Dr Kanishka Sharma

PhD, MSc, BTech

Clinical Medicine, School of Medicine and Population Health

Research Fellow

kanishka.sharma@sheffield.ac.uk
+44 114 215 9142

Polaris

Full contact details

Dr Kanishka Sharma
Clinical Medicine, School of Medicine and Population Health
Polaris
18 Claremont Crescent
Sheffield
S10 2TA

Profile: My current research focus is on the investigation of MR imaging biomarkers for the multi-centre, multi-parametric iBEAt study within the BEAt-DKD project. I obtained my PhD (2017) at the Technical University of Munich on the research topic of Machine Learning Methods for Segmentation in Autosomal Dominant Polycystic Kidney Disease. At this time, my research was funded by the EU-FP7 project TranCYST (Marie Skłodowska-Curie Actions Research Fellow) at the Mario Negri Institute for Pharmacological Research (2013-2016).

Research interests

My research interests include quantitative MRI, imaging biomarkers, machine learning applications in medical imaging, medical image segmentation and registration, multi-centre clinical trials on kidney diseases, magnetic resonance imaging for abdominal imaging.

Workstreams:

Abdominal imaging

Publications

Show: Featured publications All publications

Featured publications

Journal articles

Gooding KM, Lienczewski C, Papale M, Koivuviita N, Maziarz M, Dutius Andersson A-M, Sharma K, Pontrelli P, Garcia Hernandez A, Bailey J , Tobin K et al (2020) Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol. BMC Nephrology, 21(1).
Sharma K, Rupprecht C, Caroli A, Aparicio MC, Remuzzi A, Baust M & Navab N (2017) Automatic Segmentation of Kidneys using Deep Learning for Total Kidney Volume Quantification in Autosomal Dominant Polycystic Kidney Disease. Scientific Reports, 7(1).
Alhummiany BA, Shelley D, Saysell M, Olaru M, Kühn B, Buckley DL, Bailey J, Wroe K, Coupland C, Mansfield MW , Sourbron SP et al () Bias and Precision in Magnetic Resonance Imaging‐Based Estimates of Renal Blood Flow: Assessment by Triangulation. Journal of Magnetic Resonance Imaging.
Sharma K, Caroli A, Quach LV, Petzold K, Bozzetto M, Serra AL, Remuzzi G & Remuzzi A () Kidney volume measurement methods for clinical studies on autosomal dominant polycystic kidney disease. PLOS ONE, 12(5), e0178488-e0178488.

All publications

Journal articles

Päivärinta J, Anastasiou IA, Koivuviita N, Sharma K, Nuutila P, Ferrannini E, Solini A & Rebelos E (2023) Renal Perfusion, Oxygenation and Metabolism: The Role of Imaging. Journal of Clinical Medicine, 12(15), 5141-5141.
de Boer A, Villa G, Bane O, Bock M, Cox EF, Dekkers IA, Eckerbom P, Fernández‐Seara MA, Francis ST, Haddock B , Hall ME et al (2020) Consensus‐based technical recommendations for clinical translation of renal phase contrast MRI. Journal of Magnetic Resonance Imaging. View this article in WRRO
Gooding KM, Lienczewski C, Papale M, Koivuviita N, Maziarz M, Dutius Andersson A-M, Sharma K, Pontrelli P, Garcia Hernandez A, Bailey J , Tobin K et al (2020) Prognostic imaging biomarkers for diabetic kidney disease (iBEAt): study protocol. BMC Nephrology, 21(1).
Dekkers IA, de Boer A, Sharma K, Cox EF, Lamb HJ, Buckley DL, Bane O, Morris DM, Prasad PV, Semple SIK , Gillis KA et al (2020) Consensus-based technical recommendations for clinical translation of renal T1 and T2 mapping MRI. Magnetic Resonance Materials in Physics, Biology and Medicine, 33(1), 163-176.
Mendichovszky I, Pullens P, Dekkers I, Nery F, Bane O, Pohlmann A, de Boer A, Ljimani A, Odudu A, Buchanan C , Sharma K et al (2020) Technical recommendations for clinical translation of renal MRI: a consensus project of the Cooperation in Science and Technology Action PARENCHIMA. Magnetic Resonance Materials in Physics, Biology and Medicine, 33(1), 131-140.
Ljimani A, Caroli A, Laustsen C, Francis S, Mendichovszky IA, Bane O, Nery F, Sharma K, Pohlmann A, Dekkers IA , Vallee J-P et al (2020) Correction to: Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI. Magnetic Resonance Materials in Physics, Biology and Medicine, 33(1), 197-198.
Nery F, Buchanan CE, Harteveld AA, Odudu A, Bane O, Cox EF, Derlin K, Gach HM, Golay X, Gutberlet M , Laustsen C et al (2020) Consensus-based technical recommendations for clinical translation of renal ASL MRI. Magnetic Resonance Materials in Physics, Biology and Medicine, 33(1), 141-161.
Bane O, Mendichovszky IA, Milani B, Dekkers IA, Deux J-F, Eckerbom P, Grenier N, Hall ME, Inoue T, Laustsen C , Lerman LO et al (2020) Consensus-based technical recommendations for clinical translation of renal BOLD MRI. Magnetic Resonance Materials in Physics, Biology and Medicine, 33(1), 199-215.
Ljimani A, Caroli A, Laustsen C, Francis S, Mendichovszky IA, Bane O, Nery F, Sharma K, Pohlmann A, Dekkers IA , Vallee J-P et al (2020) Consensus-based technical recommendations for clinical translation of renal diffusion-weighted MRI. Magnetic Resonance Materials in Physics, Biology and Medicine, 33(1), 177-195.
Wolf M, de Boer A, Sharma K, Boor P, Leiner T, Sunder-Plassmann G, Moser E, Caroli A & Jerome NP (2018) Magnetic resonance imaging T1- and T2-mapping to assess renal structure and function: a systematic review and statement paper. Nephrology Dialysis Transplantation, 33(suppl_2), ii41-ii50.
Parvanova A, Trillini M, Podestà MA, Iliev IP, Aparicio C, Perna A, Peraro F, Rubis N, Gaspari F, Cannata A , Ferrari S et al (2018) Blood Pressure and Metabolic Effects of Acetyl-l-Carnitine in Type 2 Diabetes: DIABASI Randomized Controlled Trial. Journal of the Endocrine Society, 2(5), 420-436.
Sharma K, Rupprecht C, Caroli A, Aparicio MC, Remuzzi A, Baust M & Navab N (2017) Automatic Segmentation of Kidneys using Deep Learning for Total Kidney Volume Quantification in Autosomal Dominant Polycystic Kidney Disease. Scientific Reports, 7(1).
Ruggenenti P, Gentile G, Perico N, Perna A, Barcella L, Trillini M, Cortinovis M, Ferrer Siles CP, Reyes Loaeza JA, Aparicio MC , Fasolini G et al (2016) Effect of Sirolimus on Disease Progression in Patients with Autosomal Dominant Polycystic Kidney Disease and CKD Stages 3b-4. Clinical Journal of the American Society of Nephrology, 11(5), 785-794.
Caroli A, Villa G, Brambilla P, Trillini M, Sharma K, Sironi S, Remuzzi G, Perico N & Remuzzi A () Diffusion magnetic resonance imaging for kidney cyst volume quantification and non-cystic tissue characterisation in ADPKD. European Radiology.
Alhummiany BA, Shelley D, Saysell M, Olaru M, Kühn B, Buckley DL, Bailey J, Wroe K, Coupland C, Mansfield MW , Sourbron SP et al () Bias and Precision in Magnetic Resonance Imaging‐Based Estimates of Renal Blood Flow: Assessment by Triangulation. Journal of Magnetic Resonance Imaging.
Sharma K, Caroli A, Quach LV, Petzold K, Bozzetto M, Serra AL, Remuzzi G & Remuzzi A () Kidney volume measurement methods for clinical studies on autosomal dominant polycystic kidney disease. PLOS ONE, 12(5), e0178488-e0178488.

Projects

Current project participation:

08/2017 – present (role: research fellow). Biomarker Enterprise to Attack Diabetic Kidney Disease – BEAt-DKD (WP4: The iBEAt study): A major international IMI and EU-funded (public-private partnership) research project that aims to identify and validate improved prognostic biomarkers for development of effective and personalized treatments for Diabetic Kidney Disease (DKD) and involves a tight collaboration between academia, industry and SME’s. Within BEAt-DKD, WP4 involves an imaging theme (iBEAt study), a prospective multi-centre observational cohort recruiting 500 patients with type 2 diabetes at 6 participating sites in Europe (Bari, Bordeaux, Exeter, Leeds, Sheffield, Turku). The recruited patients undergo quantitative multi-parametric renal MRI (multi-vendor 3T scanners) and US at baseline followed by a central processing of the MRI images at Sheffield.

Past project participation:

2017 – 2020 (role: collaborator). Magnetic Resonance Imaging Biomarkers for Chronic Kidney Disease (PARENCHIMA). Funded by COST (European Cooperation in Science and Technology), PARENCHIMA coordinates research and collaboration among leading European groups to boost the use of renal MRI biomarkers, eliminate barriers of broader study, commercial exploitation, and improve management of chronic kidney disease patients.

Task Force participant:

Work Group 1 Participant (2019): Technical recommendations on clinical renal MRI.
Work Group 3 Participant (2018): T1- and T2-Mapping of Renal Tissue to assess Structure and Function in Chronic Kidney Disease.
2017 – 2019 (role: collaborator). The UK Renal Imaging Network (UKRIN): The Medical Research Council (MRC) funded UKRIN initiative brings together major UK renal MRI research centres to develop MRI methods for the study of the kidney.
2013 – 2017 (role: Marie Skłodowska-Curie Actions Research Fellow, PhD candidate). Translational research (training) in Polycystic Kidney Disease (TRANCYST): Development of novel kidney segmentation approaches for volumetric quantification of the ADPKD kidneys followed by evaluation on existing imaging data from clinical trials on ADPKD patients.

School of Medicine and Population Health

Dr Kanishka Sharma

Workstreams:

Featured publications

Journal articles

All publications

Journal articles

Current project participation:

Past project participation:

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