map to be optimized. The charged particle radiographies were simulated using the Geant4 Monte Carlo (MC) toolkit and an anthropomorphic adult head phantom. A was determined by calculating the particles trajectory through the X-ray CT employing a convex hull detection combined with a cubic spline path. For all particle types, the impact of using multiple projections was assessed (from 1 to 6 projections). In this study, tissue segmentation methods were also investigated in terms of achievable accuracy. The best results (mean RSP error below 0.7% and range errors below 1 mm) were obtained for a-rad when 3 projections were used. The dose delivered to the phantom by a single {\alpha}-rad was 8 \muGy, lower than the dose of X-ray radiography.

Published
2019

3. The impact of secondary fragments on the image quality of helium ion imaging.

Author

Volz, Lennart, Piersimoni, Pierluigi, Bashkirov, Vladimir A, Brons, Stephan, Collins-Fekete, Charles-Antoine, Johnson, Robert P, Schulte, Reinhard W, and Seco, Joao

Subjects
Humans, Helium, Radionuclide Imaging, Monte Carlo Method, Phantoms, Imaging, Image Processing, Computer-Assisted, helium ions, stopping power, nuclear fragmentation, ion imaging, computed tomography, single-event detector, Phantoms, Imaging, Image Processing, Computer-Assisted, Nuclear Medicine & Medical Imaging, Other Physical Sciences, Biomedical Engineering, Clinical Sciences
Abstract

Single-event ion imaging enables the direct reconstruction of the relative stopping power (RSP) information required for ion-beam therapy. Helium ions were recently hypothesized to be the optimal species for such technique. The purpose of this work is to investigate the effect of secondary fragments on the image quality of helium CT (HeCT) and to assess the performance of a prototype proton CT (pCT) scanner when operated with helium beams in Monte Carlo simulations and experiment. Experiments were conducted installing the U.S. pCT consortium prototype scanner at the Heidelberg Ion-Beam Therapy Center (HIT). Simulations were performed with the scanner using the TOPAS toolkit. HeCT images were reconstructed for a cylindrical water phantom, the CTP404 (sensitometry), and the CTP528 (line-pair) [Formula: see text] ® modules. To identify and remove individual events caused by fragmentation, the multistage energy detector of the scanner was adapted to function as a [Formula: see text] telescope. The use of the developed filter eliminated the otherwise arising ring artifacts in the HeCT reconstructed images. For the HeCT reconstructed images of a water phantom, the maximum RSP error was improved by almost a factor 8 with respect to unfiltered images in the simulation and a factor 10 in the experiment. Similarly, for the CTP404 module, the mean RSP accuracy improved by a factor 6 in both the simulation and the experiment when the filter was applied (mean relative error 0.40% in simulation, 0.45% in experiment). In the evaluation of the spatial resolution through the CTP528 module, the main effect of the filter was noise reduction. For both simulated and experimental images the spatial resolution was  ∼4 lp cm-1. In conclusion, the novel filter developed for secondary fragments proved to be effective in improving the visual quality and RSP accuracy of the reconstructed images. With the filter, the pCT scanner is capable of accurate HeCT imaging.

Published
2018

5. A theoretical framework to predict the most likely ion path in particle imaging

Author

Collins-Fekete, Charles-Antoine, Volz, Lennart, Portillo, Stephen K. N., Beaulieu, Luc, and Seco, Joao

Subjects
Physics - Medical Physics
Abstract

In this work, a generic rigorous Bayesian formalism is introduced to predict the most likely path of any ion crossing a medium between two detection points. The path is predicted based on a combination of the particle scattering in the material and measurements of its initial and final position, direction and energy. The path estimate's precision is compared to the Monte Carlo simulated path. Every ion from hydrogen to carbon is simulated in two scenarios to estimate the accuracy achievable: one where the range is fixed and one where the initial velocity is fixed. In the scenario where the range is kept constant, the maximal root-mean-square error between the estimated path and the Monte Carlo path drops significantly between the proton path estimate (0.50 mm) and the helium path estimate (0.18 mm), but less so up to the carbon path estimate (0.09 mm). In the scenario where the initial velocity is kept constant, helium have systematically the minimal root-mean-square error throughout the path. As a result, helium is found to be the optimal particle for ion imaging., Comment: 20 pages, 6 figures, 1 table

Published
2016
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10. Stopping power accuracy and achievable spatial resolution of helium ion imaging using a prototype particle CT detector system

Author

Volz, Lennart, Collins-Fekete, Charles-Antoine, Piersimoni, Pierluigi, Johnson, Robert P, Bashkirov, Vladimir, Schulte, Reinhard, and Seco, Joao

Subjects
Engineering, Biomedical Engineering, Biomedical Imaging, Bioengineering, Computed Tomography, Helium, Particle Imaging, Proton, Radiography, Resolution, Stopping Power, Biomedical engineering
Abstract

A precise relative stopping power map of the patient is crucial for accurate particle therapy. Charged particle imaging determines the stopping power either tomographically - particle computed tomography (pCT) - or by combining prior knowledge from particle radiography (pRad) and x-ray CT. Generally, multiple Coulomb scattering limits the spatial resolution. Compared to protons, heavier particles scatter less due to their lower charge/mass ratio. A theoretical framework to predict the most likely trajectory of particles in matter was developed for light ions up to carbon and was found to be the most accurate for helium comparing for fixed initial velocity. To further investigate the potential of helium in particle imaging, helium computed tomography (HeCT) and radiography (HeRad) were studied at the Heidelberg Ion-Beam Therapy Centre (HIT) using a prototype pCT detector system registering individual particles, originally developed by the U.S. pCT collaboration. Several phantoms were investigated: modules of the Catphan QA phantom for analysis of spatial resolution and achievable stopping power accuracy, a paediatric head phantom (CIRS) and a custommade phantom comprised of animal meat enclosed in a 2 % agarose mixture representing human tissue. The pCT images were reconstructed applying the CARP iterative reconstruction algorithm. The MTF10% was investigated using a sharp edge gradient technique. HeRad provides a spatial resolution above that of protons (MTF1010%=6.07 lp/cm for HeRad versus MTF10%=3.35 lp/cm for proton radiography). For HeCT, the spatial resolution was limited by the number of projections acquired (90 projections for a full scan). The RSP accuracy for all inserts of the Catphan CTP404 module was found to be 2.5% or better and is subject to further optimisation. In conclusion, helium imaging appears to offer higher spatial resolution compared to proton imaging. In future studies, the advantage of helium imaging compared to other imaging modalities in clinical applications will be further explored.

Published
2017

11. Body composition and lung cancer-associated cachexia in TRACERx

Author

Al-Sawaf, Othman, Weiss, Jakob, Skrzypski, Marcin, Lam, Jie Min, Karasaki, Takahiro, Zambrana, Francisco, Kidd, Andrew C, Frankell, Alexander M, Watkins, Thomas BK, Martinez-Ruiz, Carlos, Puttick, Clare, Black, James RM, Huebner, Ariana, Al Bakir, Maise, Sokac, Mateo, Collins, Susie, Veeriah, Selvaraju, Magno, Neil, Naceur-Lombardelli, Cristina, Prymas, Paulina, Toncheva, Antonia, Ward, Sophia, Jayanth, Nick, Salgado, Roberto, Bridge, Christopher P, Christiani, David C, Mak, Raymond H, Bay, Camden, Rosenthal, Michael, Sattar, Naveed, Welsh, Paul, Liu, Ying, Perrimon, Norbert, Popuri, Karteek, Beg, Mirza Faisal, McGranahan, Nicholas, Hackshaw, Allan, Breen, Danna M, O'Rahilly, Stephen, Birkbak, Nicolai J, Aerts, Hugo JWL, Jamal-Hanjani, Mariam, Swanton, Charles, Lester, Jason F, Bajaj, Amrita, Nakas, Apostolos, Sodha-Ramdeen, Azmina, Ang, Keng, Tufail, Mohamad, Chowdhry, Mohammed Fiyaz, Scotland, Molly, Boyles, Rebecca, Rathinam, Sridhar, Wilson, Claire, Marrone, Domenic, Dulloo, Sean, Fennell, Dean A, Matharu, Gurdeep, Shaw, Jacqui A, Riley, Joan, Primrose, Lindsay, Boleti, Ekaterini, Cheyne, Heather, Khalil, Mohammed, Richardson, Shirley, Cruickshank, Tracey, Price, Gillian, Kerr, Keith M, Benafif, Sarah, Gilbert, Kayleigh, Naidu, Babu, Patel, Akshay J, Osman, Aya, Lacson, Christer, Langman, Gerald, Shackleford, Helen, Djearaman, Madava, Kadiri, Salma, Middleton, Gary, Leek, Angela, Hodgkinson, Jack Davies, Totten, Nicola, Montero, Angeles, Smith, Elaine, Fontaine, Eustace, Granato, Felice, Doran, Helen, Novasio, Juliette, Rammohan, Kendadai, Joseph, Leena, Bishop, Paul, Shah, Rajesh, Moss, Stuart, Joshi, Vijay, Crosbie, Philip, Gomes, Fabio, Brown, Kate, Carter, Mathew, Chaturvedi, Anshuman, Priest, Lynsey, Oliveira, Pedro, Lindsay, Colin R, Blackhall, Fiona H, Krebs, Matthew G, Summers, Yvonne, Clipson, Alexandra, Tugwood, Jonathan, Kerr, Alastair, Rothwell, Dominic G, Kilgour, Elaine, Dive, Caroline, Schwarz, Roland F, Kaufmann, Tom L, Wilson, Gareth A, Rosenthal, Rachel, Van Loo, Peter, Szallasi, Zoltan, Kisistok, Judit, Diossy, Miklos, Demeulemeester, Jonas, Bunkum, Abigail, Stewart, Aengus, Magness, Alastair, Rowan, Andrew, Karamani, Angeliki, Chain, Benny, Campbell, Brittany B, Castignani, Carla, Bailey, Chris, Abbosh, Christopher, Weeden, Clare E, Lee, Claudia, Richard, Corentin, Hiley, Crispin T, Moore, David A, Pearce, David R, Karagianni, Despoina, Biswas, Dhruva, Levi, Dina, Hoxha, Elena, Cadieux, Elizabeth Larose, Lim, Emilia L, Colliver, Emma, Nye, Emma, Gronroos, Eva, Galvez-Cancino, Felip, Athanasopoulou, Foteini, Gimeno-Valiente, Francisco, Kassiotis, George, Stavrou, Georgia, Mastrokalos, Gerasimos, Zhai, Haoran, Lowe, Helen L, Matos, Ignacio Garcia, Goldman, Jacki, Reading, James L, Herrero, Javier, Rane, Jayant K, Nicod, Jerome, Hartley, John A, Peggs, Karl S, Enfield, Katey SS, Selvaraju, Kayalvizhi, Thol, Kerstin, Litchfield, Kevin, Ng, Kevin W, Chen, Kezhong, Dijkstra, Krijn, Grigoriadis, Kristiana, Thakkar, Krupa, Ensell, Leah, Shah, Mansi, Duran, Marcos Vasquez, Litovchenko, Maria, Sunderland, Mariana Werner, Hill, Mark S, Dietzen, Michelle, Leung, Michelle, Escudero, Mickael, Angelova, Mihaela, Tanic, Miljana, Sivakumar, Monica, Kanu, Nnennaya, Chervova, Olga, Lucas, Olivia, Pich, Oriol, Hobson, Philip, Pawlik, Piotr, Stone, Richard Kevin, Bentham, Robert, Hynds, Robert E, Vendramin, Roberto, Saghafinia, Sadegh, Lopez, Saioa, Gamble, Samuel, Ung, Seng Kuong Anakin, Quezada, Sergio A, Vanloo, Sharon, Zaccaria, Simone, Hessey, Sonya, Boeing, Stefan, Beck, Stephan, Bola, Supreet Kaur, Denner, Tamara, Marafioti, Teresa, Mourikis, Thanos P, Spanswick, Victoria, Barbe, Vittorio, Lu, Wei-Ting, Hill, William, Liu, Wing Kin, Wu, Yin, Naito, Yutaka, Ramsden, Zoe, Veiga, Catarina, Royle, Gary, Collins-Fekete, Charles-Antoine, Fraioli, Francesco, Ashford, Paul, Clark, Tristan, Forster, Martin D, Lee, Siow Ming, Borg, Elaine, Falzon, Mary, Papadatos-Pastos, Dionysis, Wilson, James, Ahmad, Tanya, Procter, Alexander James, Ahmed, Asia, Taylor, Magali N, Nair, Arjun, Lawrence, David, Patrini, Davide, Navani, Neal, Thakrar, Ricky M, Janes, Sam M, Hoogenboom, Emilie Martinoni, Monk, Fleur, Holding, James W, Choudhary, Junaid, Bhakhri, Kunal, Scarci, Marco, Hayward, Martin, Panagiotopoulos, Nikolaos, Gorman, Pat, Khiroya, Reena, Stephens, Robert CM, Wong, Yien Ning Sophia, Bandula, Steve, Sharp, Abigail, Smith, Sean, Gower, Nicole, Dhanda, Harjot Kaur, Chan, Kitty, Pilotti, Camilla, Leslie, Rachel, Grapa, Anca, Zhang, Hanyun, AbdulJabbar, Khalid, Pan, Xiaoxi, Yuan, Yinyin, Chuter, David, MacKenzie, Mairead, Chee, Serena, Alzetani, Aiman, Cave, Judith, Scarlett, Lydia, Richards, Jennifer, Ingram, Papawadee, Austin, Silvia, Lim, Eric, De Sousa, Paulo, Jordan, Simon, Rice, Alexandra, Raubenheimer, Hilgardt, Bhayani, Harshil, Ambrose, Lyn, Devaraj, Anand, Chavan, Hema, Begum, Sofina, Buderi, Silviu, Kaniu, Daniel, Malima, Mpho, Booth, Sarah, Nicholson, Andrew G, Fernandes, Nadia, Shah, Pratibha, Proli, Chiara, Hewish, Madeleine, Danson, Sarah, Shackcloth, Michael J, Robinson, Lily, Russell, Peter, Blyth, Kevin G, Dick, Craig, Le Quesne, John, Kirk, Alan, Asif, Mo, Bilancia, Rocco, Kostoulas, Nikos, and Thomas, Mathew

Subjects
Male, Proteomics, Cachexia, Lung Neoplasms, Antigens, Neoplasm, Carcinoma, Non-Small-Cell Lung, Body Weight, Body Composition, Humans, Neoplasm Recurrence, Local, Muscle, Skeletal, Neoplasm Proteins
Abstract

Cancer-associated cachexia (CAC) is a major contributor to morbidity and mortality in individuals with non-small cell lung cancer. Key features of CAC include alterations in body composition and body weight. Here, we explore the association between body composition and body weight with survival and delineate potential biological processes and mediators that contribute to the development of CAC. Computed tomography-based body composition analysis of 651 individuals in the TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy (Rx)) study suggested that individuals in the bottom 20th percentile of the distribution of skeletal muscle or adipose tissue area at the time of lung cancer diagnosis, had significantly shorter lung cancer-specific survival and overall survival. This finding was validated in 420 individuals in the independent Boston Lung Cancer Study. Individuals classified as having developed CAC according to one or more features at relapse encompassing loss of adipose or muscle tissue, or body mass index-adjusted weight loss were found to have distinct tumor genomic and transcriptomic profiles compared with individuals who did not develop such features. Primary non-small cell lung cancers from individuals who developed CAC were characterized by enrichment of inflammatory signaling and epithelial-mesenchymal transitional pathways, and differentially expressed genes upregulated in these tumors included cancer-testis antigen MAGEA6 and matrix metalloproteinases, such as ADAMTS3. In an exploratory proteomic analysis of circulating putative mediators of cachexia performed in a subset of 110 individuals from TRACERx, a significant association between circulating GDF15 and loss of body weight, skeletal muscle and adipose tissue was identified at relapse, supporting the potential therapeutic relevance of targeting GDF15 in the management of CAC. ispartof: NATURE MEDICINE vol:29 issue:4 ispartof: location:United States status: Published online

Published
2023

12. The evolution of non-small cell lung cancer metastases in TRACERx

Author

Al Bakir, Maise, Huebner, Ariana, Martinez-Ruiz, Carlos, Grigoriadis, Kristiana, Watkins, Thomas BK, Pich, Oriol, Moore, David A, Veeriah, Selvaraju, Ward, Sophia, Laycock, Joanne, Johnson, Diana, Rowan, Andrew, Razaq, Maryam, Akther, Mita, Naceur-Lombardelli, Cristina, Prymas, Paulina, Toncheva, Antonia, Hessey, Sonya, Dietzen, Michelle, Colliver, Emma, Frankell, Alexander, Bunkum, Abigail, Lim, Emilia L, Karasaki, Takahiro, Abbosh, Christopher, Hiley, Crispin T, Hill, Mark S, Cook, Daniel E, Wilson, Gareth A, Salgado, Roberto, Nye, Emma, Stone, Richard Kevin, Fennell, Dean A, Price, Gillian, Kerr, Keith M, Naidu, Babu, Middleton, Gary, Summers, Yvonne, Lindsay, Colin R, Blackhall, Fiona H, Cave, Judith, Blyth, Kevin G, Nair, Arjun, Ahmed, Asia, Taylor, Magali N, Procter, Alexander James, Falzon, Mary, Lawrence, David, Navani, Neal, Thakrar, Ricky M, Janes, Sam M, Papadatos-Pastos, Dionysis, Forster, Martin D, Lee, Siow Ming, Ahmad, Tanya, Quezada, Sergio, Peggs, Karl S, Van Loo, Peter, Dive, Caroline, Hackshaw, Allan, Birkbak, Nicolai J, Zaccaria, Simone, Jamal-Hanjani, Mariam, McGranahan, Nicholas, Swanton, Charles, Lester, Jason F, Bajaj, Amrita, Nakas, Apostolos, Sodha-Ramdeen, Azmina, Ang, Keng, Tufail, Mohamad, Chowdhry, Mohammed Fiyaz, Scotland, Molly, Boyles, Rebecca, Rathinam, Sridhar, Wilson, Claire, Marrone, Domenic, Dulloo, Sean, Matharu, Gurdeep, Shaw, Jacqui A, Riley, Joan, Primrose, Lindsay, Boleti, Ekaterini, Cheyne, Heather, Khalil, Mohammed, Richardson, Shirley, Cruickshank, Tracey, Benafif, Sarah, Gilbert, Kayleigh, Patel, Akshay J, Osman, Aya, Lacson, Christer, Langman, Gerald, Shackleford, Helen, Djearaman, Madava, Kadiri, Salma, Leek, Angela, Hodgkinson, Jack Davies, Totten, Nicola, Montero, Angeles, Smith, Elaine, Fontaine, Eustace, Granato, Felice, Doran, Helen, Novasio, Juliette, Rammohan, Kendadai, Joseph, Leena, Bishop, Paul, Shah, Rajesh, Moss, Stuart, Joshi, Vijay, Crosbie, Philip, Gomes, Fabio, Brown, Kate, Carter, Mathew, Chaturvedi, Anshuman, Priest, Lynsey, Oliveira, Pedro, Krebs, Matthew G, Clipson, Alexandra, Tugwood, Jonathan, Kerr, Alastair, Rothwell, Dominic G, Kilgour, Elaine, Aerts, Hugo JWL, Schwarz, Roland F, Kaufmann, Tom L, Rosenthal, Rachel, Szallasi, Zoltan, Kisistok, Judit, Sokac, Mateo, Diossy, Miklos, Demeulemeester, Jonas, Stewart, Aengus, Magness, Alastair, Karamani, Angeliki, Chain, Benny, Campbell, Brittany B, Castignani, Carla, Bailey, Chris, Puttick, Clare, Weeden, Clare E, Lee, Claudia, Richard, Corentin, Pearce, David R, Karagianni, Despoina, Biswas, Dhruva, Levi, Dina, Hoxha, Elena, Larose Cadieux, Elizabeth, Gronroos, Eva, Galvez-Cancino, Felip, Athanasopoulou, Foteini, Gimeno-Valiente, Francisco, Kassiotis, George, Stavrou, Georgia, Mastrokalos, Gerasimos, Zhai, Haoran, Lowe, Helen L, Matos, Ignacio, Goldman, Jacki, Reading, James L, Black, James RM, Herrero, Javier, Rane, Jayant K, Nicod, Jerome, Lam, Jie Min, Hartley, John A, Enfield, Katey SS, Selvaraju, Kayalvizhi, Thol, Kerstin, Litchfield, Kevin, Ng, Kevin W, Chen, Kezhong, Dijkstra, Krijn, Thakkar, Krupa, Ensell, Leah, Shah, Mansi, Vasquez, Marcos, Litovchenko, Maria, Werner Sunderland, Mariana, Leung, Michelle, Escudero, Mickael, Angelova, Mihaela, Tanic, Miljana, Sivakumar, Monica, Kanu, Nnennaya, Chervova, Olga, Lucas, Olivia, Al-Sawaf, Othman, Hobson, Philip, Pawlik, Piotr, Bentham, Robert, Hynds, Robert E, Vendramin, Roberto, Saghafinia, Sadegh, Lopez, Saioa, Gamble, Samuel, Ung, Seng Kuong Anakin, Vanloo, Sharon, Boeing, Stefan, Beck, Stephan, Bola, Supreet Kaur, Denner, Tamara, Marafioti, Teresa, Mourikis, Thanos P, Spanswick, Victoria, Barbe, Vittorio, Lu, Wei-Ting, Hill, William, Liu, Wing Kin, Wu, Yin, Naito, Yutaka, Ramsden, Zoe, Veiga, Catarina, Royle, Gary, Collins-Fekete, Charles-Antoine, Fraioli, Francesco, Ashford, Paul, Clark, Tristan, Borg, Elaine, Wilson, James, Patrini, Davide, Martinoni Hoogenboom, Emilie, Monk, Fleur, Holding, James W, Choudhary, Junaid, Bhakhri, Kunal, Scarci, Marco, Hayward, Martin, Panagiotopoulos, Nikolaos, Gorman, Pat, Khiroya, Reena, Stephens, Robert CM, Wong, Yien Ning Sophia, Bandula, Steve, Sharp, Abigail, Smith, Sean, Gower, Nicole, Dhanda, Harjot Kaur, Chan, Kitty, Pilotti, Camilla, Leslie, Rachel, Grapa, Anca, Zhang, Hanyun, AbdulJabbar, Khalid, Pan, Xiaoxi, Yuan, Yinyin, Chuter, David, MacKenzie, Mairead, Chee, Serena, Alzetani, Aiman, Scarlett, Lydia, Richards, Jennifer, Ingram, Papawadee, Austin, Silvia, Lim, Eric, De Sousa, Paulo, Jordan, Simon, Rice, Alexandra, Raubenheimer, Hilgardt, Bhayani, Harshil, Ambrose, Lyn, Devaraj, Anand, Chavan, Hema, Begum, Sofina, Buderi, Silviu, Kaniu, Daniel, Malima, Mpho, Booth, Sarah, Nicholson, Andrew G, Fernandes, Nadia, Shah, Pratibha, Proli, Chiara, Hewish, Madeleine, Danson, Sarah, Shackcloth, Michael J, Robinson, Lily, Russell, Peter, Dick, Craig, Le Quesne, John, Kirk, Alan, Asif, Mo, Bilancia, Rocco, Kostoulas, Nikos, and Thomas, Mathew

Subjects
Clonal Evolution, Cohort Studies, Evolution, Molecular, Lung Neoplasms, Carcinoma, Non-Small-Cell Lung, Disease Progression, Humans, Neoplasm Metastasis, Neoplasm Recurrence, Local, Clone Cells
Abstract

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse. ispartof: NATURE vol:616 issue:7957 ispartof: location:England status: Published online

Published
2023

13. The evolution of lung cancer and impact of subclonal selection in TRACERx

Author

Frankell, Alexander M, Dietzen, Michelle, Al Bakir, Maise, Lim, Emilia L, Karasaki, Takahiro, Ward, Sophia, Veeriah, Selvaraju, Colliver, Emma, Huebner, Ariana, Bunkum, Abigail, Hill, Mark S, Grigoriadis, Kristiana, Moore, David A, Black, James RM, Liu, Wing Kin, Thol, Kerstin, Pich, Oriol, Watkins, Thomas BK, Naceur-Lombardelli, Cristina, Cook, Daniel E, Salgado, Roberto, Wilson, Gareth A, Bailey, Chris, Angelova, Mihaela, Bentham, Robert, Martinez-Ruiz, Carlos, Abbosh, Christopher, Nicholson, Andrew G, Le Quesne, John, Biswas, Dhruva, Rosenthal, Rachel, Puttick, Clare, Hessey, Sonya, Lee, Claudia, Prymas, Paulina, Toncheva, Antonia, Smith, Jon, Xing, Wei, Nicod, Jerome, Price, Gillian, Kerr, Keith M, Naidu, Babu, Middleton, Gary, Blyth, Kevin G, Fennell, Dean A, Forster, Martin D, Lee, Siow Ming, Falzon, Mary, Hewish, Madeleine, Shackcloth, Michael J, Lim, Eric, Benafif, Sarah, Russell, Peter, Boleti, Ekaterini, Krebs, Matthew G, Lester, Jason F, Papadatos-Pastos, Dionysis, Ahmad, Tanya, Thakrar, Ricky M, Lawrence, David, Navani, Neal, Janes, Sam M, Dive, Caroline, Blackhall, Fiona H, Summers, Yvonne, Cave, Judith, Marafioti, Teresa, Herrero, Javier, Quezada, Sergio A, Peggs, Karl S, Schwarz, Roland F, Van Loo, Peter, Miedema, Daniel M, Birkbak, Nicolai J, Hiley, Crispin T, Hackshaw, Allan, Zaccaria, Simone, Jamal-Hanjani, Mariam, McGranahan, Nicholas, Swanton, Charles, Bajaj, Amrita, Nakas, Apostolos, Sodha-Ramdeen, Azmina, Ang, Keng, Tufail, Mohamad, Chowdhry, Mohammed Fiyaz, Scotland, Molly, Boyles, Rebecca, Rathinam, Sridhar, Wilson, Claire, Marrone, Domenic, Dulloo, Sean, Matharu, Gurdeep, Shaw, Jacqui A, Riley, Joa, Primrose, Lindsay, Cheyne, Heather, Khalil, Mohammed, Richardson, Shirley, Cruickshank, Tracey, Gilbert, Kayleigh, Patel, Akshay J, Osman, Aya, Lacson, Christer, Langman, Gerald, Shackleford, Helen, Djearaman, Madava, Kadiri, Salma, Leek, Angela, Hodgkinson, Jack Davies, Totten, Nicola, Montero, Angeles, Smith, Elaine, Fontaine, Eustace, Granato, Felice, Doran, Helen, Novasio, Juliette, Rammohan, Kendadai, Joseph, Leena, Bishop, Paul, Shah, Rajesh, Moss, Stuart, Joshi, Vijay, Crosbie, Philip, Gomes, Fabio, Brown, Kate, Carter, Mathew, Chaturvedi, Anshuman, Priest, Lynsey, Oliveira, Pedro, Lindsay, Colin R, Clipson, Alexandra, Tugwood, Jonathan, Kerr, Alastair, Rothwell, Dominic G, Kilgour, Elaine, Aerts, Hugo JWL, Kaufmann, Tom L, Szallasi, Zoltan, Kisistok, Judit, Sokac, Mateo, Diossy, Miklos, Demeulemeester, Jonas, Stewart, Aengus, Magness, Alastair, Rowan, Andrew, Karamani, Angeliki, Chain, Benny, Campbell, Brittany B, Castignani, Carla, Weeden, Clare E, Richard, Corentin, Pearce, David R, Karagianni, Despoina, Levi, Dina, Hoxha, Elena, Larose Cadieux, Elizabeth, Nye, Emma, Gronroos, Eva, Galvez-Cancino, Felip, Athanasopoulou, Foteini, Gimeno-Valiente, Francisco, Kassiotis, George, Stavrou, Georgia, Mastrokalos, Gerasimos, Zhai, Haoran L, Lowe, Helen L, Matos, Ignacio, Goldman, Jacki, Reading, James L, Rane, Jayant K, Lam, Jie Min, Hartley, John A, Enfield, Katey SS, Selvaraju, Kayalvizhi, Litchfield, Kevin, Ng, Kevin W, Chen, Kezhong, Dijkstra, Krijn, Thakkar, Krupa, Ensell, Leah, Shah, Mansi, Vasquez, Marcos, Litovchenko, Maria, Werner Sunderland, Mariana, Leung, Michelle, Escudero, Mickael, Tanic, Miljana, Sivakumar, Monica, Kanu, Nnennaya, Chervova, Olga, Lucas, Olivia, Al-Sawaf, Othman, Hobson, Philip, Pawlik, Piotr, Stone, Richard Kevin, Hynds, Robert E, Vendramin, Roberto, Saghafinia, Sadegh, Lopez, Saioa, Gamble, Samuel, Ung, Seng Kuong Anakin, Vanloo, Sharon, Boeing, Stefan, Beck, Stephan, Bola, Supreet Kaur, Denner, Tamara, Mourikis, Thanos P, Spanswick, Victoria, Barbe, Vittorio, Lu, Wei-Ting, Hill, William, Wu, Yin, Naito, Yutaka, Ramsden, Zoe, Veiga, Catarina, Royle, Gary, Collins-Fekete, Charles-Antoine, Fraioli, Francesco, Ashford, Paul, Clark, Tristan, Borg, Elaine, Wilson, James, Procter, Alexander James, Ahmed, Asia, Taylor, Magali N, Nair, Arjun, Patrini, Davide, Martinoni Hoogenboom, Emilie, Monk, Fleur, Holding, James W, Choudhary, Junaid, Bhakhri, Kunal, Scarci, Marco, Hayward, Martin, Panagiotopoulos, Nikolaos, Gorman, Pat, Khiroya, Reena, Stephens, Robert CM, Wong, Yien Ning Sophia, Bandula, Steve, Sharp, Abigail, Smith, Sean, Gower, Nicole, Dhanda, Harjot Kaur, Chan, Kitty, Pilotti, Camilla, Leslie, Rachel, Grapa, Anca, Zhang, Hanyun, AbdulJabbar, Khalid, Pan, Xiaoxi, Yuan, Yinyin, Chuter, David, MacKenzie, Mairead, Chee, Serena, Alzetani, Aiman, Scarlett, Lydia, Richards, Jennifer, Ingram, Papawadee, Austin, Silvia, De Sousa, Paulo, Jordan, Simon, Rice, Alexandra, Raubenheimer, Hilgardt, Bhayani, Harshil, Ambrose, Lyn, Devaraj, Anand, Chavan, Hema, Begum, Sofina, Buderi, Silviu, Kaniu, Daniel, Malima, Mpho, Booth, Sarah, Fernandes, Nadia, Shah, Pratibha, Proli, Chiara, Danson, Sarah, Robinson, Lily, Dick, Craig, Kirk, Alan, Asif, Mo, Bilancia, Rocco, Kostoulas, Nikos, and Thomas, Mathew

Subjects
Lung Neoplasms, Treatment Outcome, DNA Copy Number Variations, Mutagenesis, Carcinoma, Non-Small-Cell Lung, Mutation, Smoking, Humans, Adenocarcinoma of Lung, Neoplasm Recurrence, Local, Phylogeny
Abstract

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource. ispartof: NATURE vol:616 issue:7957 ispartof: location:England status: Published online

Published
2023

14. Evolutionary characterization of lung adenocarcinoma morphology in TRACERx

Author

Karasaki, Takahiro, Moore, David A, Veeriah, Selvaraju, Naceur-Lombardelli, Cristina, Toncheva, Antonia, Magno, Neil, Ward, Sophia, Al Bakir, Maise, Watkins, Thomas BK, Grigoriadis, Kristiana, Huebner, Ariana, Hill, Mark S, Frankell, Alexander M, Abbosh, Christopher, Puttick, Clare, Zhai, Haoran, Gimeno-Valiente, Francisco, Saghafinia, Sadegh, Kanu, Nnennaya, Dietzen, Michelle, Pich, Oriol, Lim, Emilia L, Martinez-Ruiz, Carlos, Black, James RM, Biswas, Dhruva, Campbell, Brittany B, Lee, Claudia, Colliver, Emma, Enfield, Katey SS, Hessey, Sonya, Hiley, Crispin T, Zaccaria, Simone, Litchfield, Kevin, Birkbak, Nicolai J, Cadieux, Elizabeth Larose, Demeulemeester, Jonas, Van Loo, Peter, Adusumilli, Prasad R, Tan, Kay See, Cheema, Waseem, Sanchez-Vega, Francisco, Jones, David R, Rekhtman, Natasha, Travis, William D, Hackshaw, Allan, Marafioti, Teresa, Salgado, Roberto, Le Quesne, John, Nicholson, Andrew G, McGranahan, Nicholas, Swanton, Charles, Jamal-Hanjani, Mariam, Lester, Jason F, Bajaj, Amrita, Nakas, Apostolos, Sodha-Ramdeen, Azmina, Ang, Keng, Tufail, Mohamad, Chowdhry, Mohammed Fiyaz, Scotland, Molly, Boyles, Rebecca, Rathinam, Sridhar, Wilson, Claire, Marrone, Domenic, Dulloo, Sean, Fennell, Dean A, Matharu, Gurdeep, Shaw, Jacqui A, Riley, Joan, Primrose, Lindsay, Boleti, Ekaterini, Cheyne, Heather, Khalil, Mohammed, Richardson, Shirley, Cruickshank, Tracey, Price, Gillian, Kerr, Keith M, Benafif, Sarah, Gilbert, Kayleigh, Naidu, Babu, Patel, Akshay J, Osman, Aya, Lacson, Christer, Langman, Gerald, Shackleford, Helen, Djearaman, Madava, Kadiri, Salma, Middleton, Gary, Leek, Angela, Hodgkinson, Jack Davies, Totten, Nicola, Montero, Angeles, Smith, Elaine, Fontaine, Eustace, Granato, Felice, Doran, Helen, Novasio, Juliette, Rammohan, Kendadai, Joseph, Leena, Bishop, Paul, Shah, Rajesh, Moss, Stuart, Joshi, Vijay, Crosbie, Philip, Gomes, Fabio, Brown, Kate, Carter, Mathew, Chaturvedi, Anshuman, Priest, Lynsey, Oliveira, Pedro, Lindsay, Colin R, Blackhall, Fiona H, Krebs, Matthew G, Summers, Yvonne, Clipson, Alexandra, Tugwood, Jonathan, Kerr, Alastair, Rothwell, Dominic G, Kilgour, Elaine, Dive, Caroline, Aerts, Hugo JWL, Schwarz, Roland F, Kaufmann, Tom L, Wilson, Gareth A, Rosenthal, Rachel, Szallasi, Zoltan, Kisistok, Judit, Sokac, Mateo, Diossy, Miklos, Bunkum, Abigail, Stewart, Aengus, Magness, Alastair, Rowan, Andrew, Karamani, Angeliki, Chain, Benny, Castignani, Carla, Bailey, Chris, Weeden, Clare E, Richard, Corentin, Pearce, David R, Karagianni, Despoina, Levi, Dina, Hoxha, Elena, Nye, Emma, Gronroos, Eva, Galvez-Cancino, Felip, Athanasopoulou, Foteini, Kassiotis, George, Stavrou, Georgia, Mastrokalos, Gerasimos, Lowe, Helen L, Matos, Ignacio Garcia, Goldman, Jacki, Reading, James L, Herrero, Javier, Rane, Jayant K, Nicod, Jerome, Lam, Jie Min, Hartley, John A, Peggs, Karl S, Selvaraju, Kayalvizhi, Thol, Kerstin, Ng, Kevin W, Chen, Kezhong, Dijkstra, Krijn, Thakkar, Krupa, Ensell, Leah, Shah, Mansi, Duran, Marcos Vasquez, Litovchenko, Maria, Sunderland, Mariana Werner, Leung, Michelle, Escudero, Mickael, Angelova, Mihaela, Tanic, Miljana, Sivakumar, Monica, Chervova, Olga, Lucas, Olivia, Al-Sawaf, Othman, Prymas, Paulina, Hobson, Philip, Pawlik, Piotr, Stone, Richard Kevin, Bentham, Robert, Hynds, Robert E, Vendramin, Roberto, Lopez, Saioa, Gamble, Samuel, Ung, Seng Kuong Anakin, Quezada, Sergio A, Vanloo, Sharon, Boeing, Stefan, Beck, Stephan, Bola, Supreet Kaur, Denner, Tamara, Mourikis, Thanos P, Spanswick, Victoria, Barbe, Vittorio, Lu, Wei-Ting, Hill, William, Liu, Wing Kin, Wu, Yin, Naito, Yutaka, Ramsden, Zoe, Veiga, Catarina, Royle, Gary, Collins-Fekete, Charles-Antoine, Fraioli, Francesco, Ashford, Paul, Clark, Tristan, Forster, Martin D, Lee, Siow Ming, Borg, Elaine, Falzon, Mary, Papadatos-Pastos, Dionysis, Wilson, James, Ahmad, Tanya, Procter, Alexander James, Ahmed, Asia, Taylor, Magali N, Nair, Arjun, Lawrence, David, Patrini, Davide, Navani, Neal, Thakrar, Ricky M, Janes, Sam M, Hoogenboom, Emilie Martinoni, Monk, Fleur, Holding, James W, Choudhary, Junaid, Bhakhri, Kunal, Scarci, Marco, Hayward, Martin, Panagiotopoulos, Nikolaos, Gorman, Pat, Khiroya, Reena, Stephens, Robert CM, Wong, Yien Ning Sophia, Bandula, Steve, Sharp, Abigail, Smith, Sean, Gower, Nicole, Dhanda, Harjot Kaur, Chan, Kitty, Pilotti, Camilla, Leslie, Rachel, Grapa, Anca, Zhang, Hanyun, AbdulJabbar, Khalid, Pan, Xiaoxi, Yuan, Yinyin, Chuter, David, MacKenzie, Mairead, Chee, Serena, Alzetani, Aiman, Cave, Judith, Scarlett, Lydia, Richards, Jennifer, Ingram, Papawadee, Austin, Silvia, Lim, Eric, De Sousa, Paulo, Jordan, Simon, Rice, Alexandra, Raubenheimer, Hilgardt, Bhayani, Harshil, Ambrose, Lyn, Devaraj, Anand, Chavan, Hema, Begum, Sofina, Buderi, Silviu, Kaniu, Daniel, Malima, Mpho, Booth, Sarah, Fernandes, Nadia, Shah, Pratibha, Proli, Chiara, Hewish, Madeleine, Danson, Sarah, Shackcloth, Michael J, Robinson, Lily, Russell, Peter, Blyth, Kevin G, Dick, Craig, Kirk, Alan, Asif, Mo, Bilancia, Rocco, Kostoulas, Nikos, and Thomas, Mathew

Subjects
TRACERx Consortium
Abstract

Lung adenocarcinomas (LUADs) display a broad histological spectrum from low-grade lepidic tumors through to mid-grade acinar and papillary and high-grade solid, cribriform and micropapillary tumors. How morphology reflects tumor evolution and disease progression is poorly understood. Whole-exome sequencing data generated from 805 primary tumor regions and 121 paired metastatic samples across 248 LUADs from the TRACERx 421 cohort, together with RNA-sequencing data from 463 primary tumor regions, were integrated with detailed whole-tumor and regional histopathological analysis. Tumors with predominantly high-grade patterns showed increased chromosomal complexity, with higher burden of loss of heterozygosity and subclonal somatic copy number alterations. Individual regions in predominantly high-grade pattern tumors exhibited higher proliferation and lower clonal diversity, potentially reflecting large recent subclonal expansions. Co-occurrence of truncal loss of chromosomes 3p and 3q was enriched in predominantly low-/mid-grade tumors, while purely undifferentiated solid-pattern tumors had a higher frequency of truncal arm or focal 3q gains and SMARCA4 gene alterations compared with mixed-pattern tumors with a solid component, suggesting distinct evolutionary trajectories. Clonal evolution analysis revealed that tumors tend to evolve toward higher-grade patterns. The presence of micropapillary pattern and 'tumor spread through air spaces' were associated with intrathoracic recurrence, in contrast to the presence of solid/cribriform patterns, necrosis and preoperative circulating tumor DNA detection, which were associated with extra-thoracic recurrence. These data provide insights into the relationship between LUAD morphology, the underlying evolutionary genomic landscape, and clinical and anatomical relapse risk. ispartof: NATURE MEDICINE vol:29 issue:4 ispartof: location:United States status: Published online

Published
2023

23. Experimental comparison of photon versus particle computed tomography to predict tissue relative stopping powers.

Author

Bär, Esther, Volz, Lennart, Collins‐Fekete, Charles‐Antoine, Brons, Stephan, Runz, Armin, Schulte, Reinhard Wilhelm, and Seco, Joao

Subjects
COMPUTED tomography, DUAL energy CT (Tomography), COMPACT bone, BONE marrow, PHOTONS, PROTON beams, TISSUES
Abstract

Purpose: Measurements comparing relative stopping power (RSP) accuracy of state‐of‐the‐art systems representing single‐energy and dual‐energy computed tomography (SECT/DECT) with proton CT (pCT) and helium CT (HeCT) in biological tissue samples. Methods: We used 16 porcine and bovine samples of various tissue types and water, covering an RSP range from 0.90±0.06 to 1.78 ±0.05. Samples were packed and sealed into 3D‐printed cylinders (d=2 cm, h=5 cm) and inserted into an in‐house designed cylindrical polymethyl methacrylate (PMMA) phantom (d=10 cm, h=10 cm). We scanned the phantom in a commercial SECT and DECT (120 kV; 100 and 140 kV/Sn (tin‐filtered)); and acquired pCT and HeCT (E∼200 MeV/u, 2∘ steps, ∼6.2×106 (p)/∼2.3×106 (He) particles/projection) with a particle imaging prototype. RSP maps were calculated from SECT/DECT using stoichiometric methods and from pCT/HeCT using the DROP‐TVS algorithm. We estimated the average RSP of each tissue per modality in cylindrical volumes of interest and compared it to ground truth RSP taken from peak‐detection measurements. Results: Throughout all samples, we observe the following root‐mean‐squared RSP prediction errors ± combined uncertainty from reference measurement and imaging: SECT 3.10±2.88%, DECT 0.75±2.80%, pCT 1.19± 2.81%, and HeCT 0.78±2.81%. The largest mean errors ± combined uncertainty per modality are SECT 8.22 ±2.79% in cortical bone, DECT 1.74±2.00% in back fat, pCT 1.80 ±4.27% in bone marrow, and HeCT 1.37±4.25% in bone marrow. Ring artifacts were observed in both pCT and HeCT reconstructions, imposing a systematic shift to predicted RSPs. Conclusion: Comparing state‐of‐the‐art SECT/DECT technology and a pCT/HeCT prototype, DECT provided the most accurate RSP prediction, closely followed by particle imaging. The novel modalities pCT and HeCT have the potential to further improve on RSP accuracies with work focusing on the origin and correction of ring artifacts. Future work will study accuracy of proton treatment plans using RSP maps from investigated imaging modalities. [ABSTRACT FROM AUTHOR]

Published
2022
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29. Improving single-event particle imaging by u0394E-E filtering

Author

Collins-Fekete, Charles-Antoine

Abstract

In single-event particle imaging, removing nuclear interaction events is crucial for accurate relative stopping power (RSP) reconstruction. Additionally, for imaging with ions, secondary fragments have to be separated from the primary histories. We investigate the use of a u0394E-E filter in helium CT (HeCT) and proton CT (pCT) with the preclinical prototype pCT scanner developed by the US pCT collaboration.Experimental HeCT scans were obtained with the scanner at the Heidelberg Ion-Beam Therapy Center. Simulated HeCT and pCT scans were acquired based on the prototype using the TOPAS Monte Carlo toolkit. To filter out secondary fragments and nuclear interactions that occurred within the detector, the scanner 5-stage energy/range detector was adapted as u0394E-E telescope. The u0394E-E filter was compared to the data filters currently used as standard with the prototype.Accurate HeCT was possible only when using the developed filter, as large systematic fluctuations were present in the reconstructions otherwise (Fig. 1). With the filter, both simulated and experimental HeCT yielded a mean RSP accuracy better than 0.5% (Fig. 2). For pCT, the filter removed similar, yet less pronounced systematic uncertainties and the achieved accuracy was close tosimulations for that nuclear interactions were disabled.In conclusion, u0394E-E filtering proved to be effective in improving the visual quality and RSP accuracy of both HeCT and pCT. For the first time, accurate experimental single-event HeCT images could be presented.

Published
2017

31. Abstract ID: 180 On the use of Monte Carlo techniques to improve particle imaging noise filtering and spatial resolution

Author

Collins Fekete Charles-Antoine, Beaulieu Luc, and Seco Joao

Subjects
Physics, Proton, business.industry, Detector, Monte Carlo method, Biophysics, General Physics and Astronomy, General Medicine, Noise (electronics), Imaging phantom, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, 0302 clinical medicine, Optics, 030220 oncology & carcinogenesis, Electronic engineering, Stopping power (particle radiation), Radiology, Nuclear Medicine and imaging, business, Particle filter, Image resolution
Abstract

Particle imaging has shown growing interest in the recent literature as it allows direct measurement of the tissue relative stopping power (RSP) within a patient, using either the radiographic or tomographic images [1] . However, its accuracy is limited by the multiple Coulomb scattering (MCS) suffered by the particles through the phantom and by the secondary particles noise measured on the detector that creates artefact in the reconstructed images. Monte Carlo (MC) techniques help investigate the spatial resolution gain obtained by using 1) different path estimate or 2) different ions to reduce the MCS effect on the final images [2] , [3] , [4] . Furthermore, secondary particles filtering techniques are paramount to achieve high RSP accuracy but may reduce contrast and spatial resolution along the process. The effect of the applied filters can be directly studied on the noise power spectrum (NPS) of perfect images acquired through MC simulations. Initial investigation demonstrates that He ions is the optimal choice between light ions (i.e. 1H to 6C) to achieve the highest path accuracy [2] decreasing the root-mean square uncertainty between the MC reference and the path estimate from 0.5 [mm] for protons to 0.18 [mm] for He. This has been shown to leads to higher spatial resolution radiographic images. On the other hands, the NPS spectrum [mm2] increases due to secondary particles on unfiltered He image is 300 times higher than that of proton, stressing the need for smart secondary particle filters.

Published
2017

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