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669 results on '"D'Arco, Felice"'

2. Evaluation of epilepsy lesion visualisation enhancement in low-field MRI using image quality transfer: a preliminary investigation of clinical potential for applications in developing countries

Author

Figini, Matteo, Lin, Hongxiang, D’Arco, Felice, Ogbole, Godwin, Rossi-Espagnet, Maria Camilla, Oyinloye, Olalekan Ibukun, Yaria, Joseph, Nzeh, Donald Amasike, Atalabi, Mojisola Omolola, Carmichael, David W., Cross, Judith Helen, Lagunju, Ikeoluwa, Fernandez-Reyes, Delmiro, and Alexander, Daniel C.

Published
2024
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3. BCL11A intellectual developmental disorder: defining the clinical spectrum and genotype-phenotype correlations

Author

Peron, Angela, D’Arco, Felice, Aldinger, Kimberly A., Smith-Hicks, Constance, Zweier, Christiane, Gradek, Gyri A., Bradbury, Kimberley, Accogli, Andrea, Andersen, Erica F., Au, Ping Yee Billie, Battini, Roberta, Beleford, Daniah, Bird, Lynne M., Bouman, Arjan, Bruel, Ange-Line, Busk, Øyvind Løvold, Campeau, Philippe M., Capra, Valeria, Carlston, Colleen, Carmichael, Jenny, Chassevent, Anna, Clayton-Smith, Jill, Bamshad, Michael J., Earl, Dawn L., Faivre, Laurence, Philippe, Christophe, Ferreira, Patrick, Graul-Neumann, Luitgard, Green, Mary J., Haffner, Darrah, Haldipur, Parthiv, Hanna, Suhair, Houge, Gunnar, Jones, Wendy D., Kraus, Cornelia, Kristiansen, Birgit Elisabeth, Lespinasse, James, Low, Karen J., Lynch, Sally Ann, Maia, Sofia, Mao, Rong, Kalinauskiene, Ruta, Melver, Catherine, McDonald, Kimberly, Montgomery, Tara, Morleo, Manuela, Motter, Constance, Openshaw, Amanda S., Palumbos, Janice Cox, Parikh, Aditi Shah, Perilla-Young, Yezmin, Powell, Cynthia M., Person, Richard, Desai, Megha, Piard, Juliette, Pfundt, Rolph, Scala, Marcello, Serey-Gaut, Margaux, Shears, Deborah, Slavotinek, Anne, Suri, Mohnish, Turner, Claire, Tvrdik, Tatiana, Weiss, Karin, Wentzensen, Ingrid M., Zollino, Marcella, Hsieh, Tzung-Chien, de Vries, Bert B. A., Guillemot, Francois, Dobyns, William B., Viskochil, David, and Dias, Cristina

Published
2024
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4. Integrating standard epilepsy protocol, ASL-perfusion, MP2RAGE/EDGE and the MELD-FCD classifier in the detection of subtle epileptogenic lesions: a 3 Tesla MRI pilot study

Author

Pastore, Luigi Vincenzo, Sudhakar, Sniya Valsa, Mankad, Kshitij, De Vita, Enrico, Biswas, Asthik, Tisdall, Martin M., Chari, Aswin, Figini, Matteo, Tahir, M. Zubair, Adler, Sophie, Moeller, Friederike, Cross, J. Helen, Pujar, Suresh, Wagstyl, Konrad, Ripart, Mathilde, Löbel, Ulrike, Cirillo, Luigi, and D’Arco, Felice

Published
2024
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8. Low-field magnetic resonance image enhancement via stochastic image quality transfer

Author

Lin, Hongxiang, Figini, Matteo, D'Arco, Felice, Ogbole, Godwin, Tanno, Ryutaro, Blumberg, Stefano B., Ronan, Lisa, Brown, Biobele J., Carmichael, David W., Lagunju, Ikeoluwa, Cross, Judith Helen, Fernandez-Reyes, Delmiro, and Alexander, Daniel C.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Low-field (<1T) magnetic resonance imaging (MRI) scanners remain in widespread use in low- and middle-income countries (LMICs) and are commonly used for some applications in higher income countries e.g. for small child patients with obesity, claustrophobia, implants, or tattoos. However, low-field MR images commonly have lower resolution and poorer contrast than images from high field (1.5T, 3T, and above). Here, we present Image Quality Transfer (IQT) to enhance low-field structural MRI by estimating from a low-field image the image we would have obtained from the same subject at high field. Our approach uses (i) a stochastic low-field image simulator as the forward model to capture uncertainty and variation in the contrast of low-field images corresponding to a particular high-field image, and (ii) an anisotropic U-Net variant specifically designed for the IQT inverse problem. We evaluate the proposed algorithm both in simulation and using multi-contrast (T1-weighted, T2-weighted, and fluid attenuated inversion recovery (FLAIR)) clinical low-field MRI data from an LMIC hospital. We show the efficacy of IQT in improving contrast and resolution of low-field MR images. We demonstrate that IQT-enhanced images have potential for enhancing visualisation of anatomical structures and pathological lesions of clinical relevance from the perspective of radiologists. IQT is proved to have capability of boosting the diagnostic value of low-field MRI, especially in low-resource settings., Comment: Accepted in Medical Image Analysis

Published
2023
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11. Head and Neck Infections

Author

D’Arco, Felice, Nash, Robert, Ugga, Lorenzo, Medina, L. Santiago, Series Editor, Applegate, Kimberly E., Series Editor, Blackmore, C. Craig, Series Editor, Otero, Hansel J., editor, and Kaplan, Summer L., editor

Published
2024
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15. Image Quality Transfer Enhances Contrast and Resolution of Low-Field Brain MRI in African Paediatric Epilepsy Patients

Author

Figini, Matteo, Lin, Hongxiang, Ogbole, Godwin, Arco, Felice D, Blumberg, Stefano B., Carmichael, David W., Tanno, Ryutaro, Kaden, Enrico, Brown, Biobele J., Lagunju, Ikeoluwa, Cross, Helen J., Fernandez-Reyes, Delmiro, and Alexander, Daniel C.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Physics - Medical Physics
Abstract

1.5T or 3T scanners are the current standard for clinical MRI, but low-field (<1T) scanners are still common in many lower- and middle-income countries for reasons of cost and robustness to power failures. Compared to modern high-field scanners, low-field scanners provide images with lower signal-to-noise ratio at equivalent resolution, leaving practitioners to compensate by using large slice thickness and incomplete spatial coverage. Furthermore, the contrast between different types of brain tissue may be substantially reduced even at equal signal-to-noise ratio, which limits diagnostic value. Recently the paradigm of Image Quality Transfer has been applied to enhance 0.36T structural images aiming to approximate the resolution, spatial coverage, and contrast of typical 1.5T or 3T images. A variant of the neural network U-Net was trained using low-field images simulated from the publicly available 3T Human Connectome Project dataset. Here we present qualitative results from real and simulated clinical low-field brain images showing the potential value of IQT to enhance the clinical utility of readily accessible low-field MRIs in the management of epilepsy., Comment: 6 pages, 3 figures, accepted at ICLR 2020 workshop on Artificial Intelligence for Affordable Healthcare

Published
2020

21. Deep Learning for Low-Field to High-Field MR: Image Quality Transfer with Probabilistic Decimation Simulator

Author

Lin, Hongxiang, Figini, Matteo, Tanno, Ryutaro, Blumberg, Stefano B., Kaden, Enrico, Ogbole, Godwin, Brown, Biobele J., D'Arco, Felice, Carmichael, David W., Lagunju, Ikeoluwa, Cross, Helen J., Fernandez-Reyes, Delmiro, and Alexander, Daniel C.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

MR images scanned at low magnetic field ($<1$T) have lower resolution in the slice direction and lower contrast, due to a relatively small signal-to-noise ratio (SNR) than those from high field (typically 1.5T and 3T). We adapt the recent idea of Image Quality Transfer (IQT) to enhance very low-field structural images aiming to estimate the resolution, spatial coverage, and contrast of high-field images. Analogous to many learning-based image enhancement techniques, IQT generates training data from high-field scans alone by simulating low-field images through a pre-defined decimation model. However, the ground truth decimation model is not well-known in practice, and lack of its specification can bias the trained model, aggravating performance on the real low-field scans. In this paper we propose a probabilistic decimation simulator to improve robustness of model training. It is used to generate and augment various low-field images whose parameters are random variables and sampled from an empirical distribution related to tissue-specific SNR on a 0.36T scanner. The probabilistic decimation simulator is model-agnostic, that is, it can be used with any super-resolution networks. Furthermore we propose a variant of U-Net architecture to improve its learning performance. We show promising qualitative results from clinical low-field images confirming the strong efficacy of IQT in an important new application area: epilepsy diagnosis in sub-Saharan Africa where only low-field scanners are normally available.

Published
2019

29. Neuroradiologic, Clinical, and Genetic Characterization of Cerebellar Heterotopia: A Pediatric Multicentric Study.

Author

Pasca, Ludovica, Arrigoni, Filippo, Romaniello, Romina, Severino, Maria Savina, Politano, Davide, D'Abrusco, Fulvio, Garau, Jessica, De Giorgis, Valentina, Carpani, Adriana, Signorini, Sabrina, Orcesi, Simona, D'Arco, Felice, Alfei, Enrico, Cattaneo, Elisa, Rognone, Elisa, Uccella, Sara, Divizia, Maria Teresa, Infantino, Paolo, Valente, Enza Maria, and Borgatti, Renato

Published
2025
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30. Natural history of spinal cord compression stage AFMS3 in infants with achondroplasia: retrospective cohort study.

Author

Shang-Mei Cheung, Moira, Cocca, Alessandra, Harvey, Charlotte H., Brett, Connor Stephen S., Offiah, Amaka C., Borg, Stephanie, Jenko, Nathan, D'Arco, Felice, and Thompson, Dominic

Subjects
FIBROBLAST growth factor receptors, SUDDEN infant death syndrome, FORAMEN magnum, CEREBROSPINAL fluid, SOMATOSENSORY evoked potentials, INTRAOPERATIVE monitoring, NEUROLOGIC examination, CAUSE of death statistics
Published
2024
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31. Etiology of Childhood Profound Sensorineural Hearing Loss: The Role of Hearing Loss Gene Panel Testing.

Author

Rajput, Kaukab, Akhtar, Umar, Pagarkar, Waheeda, Rajput, Sarah, Walder, Claire, D'Arco, Felice, Cochrane, Lesley, Nash, Robert, Bitner‐Glindzicz, Maria, and Omar, Rohani

Abstract

Objective: Establishing the cause of hearing loss (HL) is important and rewarding, though not without its challenges. While our ability to identify the etiology for HL has improved with advances in scientific knowledge, a significant proportion of cases remain of unknown etiology. Recent protocol changes within the NHS Genomic Medicine Service support the utilization of the HL gene panel test, rather than individual gene tests. In light of these changes, determining the yield of these more extensive panel tests is important in informing future practice. Study Design: Retrospective study. Setting: The Cochlear Implant (CI) Department at Great Ormond Street Hospital (GOSH). Methods: Four hundred seventy‐six children with profound HL were identified from a database of referrals to the GOSH CI Department. Data on etiology of HL including genetic diagnosis was collected from hospital notes on an electronic patient records system and hospital genetics database. Results: We identified a positive result in 163/476 (34%) cases through the gene panel test, representing an additional 19% yield to current level 1 investigations. Genetic HL, including both syndromic (including those not covered by the HL gene panel) and nonsyndromic (209/476, 44%) was the most common etiology in our cohort. Perinatal, intrauterine, ototoxicity, meningitis, and encephalitis categories altogether comprised 97/476 (20%) cases. Conclusion: Gene panel testing provides significant additional yield over current level 1 investigations which include GJB2 testing only. This has far‐reaching implications for how we optimize investigations into HL in children and counsel families, and for future early interventions. [ABSTRACT FROM AUTHOR]

Published
2024
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37. Constitutional mismatch repair deficiency (CMMRD) presenting with high-grade glioma, multiple developmental venous anomalies and malformations of cortical development—a multidisciplinary/multicentre approach and neuroimaging clues to clinching the diagnosis

Author

Chhabda, Sahil, Sudhakar, Sniya, Mankad, Kshitij, Jorgensen, Mette, Carceller, Fernando, Jacques, Thomas S., Merve, Ashirwad, Aizpurua, Miren, Chalker, Jane, Garimberti, Elisa, and D’Arco, Felice

Published
2021
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39. Sotos Syndrome: Deep Neuroimaging Phenotyping Reveals a High Prevalence of Malformations of Cortical Development.

Author

Neeman, Bar, Sudhakar, Sniya, Biswas, Asthik, Rosenblum, Jessica, Sidpra, Jai, D'Arco, Felice, Löbel, Ulrike, Gómez-Chiari, Marta, Serrano, Mercedes, Bolasell, Mercè, Reddy, Kartik, Ben-Sira, Liat, Zakzouk, Reem, Al-Hashem, Amal, Mirsky, David M., Patel, Rajan, Radhakrishnan, Rupa, Shekdar, Karuna, Whitehead, Matthew T., and Mankad, Kshitij

Published
2024
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41. Incomplete partition type II in its various manifestations: isolated, in association with EVA, syndromic, and beyond; a multicentre international study.

Author

D'Arco, Felice, Kandemirli, Sedat G., Dahmoush, Hisham M., Alves, Cesar A. P. F., Severino, Mariasavina, Dellepiane, Francesco, Robson, Caroline D., Lequin, Maarten H., Rossi-Espagnet, Camilla, O'Brien, William T., Nash, Robert, Clement, Emma, and Juliano, Amy F.

Subjects
MEMBRANE transport proteins, VESTIBULAR aqueduct, GOITER, SENSORINEURAL hearing loss, COMPUTED tomography, RETROSPECTIVE studies, MAGNETIC resonance imaging, LONGITUDINAL method, RESEARCH, MEDICAL records, ACQUISITION of data, PENDRED syndrome, GENETIC mutation, GENOTYPES, PHENOTYPES, GENETIC testing
Abstract

Purpose: Incomplete partition type II (IP-II) is characterized by specific histological features and radiological appearance. It may occur in isolation or in association with an enlarged vestibular aqueduct (EVA). Among those with IP-II and EVA, a subset has a diagnosis of Pendred syndrome. This study aimed to explore the prevalence of isolated IP-II, IP-II with EVA, and cases with a genetic or syndromic basis in our cohort. Methods: From a large, multicentre database of dysplastic cochleae (446 patients, 892 temporal bones), those with imaging features of IP-II were examined in detail, including whether there was a genetic or syndromic association. Results: A total of 78 patients with IP-II were identified. Among these, 55 patients had bilateral IP-II and EVA (only 12 with typical Mondini triad), 8 with bilateral IP-II and normal VA, 2 with bilateral IP-II and unilateral EVA, and 13 with unilateral IP-II (9 with unilateral EVA). Among the group with bilateral IP-II and bilateral EVA in whom genetic analysis was available, 14 out of 29 (48%) had SLC26A4 mutations and a diagnosis of Pendred syndrome, 1 had a FOXI1 mutation, and a few other genetic abnormalities; none had KCNJ10 pathogenic variants. Conclusion: Bilateral IP-II-bilateral EVA may be seen in the context of Pendred syndrome (SLC26A4 or FOXI1 mutations) but, in the majority of our cohort, no genetic abnormalities were found, suggesting the possibility of unknown genetic associations. IP-II in isolation (without EVA) is favored to be genetic when bilateral, although the cause is often unknown. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Characterizing Frontal Lobe Seizure Semiology in Children

Author

van Dalen, Thijs, primary, Kirkham, Jessica F, additional, Chari, Aswin, additional, D'Arco, Felice, additional, Moeller, Friederike, additional, Eltze, Christin, additional, Cross, J Helen, additional, Tisdall, Martin M, additional, and Thornton, Rachel C, additional

Published
2024
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47. The clinical and genetic spectrum of inherited glycosylphosphatidylinositol deficiency disorders

Author

Genetica Klinische Genetica, Child Health, MS Radiologie, Circulatory Health, MS Neonatologie, Sidpra, Jai, Sudhakar, Sniya, Biswas, Asthik, Massey, Flavia, Turchetti, Valentina, Lau, Tracy, Cook, Edward, Alvi, Javeria Raza, Elbendary, Hasnaa M, Jewell, Jerry L, Riva, Antonella, Orsini, Alessandro, Vignoli, Aglaia, Federico, Zara, Rosenblum, Jessica, Schoonjans, An-Sofie, de Wachter, Matthias, Delgado Alvarez, Ignacio, Felipe-Rucián, Ana, Haridy, Nourelhoda A, Haider, Shahzad, Zaman, Mashaya, Banu, Selina, Anwaar, Najwa, Rahman, Fatima, Maqbool, Shazia, Yadav, Rashmi, Salpietro, Vincenzo, Maroofian, Reza, Patel, Rajan, Radhakrishnan, Rupa, Prabhu, Sanjay P, Lichtenbelt, Klaske, Stewart, Helen, Murakami, Yoshiko, Löbel, Ulrike, D'Arco, Felice, Wakeling, Emma, Jones, Wendy, Hay, Eleanor, Bhate, Sanjay, Jacques, Thomas S, Mirsky, David M, Whitehead, Matthew T, Zaki, Maha S, Sultan, Tipu, Striano, Pasquale, Jansen, Anna C, Lequin, Maarten, de Vries, Linda S, Severino, Mariasavina, Edmondson, Andrew C, Menzies, Lara, Campeau, Philippe M, Houlden, Henry, McTague, Amy, Efthymiou, Stephanie, Mankad, Kshitij, Genetica Klinische Genetica, Child Health, MS Radiologie, Circulatory Health, MS Neonatologie, Sidpra, Jai, Sudhakar, Sniya, Biswas, Asthik, Massey, Flavia, Turchetti, Valentina, Lau, Tracy, Cook, Edward, Alvi, Javeria Raza, Elbendary, Hasnaa M, Jewell, Jerry L, Riva, Antonella, Orsini, Alessandro, Vignoli, Aglaia, Federico, Zara, Rosenblum, Jessica, Schoonjans, An-Sofie, de Wachter, Matthias, Delgado Alvarez, Ignacio, Felipe-Rucián, Ana, Haridy, Nourelhoda A, Haider, Shahzad, Zaman, Mashaya, Banu, Selina, Anwaar, Najwa, Rahman, Fatima, Maqbool, Shazia, Yadav, Rashmi, Salpietro, Vincenzo, Maroofian, Reza, Patel, Rajan, Radhakrishnan, Rupa, Prabhu, Sanjay P, Lichtenbelt, Klaske, Stewart, Helen, Murakami, Yoshiko, Löbel, Ulrike, D'Arco, Felice, Wakeling, Emma, Jones, Wendy, Hay, Eleanor, Bhate, Sanjay, Jacques, Thomas S, Mirsky, David M, Whitehead, Matthew T, Zaki, Maha S, Sultan, Tipu, Striano, Pasquale, Jansen, Anna C, Lequin, Maarten, de Vries, Linda S, Severino, Mariasavina, Edmondson, Andrew C, Menzies, Lara, Campeau, Philippe M, Houlden, Henry, McTague, Amy, Efthymiou, Stephanie, and Mankad, Kshitij

Published
2024

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