Article
Multidisciplinary Sciences
Marco Palombo, Vanya Valindria, Saurabh Singh, Eleni Chiou, Francesco Giganti, Hayley Pye, Hayley C. Whitaker, David Atkinson, Shonit Punwani, Daniel C. Alexander, Eleftheria Panagiotaki
Summary: This study introduces a biophysical model called rVERDICT for prostate diffusion and relaxation MRI, which provides unbiased estimates of T1/T2 and microstructural parameters by accounting for compartment-specific relaxation effects. The feasibility of rVERDICT estimates for Gleason grade discrimination was tested and found to outperform classic VERDICT and ADC from mp-MRI. The relaxation estimates of rVERDICT were compared against independent multi-TE acquisitions, showing no significant difference, and exhibited high repeatability in rescanning patients. The rVERDICT model allows for accurate, fast, and repeatable estimation of diffusion and relaxation properties of PCa, enabling discrimination of Gleason grades 3 + 3, 3 + 4, and ≥ 4 + 3.
SCIENTIFIC REPORTS
(2023)
Article
Oncology
Matteo Figini, Antonella Castellano, Michele Bailo, Marcella Callea, Marcello Cadioli, Samira Bouyagoub, Marco Palombo, Valentina Pieri, Pietro Mortini, Andrea Falini, Daniel C. Alexander, Mara Cercignani, Eleftheria Panagiotaki
Summary: The aim of this study was to expand the VERDICT-MRI framework to model brain tumors and characterize cellular and vascular features. Diffusion MRI data were collected from 21 patients with different types of brain tumors. Different diffusion models were fitted and compared based on their ability to characterize key tumor components. The best-performing model showed agreement with histology and had potential for differentiating tumor types and sub-regions.
Article
Neurosciences
Ileana O. Jelescu, Alexandre de Skowronski, Francoise Geffroy, Marco Palombo, Dmitry S. Novikov
Summary: Research focuses on diffusion MRI in gray matter, proposing Neurite Exchange Imaging (NEXI) as a more suitable model, with in vivo experiments showing the essential role of water exchange in interpreting diffusion MRI measurements in gray matter.
Article
Multidisciplinary Sciences
Alexander Wong, Hayden Gunraj, Vignesh Sivan, Masoom A. Haider
Summary: Prostate cancer is the second most common cancer in men worldwide and early screening is crucial. Correlated diffusion imaging (CDI) shows promise as a screening tool. In the largest study of its kind, hyperintensity in CDIs is found to be a strong indicator of PCa presence and performs well in cancerous tissue delineation.
SCIENTIFIC REPORTS
(2022)
Review
Biochemistry & Molecular Biology
Matteo Ferro, Ottavio de Cobelli, Mihai Dorin Vartolomei, Giuseppe Lucarelli, Felice Crocetto, Biagio Barone, Alessandro Sciarra, Francesco Del Giudice, Matteo Muto, Martina Maggi, Giuseppe Carrieri, Gian Maria Busetto, Ugo Falagario, Daniela Terracciano, Luigi Cormio, Gennaro Musi, Octavian Sabin Tataru
Summary: Radiomics and genomics play crucial roles in prostate cancer research, enhancing clinical value through mathematical analysis and machine learning. Validation of recent findings in large, randomized cohorts can establish the role of radiogenomics in the future.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Alexis Reymbaut, Alex Valcourt Caron, Guillaume Gilbert, Filip Szczepankiewicz, Markus Nilsson, Simon K. Warfield, Maxime Descoteaux, Benoit Scherrer
Summary: Diffusion tensor imaging provides increased sensitivity to microstructural tissue changes compared to conventional anatomical imaging, but presents limited specificity. To address this issue, the DIAMOND model subdivides voxel content into diffusion compartments and estimates compartmental non-central matrix-variate Gamma distributions of diffusion tensors. Incorporating tensor-valued diffusion encoding, the Magic DIAMOND model demonstrates improved accuracy in estimating brain microstructural features, particularly in regions of fiber crossing.
MEDICAL IMAGE ANALYSIS
(2021)
Review
Medicine, General & Internal
Heinz-Peter Schlemmer, Bernd Joachim Krause, Viktoria Schuetz, David Bonekamp, Sarah Marie Schwarzenboeck, Markus Hohenfellner
Summary: Currently, multiparametric MRI and MR/TRUS fusion biopsy significantly improve the detection of clinically significant prostate cancer, while PSMA hybrid imaging aids in the staging of high-risk patients and detection of recurrences.
DEUTSCHES ARZTEBLATT INTERNATIONAL
(2021)
Article
Medicine, General & Internal
Snigdha Sen, Vanya Valindria, Paddy J. Slator, Hayley Pye, Alistair Grey, Alex Freeman, Caroline Moore, Hayley Whitaker, Shonit Punwani, Saurabh Singh, Eleftheria Panagiotaki
Summary: Quantitative diffusion MRI can effectively differentiate between false positive, true positive, and normal tissue, reducing unnecessary biopsies caused by false positive prostate lesions.
Review
Radiology, Nuclear Medicine & Medical Imaging
Jung Jae Park, Chan Kyo Kim
Summary: This article reviews recent literature on the diagnostic value of pre-biopsy prostate MRI as a triage tool and discusses unresolved issues regarding the paradigm shift in the diagnosis of prostate cancer.
KOREAN JOURNAL OF RADIOLOGY
(2022)
Review
Oncology
Mostafa Alabousi, Sangeet Ghai
Summary: Prostate cancer is a common malignancy in men, and radical whole-gland therapies often lead to significant morbidity. Focal therapies, guided by magnetic resonance imaging (MRI), selectively treat the diseased part and minimize associated morbidity. Recent trials of MRI-guided high-intensity focused ultrasound techniques have shown promising outcomes in the treatment of localized prostate cancer. Focal ultrasound-guided HIFU and TULSA ablation have demonstrated better oncologic results and potential for additional costs associated with MRI guidance.
FRONTIERS IN ONCOLOGY
(2023)
Review
Oncology
Adam Retter, Fiona Gong, Tom Syer, Saurabh Singh, Sola Adeleke, Shonit Punwani
Summary: Imaging plays a crucial role in cancer management, with new techniques like diffusion-weighted imaging and PET being developed to overcome the limitations of conventional methods. Machine learning shows promising potential in cancer diagnosis and treatment, alongside advancements in MRI and new PET tracers.
MOLECULAR ONCOLOGY
(2021)
Article
Urology & Nephrology
Andrew J. Vickers
Summary: This study aimed to assess the impact of MRI-targeted biopsy on mortality risk for high-grade prostate cancers identified in men with negative systematic biopsy results. The results showed that a large number of men need to be diagnosed and treated for prostate cancer in order to prevent just one prostate cancer death when targeting MRI-visible tumors during biopsy.
Article
Radiology, Nuclear Medicine & Medical Imaging
Christine H. Feng, Christopher C. Conlin, Kanha Batra, Ana E. Rodriguez-Soto, Roshan Karunamuni, Aaron Simon, Joshua Kuperman, Rebecca Rakow-Penner, Michael E. Hahn, Anders M. Dale, Tyler M. Seibert
Summary: The study evaluated the slowest diffusion compartment of a four-compartment spectrum imaging model (RSI4-C-1) as a quantitative voxel-level classifier of PCa, which outperformed conventional ADC and showed potential for clinical applications.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Farshad Moradi, Andrea Farolfi, Stefano Fanti, Andrei Iagaru
Summary: Molecular imaging is rapidly evolving in the initial evaluation of prostate cancer, biochemical recurrence, and metastatic disease, offering superior diagnostic performance compared to anatomic imaging, yet facing challenges due to variable tumor biology and metabolic alterations.
EUROPEAN JOURNAL OF RADIOLOGY
(2021)
Article
Engineering, Biomedical
Xueyan Zhou, Xiaobing Fan, Aritrick Chatterjee, Ambereen Yousuf, Tatjana Antic, Aytekin Oto, Gregory S. Karczmar
Summary: The spatial two-tissue compartment model (2TCM) was used to analyze prostate dynamic contrast enhanced (DCE) MRI data. The 2TCM showed higher accuracy in fitting the data compared to the standard Tofts model and provided new information in diagnosing prostate cancer. The fast Ktrans 1 parameter from the 2TCM had the highest area under the curve (AUC) in receiver operating characteristic (ROC) analysis.
PHYSICAL AND ENGINEERING SCIENCES IN MEDICINE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Rafat Chowdhury, Christoph A. Mueller, Lorna Smith, Fiona Gong, Marianthi-Vasiliki Papoutsaki, Harriet Rogers, Tom Syer, Saurabh Singh, Giorgio Brembilla, Adam Retter, Max Bullock, Lucy Caselton, Manju Mathew, Eoin Dineen, Thomas Parry, Juergen Hennig, Dominik von Elverfeldt, Andreas B. Schmidt, Jan-Bernd Hovener, Mark Emberton, David Atkinson, Alan Bainbridge, David G. Gadian, Shonit Punwani
Summary: This study aimed to validate a signal simulation framework for sequence parameter optimization and demonstrate the feasibility of using ME-bSSFP for HP C-13-MRI in patients. The results showed that ME-bSSFP allows for metabolic imaging of the prostate and can differentiate between aggressive prostate cancer and healthy tissue.
JOURNAL OF MAGNETIC RESONANCE IMAGING
(2023)
Letter
Urology & Nephrology
Edward J. J. Bass, Hashim U. U. Ahmed
Editorial Material
Primary Health Care
Samuel W. D. Merriel, Andrew Seggie, Hashim Ahmed
BRITISH JOURNAL OF GENERAL PRACTICE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Ryan Fullarton, Lennart Volz, Nikolaos Dikaios, Reinhard Schulte, Gary Royle, Philip M. Evans, Joao Seco, Charles-Antoine Collins-Fekete
Summary: This study proposes a particle imaging filter, called the Prior Filter, which uses prior information and electromagnetic interaction principles to identify particles that have undergone nuclear interactions. The filter effectively reduces image noise and maintains good performance even with a dose reduction.
Article
Multidisciplinary Sciences
Gavrielle R. Untracht, Nikolaos Dikaios, Abdullah K. Durrani, Mariam Bapir, Marinko V. Sarunic, David D. Sampson, Christian Heiss, Danuta M. Sampson
Summary: This pilot study evaluates OCTA-derived microvascular parameters in healthy individuals and patients with diabetes. It establishes reference values for different regions of the body and identifies potential biomarkers for diabetes.
SCIENTIFIC REPORTS
(2023)
Article
Mathematics
Nicholas E. E. Protonotarios, George A. A. Kastis, Andreas D. D. Fotopoulos, Andreas G. G. Tzakos, Dimitrios Vlachos, Nikolaos Dikaios
Summary: This study focuses on improving motion correction algorithms in PET by using a motion-compensated image reconstruction (MCIR) algorithm based on a parabolic surrogate likelihood function. The parabolic surrogate algorithm converges faster than the expectation maximization (EM) algorithm, making it particularly useful in computationally demanding PET motion correction.
Letter
Urology & Nephrology
Alexander Light, Xiaomeng Li, Marjorie Otieno, Hashim U. Ahmed, Taimur T. Shah
Article
Multidisciplinary Sciences
Oliver Brunckhorst, Jaroslaw Liszka, Callum James, Jack B. Fanshawe, Mohamed Hammadeh, Robert Thomas, Shahid Khan, Matin Sheriff, Hashim U. Ahmed, Mieke Van Hemelrijck, Gordon Muir, Robert Stewart, Prokar Dasgupta, Kamran Ahmed
Summary: This study aims to explore the potential treatment, patient, and oncological factors associated with mental wellbeing outcomes in newly diagnosed prostate cancer patients. It will recruit 300 participants undergoing different treatment options for 12-month follow-up and collect questionnaire-based data for analysis. The results will provide clinical value in guiding future prognosis research and identifying individuals in need of additional monitoring or support.
Article
Multidisciplinary Sciences
Bojidar Rangelov, Alexandra Young, Watjana Lilaonitkul, Shahab Aslani, Paul Taylor, Eyjolfur Guomundsson, Qianye Yang, Yipeng Hu, John R. Hurst, David J. Hawkes, Joseph Jacob
Summary: The COVID-19 pandemic has presented a significant challenge to healthcare systems worldwide. This study developed an unsupervised data-driven model called SuStaIn, which can be used to predict short-term infectious diseases like COVID-19 based on commonly recorded clinical measures. The model identified three COVID-19 subtypes and introduced disease severity stages, both of which were predictive of in-hospital mortality or escalation of treatment. This model can be adapted for future outbreaks of COVID-19 or other infectious diseases.
SCIENTIFIC REPORTS
(2023)
Article
Psychiatry
Siegfried K. Wagner, Mario Cortina-Borja, Steven M. Silverstein, Yukun Zhou, David Romero-Bascones, Robbert R. Struyven, Emanuele Trucco, Muthu R. K. Mookiah, Tom MacGillivray, Stephen Hogg, Timing Liu, Dominic J. Williamson, Nikolas Pontikos, Praveen J. Patel, Konstantinos Balaskas, Daniel C. Alexander, Kelsey V. Stuart, Anthony P. Khawaja, Alastair K. Denniston, Jugnoo S. Rahi, Axel Petzold, Pearse A. Keane
Summary: This study found measurable differences in neural and vascular integrity of the retina in patients with schizophrenia, which were mostly secondary to the higher prevalence of diabetes and hypertension in these patients.
Article
Radiology, Nuclear Medicine & Medical Imaging
Saurabh Singh, Francesco Giganti, Louise Dickinson, Harriet Rogers, Baris Kanber, Joey Clemente, Hayley Pye, Susan Heavey, Urszula Stopka-Farooqui, Edward W. Johnston, Caroline M. Moore, Alex Freeman, Hayley C. Whitaker, Daniel C. Alexander, Eleftheria Panagiotaki, Shonit Punwani
Summary: This study aimed to assess the image quality of ADC and FIC maps derived from conventional diffusion-weighted MRI and VERDICT MRI in patients from the INNOVATE trial. The results showed that the image quality was comparable between FIC and ADC, but the image quality of ADC was higher than FIC when assessed using the Likert score.
EUROPEAN JOURNAL OF RADIOLOGY
(2023)
Article
Developmental Biology
Nada Mufti, Joanna Chappell, Patrick O'Brien, George Attilakos, Hassna Irzan, Magda Sokolska, Priya Narayanan, Trevor Gaunt, Paul D. Humphries, Premal Patel, Elspeth Whitby, Eric Jauniaux, J. Ciaran Hutchinson, Neil J. Sebire, David Atkinson, Giles Kendall, Sebastien Ourselin, Tom Vercauteren, Anna L. David, Andrew Melbourne
Summary: The study investigates the use of super-resolution reconstruction (SRR) MRI to improve placental assessment and predict adverse maternal outcomes. The results show that SRR imaging and paired imaging can enhance the detection of pathological MRI markers, aiding in surgical planning.
Article
Multidisciplinary Sciences
A. S. Fokas, N. Dikaios, Y. C. Yortsos
Summary: The susceptible-exposed-infectious-recovered (SEIR) models with constant coefficients are the most widely used mathematical models in epidemiology. However, epidemiological data from Europe show that for the first wave of the COVID-19 epidemic, these models predict an algebraic equilibrium instead of exponential as expected. By allowing parameters reflecting behavioral aspects of the SEIR model to vary nonlinearly with the extent of the epidemic, a new model with algebraic behavior is constructed. This study also demonstrates the optimality of the algebraic forecasting model using deep learning.
ROYAL SOCIETY OPEN SCIENCE
(2023)
Article
Medicine, General & Internal
Muhammad Usman Saeed, Nikolaos Dikaios, Aqsa Dastgir, Ghulam Ali, Muhammad Hamid, Fahima Hajjej
Summary: This research introduces a novel deep learning model for spine segmentation and vertebrae recognition using CT images. The model consists of a modified U-Net for spine segmentation and a 3D deep learning model for vertebrae recognition. Experimental results demonstrate that the proposed model achieves more accurate results than the state-of-the-art methods in spine segmentation and vertebrae recognition.
Meeting Abstract
Ophthalmology
Dominic Williamson, Robbert Struyven, Siegfried Wagner, David Romero-Bascones, Yukun Zhou, Mateo Gende Lozano, Timing Liu, Mario Cortina Borja, Jugnoo Rahi, Axel Petzold, Yue Wu, Cecilia S. Lee, Aaron Y. Lee, Alastair K. Denniston, Daniel Alexander, Pearse Keane
INVESTIGATIVE OPHTHALMOLOGY & VISUAL SCIENCE
(2023)