Evaluating the metabolic effects of neoadjuvant treatment in clear cell renal cell carcinoma using hyperpolarised [1-13C]pyruvate MRI

Evaluating the metabolic effects of neoadjuvant treatment in clear cell renal cell carcinoma using hyperpolarised [1-13C]pyruvate MRI | medRxiv /* */ /* */ <!-- <!-- /*! * yepnope1.5.4 * (c) WTFPL, GPLv2 */ (function(a,b,c){function d(a){return"[object Function]"==o.call(a)}function e(a){return"string"==typeof a}function f(){}function g(a){return!a||"loaded"==a||"complete"==a||"uninitialized"==a}function h(){var a=p.shift();q=1,a?a.t?m(function(){("c"==a.t?B.injectCss:B.injectJs)(a.s,0,a.a,a.x,a.e,1)},0):(a(),h()):q=0}function i(a,c,d,e,f,i,j){function k(b){if(!o&&g(l.readyState)&&(u.r=o=1,!q&&h(),l.onload=l.onreadystatechange=null,b)){"img"!=a&&m(function(){t.removeChild(l)},50);for(var d in y[c])y[c].hasOwnProperty(d)&&y[c][d].onload()}}var 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, Ashley Grimmer , Elizabeth Latimer , Alixander S Khan , Andrew N Priest , Andrew B Gill , Joshua D Kaggie , Martin J Graves , Tristan Barrett , James MS Wason , Helen Mossop , Martin Thomas , Sulekha Said , Anne Y Warren , Kate Fife , Tim Eisen , Athena Matakidou , Will Ince , Brent O’Carrigan , James Jones , Sarah J Welsh , Thomas J Mitchell , James N Armitage , Antony CP Riddick , Grant D Stewart , Ferdia A Gallagher doi: https://doi.org/10.1101/2025.05.22.25328092 Ines Horvat-Menih 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: ih357{at}cam.ac.uk Mary A McLean 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Jonathan Birchall 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Maria Jesus Zamora Morales 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Marta Wylot 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Stephan Ursprung 2 Netherlands Cancer Institute , 1066CX Amsterdam, Netherlands Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ramona Woitek 3 Research Center for Medical Image Analysis and Artificial Intelligence (MIAAI), Danube Private University , 3500 Krems an der Donau, Austria Find this author on Google Scholar Find this author on PubMed Search for this author on this site Eva Serrao 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ashley Grimmer 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Elizabeth Latimer 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Alixander S Khan 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Andrew N Priest 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Andrew B Gill 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Joshua D Kaggie 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Martin J Graves 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tristan Barrett 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site James MS Wason 5 Population Health Sciences Institute, Newcastle University , Newcastle upon Tyne, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Helen Mossop 5 Population Health Sciences Institute, Newcastle University , Newcastle upon Tyne, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Martin Thomas 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sulekha Said 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Anne Y Warren 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Kate Fife 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Tim Eisen 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Athena Matakidou 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Will Ince 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Brent O’Carrigan 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site James Jones 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Sarah J Welsh 6 Pinto Medical Consultancy , Cambridge, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Thomas J Mitchell 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK 7 Department of Surgery, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site James N Armitage 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Antony CP Riddick 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Grant D Stewart 4 Cambridge University Hospitals NHS Foundation Trust , Cambridge CB2 0QQ, UK 7 Department of Surgery, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Ferdia A Gallagher 1 Department of Radiology, University of Cambridge , Cambridge CB2 0QQ, UK Find this author on Google Scholar Find this author on PubMed Search for this author on this site Abstract Full Text Info/History Metrics Supplementary material Data/Code Preview PDF Abstract Despite recent advances, ∼50% of people developing renal cell carcinoma (RCC) will die of the disease. The development of new neoadjuvant therapeutic strategies requires reliable companion biomarkers to measure early and successful response to treatment. Tumour size changes are often late markers of response, but novel imaging-based biomarkers may be more accurate for treatment response prediction. Here we evaluated the potential of hyperpolarised carbon-13 MRI (HP 13 C-MRI) as an emerging clinical imaging technique for assessing response to neoadjuvant treatment in RCC, as part of the WIndow of opportunity in REnal cancer (WIRE) trial. The change in LAC/PYR ratio following treatment was variable across the four patients (mean±S.D. %change = +6±27%). LAC/PYR decreased in the patient treated with cediranib monotherapy (−21%), and in one of the patients receiving combination treatment (−14%). A higher LAC/PYR ratio post-treatment was observed in the second patient receiving combination treatment (+21%) and in the patient receiving olaparib monotherapy (+35%). This is the first study to evaluate the potential of clinical HP 13 C-MRI in assessing early treatment response in renal cancer, which detected metabolic changes following treatment in the absence of significant changes in tumour size. Future studies should assess this finding in larger patient cohorts. Patient summary In this study we used an emerging clinical imaging technique, called hyperpolarised carbon-13 MRI, to visualise how kidney cancer changes with drug treatment before surgery. The method visualised rapid changes in cancer metabolism before substantial changes were seen in tumour size, the latter being the conventional method for detecting response to treatment. Hyperpolarised carbon-13 MRI holds promise in informing clinicians which cancers have successfully responded, and which may benefit from a change in treatment. Introduction Renal cell carcinoma (RCC) is the most common kidney malignancy with an increasing incidence globally, but with no decline in mortality rates 1 . Surgery with curative intent is the treatment of choice for clinically-fit patients whose disease burden is amenable to resection, yet ∼30% experience recurrence 1 , 2 . Neoadjuvant approaches may allow more rapid treatment of patients with aggressive localised disease whilst potentially minimising the need for adjuvant therapy after surgery 3 . A particular challenge for studies evaluating neoadjuvant therapy is the lack of validated predictive biomarkers in RCC, which delays the advancement of novel agents 3 . Currently the treatment response is determined using the RECIST 1.1 criteria (Response Evaluation Criteria in Solid Tumours), which are based on the change in size of target lesions 4 . However, not only is evidence lacking for the use of RECIST-defined progression as a clinically valid endpoint for treatment modification, but also morphologic changes alone may be insufficient for capturing response to novel targeted therapies 4 . Hyperpolarised [1- 13 C]pyruvate MRI (HP 13 C-MRI) is a novel clinical imaging technique to probe metabolic conversion of injected hyperpolarised [1- 13 C]pyruvate tracer to [1- 13 C]lactate. A decrease in tumour lactate labelling has been demonstrated after several weeks of treatment in prostate cancer 5 , and furthermore, the technique detected response to neoadjuvant therapy in breast cancer after only 7-11 days, which outperformed conventional MRI in distinguishing pathological complete response from non-responders 6 . In renal cancer, the HP 13 C-MRI has shown potential for assessing tumour aggressiveness, but has not yet been probed as a marker of treatment response 7 . WIndow-of-opportunity in REnal cell cancer (WIRE) is a phase II, multi-arm, non-randomised trial which probes the biological mechanism of novel targeted therapies during the interval between diagnosis and surgery ( NCT03741426 ). Here we report the application of HP 13 C-MRI to probe metabolic treatment response to: cediranib (a tyrosine-kinase inhibitor), olaparib (a poly ADP-ribose polymerase or PARP inhibitor), and both agents in combination. Findings were compared to changes in tumour size, perfusion, and diffusion. Results Details on Patients and Methods are to be found in Supplementary. Four patients with a diagnosis of resectable clear cell RCC (ccRCC) who were recruited to the WIRE trial underwent successful HP 13 C-MRI before and after treatment. An overview of the clinical characteristics is presented in Suppl. Table S1. Representative maps of 13 C-LAC/PYR ratio overlaid on anatomical T 1 w images before and after treatment are presented in Fig. 1 . Quantitative results are presented in Suppl. Table S2. The mean LAC/PYR ratio change for all four patients showed a slight increase of +6% post-treatment but with a significant interpatient variation in the S.D. of 27%. Patients 1 and 2 demonstrated a decrease in the tumour LAC/PYR of -21% (baseline: 0.19; post-treatment: 0.15) and -14% (baseline: 0.21; post-treatment: 0.18), while Patients 3 and 4 showed an increase in the tumour LAC/PYR ratio post-treatment of +21% (baseline: 0.07; post-treatment: 0.09) and +35% (baseline: 0.17; post-treatment: 0.23) respectively. Download figure Open in new tab Figure 1. Representative LAC/PYR maps of the four patients overlaid on T 1 w images, with tumour ROIs annotated in blue (baseline) and green (post-treatment). Percentage changes between baseline and post-treatment LAC/PYR ratio presented in arrows for each individual patient. ROI = region of interest. The perfusion surrogate, f p , showed the greatest and most consistent changes post-treatment of -31±18%, followed by the hypoxia surrogate, R 2 *, of +18±21% ( Fig. 2a ). The treatment effect on diffusion coefficient, D 0 , was variable, where Patients 1 and 3 exhibited a decrease (−14% and -3%, respectively), and Patients 2 and 4 an increase (+4% and +10%, respectively). Only small alterations were observed in tumour diameters, with a mean decrease of -4% from 9.1 cm at baseline to 8.7 cm at post-treatment (S.D. 3%). Mean volumetric changes were greater: -10% over the treatment time course (S.D. 18%); Patient 4 (olaparib only) showed a 13% increase in tumour volume post-treatment. This was associated with greatest increase in D 0 of +10% indicating reduced restriction, the largest decrease in the f p of -57%, as well as the highest baseline R 2 *, which remained high post-treatment (0% change). Correlative analysis as shown in Fig. 2b , with detailed results in Suppl. Table S3, confirmed a significant relationship between the %changes in tumour volume and D 0 (Pearson r = 0.96, P < 0.05), and though non-significant, a strong negative correlation coefficient with f p (Pearson r = -0.84, P = 0.165), and R 2 * (Pearson r = -0.92, P = 0.052), respectively. The LAC/PYR changes were independent of the alterations in other imaging metrics. Download figure Open in new tab Figure 2. (a) Paired plots representing changes in the imaging parameters pre- (blue) and post-treatment (green). LAC/PYR ratio and D 0 showed variable changes, whereas f p and R 2 * were most consistently altered post-treatment. (b) Correlation analyses between these imaging parameters presented in a heatmap, labelled with respective Pearson coefficients. B = baseline, After-Tx = after-treatment. Discussion Four patients undergoing neoadjuvant treatment showed variable changes in the tumour LAC/PYR ratio, which occurred in the absence of diameter or volume changes, suggesting that HP 13 C-MRI may distinguish early metabolic changes before morphological ones can be measured. These results are similar to those reported previously in breast cancer, where an increase in LAC/PYR ratio predicted response to standard-of-care neoadjuvant chemotherapy after 7-11 days 6 . We have demonstrated previously that the LAC/PYR ratio increased in breast cancer patients undergoing olaparib therapy, irrespective of their response 6 . PARP inhibitors are known to increase intracellular concentrations of nicotinamide adenine dinucleotide (NAD+), an essential co-factor for many redox pathways, which then becomes available as a co-factor for the reaction catalysed by lactate dehydrogenase, promoting the exchange between pyruvate and lactate 8 . An increase in lactate labelling could therefore represent drug engagement with the target 9 . The LAC/PYR ratio decreased in the patient receiving cediranib monotherapy (−21%) and increased in the patient receiving olaparib alone (+35%), with the two patients on combinational therapy showing values between these two values: this supports the suggestion that cediranib and olaparib have opposing effects on tumour metabolism, as well as potential for distinguishing between responders and non-responders in patients receiving olaparib. Furthermore, Patient 4 displayed the greatest decrease in the perfusion fraction (−57%) across all the patients, even though olaparib is not an antiangiogenic agent and this may be related to high tumour hypoxia, as measured by the hypoxia surrogate R 2 *, which has been previously suggested to enhance the action of olaparib 10 . The present study is the first to evaluate the potential of HP 13 C-MRI in assessing early treatment response in renal cancer. HP 13 C-MRI detected metabolic changes following treatment in the absence of significant changes in size on clinical proton MRI and larger trials are needed to confirm these findings and to correlate these changes with long-term clinical outcome. Data Availability All data produced in the present study are available upon reasonable request to the authors. Conflicts of interest G.D.S. has received educational grants from Pfizer, AstraZeneca, and Intuitive Surgical; consultancy fees from Pfizer, MSD, EUSA Pharma, and CMR Surgical; travel expenses from MSD and Pfizer; speaker fees from Pfizer; clinical lead (urology) National Kidney Cancer Audit and Topic Advisor for the NICE kidney cancer guideline. S.J.W. is a founder and director of Pinto Medical Consultancy. F.A.G. and J.D.K. have research grants from GlaxoSmithKline and AstraZeneca and research support from GE Healthcare. F.A.G. has consulted for AstraZeneca on behalf of the University of Cambridge. Funding This study was funded by Cancer Research UK (C19212/A27150, C19212/A29082, and C19212/A16628). This study was supported by AstraZeneca and Merck Sharp & Dohme LLC, a subsidiary of Merck & Co., Inc., Rahway, NJ, USA, who are codeveloping olaparib. This research was also supported by the Mark Foundation for Cancer Research (RG95043), Cancer Research UK Cambridge Centre (C9685/A25177 and CTRQQR-2021\100012), and the National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC-1215-20014 and NIHR203312) and the Cambridge Clinical Trials Unit (CCTU). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. The authors have additional funding from the National Cancer Imaging Translational Accelerator (NCITA; C42780/A27066), the Cambridge Experimental Cancer Medicine Centre, the Mark Foundation Institute for Integrated Cancer Medicine (MFICM), the Canadian Institute For Advanced Research (CIFAR). Acknowledgements We acknowledge the invaluable feedback by the patient representatives, as well as the administrative and technical support from the Advanced Cancer Imaging and Urological Malignancies programmes, Cancer Research UK (CRUK) Cambridge Centre, and radiographers of the Magnetic Resonance Spectroscopy Unit, Addenbrookes. Footnotes ↵ † Joint senior authors. References 1. ↵ Stewart GD , Klatte T , Cosmai L , et al. The multispeciality approach to the management of localised kidney cancer . The Lancet . 2022 ; 400 ( 10351 ): 523 – 534 . doi: 10.1016/S0140-6736(22)01059-5 OpenUrl CrossRef 2. ↵ Fallara G , Larcher A , Dabestani S , et al. Recurrence pattern in localized RCC: results from a European multicenter database (RECUR) . Urologic Oncology: Seminars and Original Investigations . 2022 ; 40 ( 11 ): 494 .e11-494.e17. doi: 10.1016/j.urolonc.2022.08.007 OpenUrl CrossRef 3. ↵ Marandino L , Campi R , Amparore D , et al. Neoadjuvant and Adjuvant Immune-based Approach for Renal Cell Carcinoma: Pros, Cons, and Future Directions . European Urology Oncology . Published online September 2024:S2588931124002116. doi: 10.1016/j.euo.2024.09.002 OpenUrl CrossRef 4. ↵ Ko CC , Yeh LR , Kuo YT , Chen JH . Imaging biomarkers for evaluating tumor response: RECIST and beyond . Biomark Res . 2021 ; 9 ( 1 ): 52 . doi: 10.1186/s40364-021-00306-8 OpenUrl CrossRef PubMed 5. ↵ Aggarwal R , Vigneron DB , Kurhanewicz J. Hyperpolarized 1-[13 C]-Pyruvate Magnetic Resonance Imaging Detects an Early Metabolic Response to Androgen Ablation Therapy in Prostate Cancer . European Urology . 2017 ; 72 ( 6 ): 1028 – 1029 . doi: 10.1016/j.eururo.2017.07.022 OpenUrl CrossRef PubMed 6. ↵ Woitek R , McLean MA , Ursprung S , et al. Hyperpolarized Carbon-13 MRI for Early Response Assessment of Neoadjuvant Chemotherapy in Breast Cancer Patients . Cancer Res . 2021 ; 81 ( 23 ): 6004 – 6017 . doi: 10.1158/0008-5472.CAN-21-1499 OpenUrl Abstract / FREE Full Text 7. ↵ Ursprung S , Woitek R , McLean MA , et al. Hyperpolarized 13C-Pyruvate Metabolism as a Surrogate for Tumor Grade and Poor Outcome in Renal Cell Carcinoma—A Proof of Principle Study . Cancers . 2022 ; 14 ( 2 ): 335 . doi: 10.3390/cancers14020335 OpenUrl CrossRef PubMed 8. ↵ Hurtado-Bagès S , Knobloch G , Ladurner AG , Buschbeck M. The taming of PARP1 and its impact on NAD+ metabolism . Molecular Metabolism . 2020 ; 38 : 100950 . doi: 10.1016/j.molmet.2020.01.014 OpenUrl CrossRef PubMed 9. ↵ Brindle K. Watching tumours gasp and die with MRI: the promise of hyperpolarised 13C MR spectroscopic imaging . Br J Radiol . 2012 ; 85 ( 1014 ): 697 – 708 . doi: 10.1259/bjr/81120511 OpenUrl Abstract / FREE Full Text 10. ↵ Alvarez Secord A , O’Malley DM , Sood AK , Westin SN , Liu JF . Rationale for combination PARP inhibitor and antiangiogenic treatment in advanced epithelial ovarian cancer: A review . Gynecologic Oncology . 2021 ; 162 ( 2 ): 482 – 495 . doi: 10.1016/j.ygyno.2021.05.018 OpenUrl CrossRef PubMed View the discussion thread. Back to top Previous Next Posted May 23, 2025. Download PDF Supplementary Material Data/Code Email Thank you for your interest in spreading the word about medRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. 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Share Evaluating the metabolic effects of neoadjuvant treatment in clear cell renal cell carcinoma using hyperpolarised [1- 13 C]pyruvate MRI Ines Horvat-Menih , Mary A McLean , Jonathan Birchall , Maria Jesus Zamora Morales , Marta Wylot , Stephan Ursprung , Ramona Woitek , Eva Serrao , Ashley Grimmer , Elizabeth Latimer , Alixander S Khan , Andrew N Priest , Andrew B Gill , Joshua D Kaggie , Martin J Graves , Tristan Barrett , James MS Wason , Helen Mossop , Martin Thomas , Sulekha Said , Anne Y Warren , Kate Fife , Tim Eisen , Athena Matakidou , Will Ince , Brent O’Carrigan , James Jones , Sarah J Welsh , Thomas J Mitchell , James N Armitage , Antony CP Riddick , Grant D Stewart , Ferdia A Gallagher medRxiv 2025.05.22.25328092; doi: https://doi.org/10.1101/2025.05.22.25328092 Share This Article: Copy Citation Tools Evaluating the metabolic effects of neoadjuvant treatment in clear cell renal cell carcinoma using hyperpolarised [1- 13 C]pyruvate MRI Ines Horvat-Menih , Mary A McLean , Jonathan Birchall , Maria Jesus Zamora Morales , Marta Wylot , Stephan Ursprung , Ramona Woitek , Eva Serrao , Ashley Grimmer , Elizabeth Latimer , Alixander S Khan , Andrew N Priest , Andrew B Gill , Joshua D Kaggie , Martin J Graves , Tristan Barrett , James MS Wason , Helen Mossop , Martin Thomas , Sulekha Said , Anne Y Warren , Kate Fife , Tim Eisen , Athena Matakidou , Will Ince , Brent O’Carrigan , James Jones , Sarah J Welsh , Thomas J Mitchell , James N Armitage , Antony CP Riddick , Grant D Stewart , Ferdia A Gallagher medRxiv 2025.05.22.25328092; doi: https://doi.org/10.1101/2025.05.22.25328092 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Radiology and Imaging Subject Areas All Articles Addiction Medicine (568) Allergy and Immunology (863) Anesthesia (297) Cardiovascular Medicine (4421) Dentistry and Oral Medicine (443) Dermatology (382) Emergency Medicine (606) Endocrinology (including Diabetes Mellitus and Metabolic Disease) (1507) Epidemiology (15212) Forensic Medicine (30) Gastroenterology (1121) Genetic and Genomic Medicine (6581) Geriatric Medicine (667) Health Economics (996) Health Informatics (4520) Health Policy (1366) Health Systems and Quality Improvement (1611) Hematology (539) HIV/AIDS (1264) Infectious Diseases (except HIV/AIDS) (15906) Intensive Care and Critical Care Medicine (1103) Medical Education (620) Medical Ethics (144) Nephrology (667) Neurology (6580) Nursing (345) Nutrition (998) Obstetrics and Gynecology (1141) Occupational and Environmental Health (956) Oncology (3324) Ophthalmology (970) Orthopedics (369) Otolaryngology (420) Pain Medicine (435) Palliative Medicine (129) Pathology (663) Pediatrics (1689) Pharmacology and Therapeutics (691) Primary Care Research (710) Psychiatry and Clinical Psychology (5433) Public and Global Health (9212) Radiology and Imaging (2193) Rehabilitation Medicine and Physical Therapy (1368) Respiratory Medicine (1194) Rheumatology (593) Sexual and Reproductive Health (709) Sports Medicine (529) Surgery (709) Toxicology (99) Transplantation (288) Urology (265) (function(){function c(){var b=a.contentDocument||a.contentWindow.document;if(b){var d=b.createElement('script');d.innerHTML="window.__CF$cv$params={r:'9ff61aa26a74ad07',t:'MTc3OTM5Mjk2Mg=='};var a=document.createElement('script');a.src='/cdn-cgi/challenge-platform/scripts/jsd/main.js';document.getElementsByTagName('head')[0].appendChild(a);";b.getElementsByTagName('head')[0].appendChild(d)}}if(document.body){var a=document.createElement('iframe');a.height=1;a.width=1;a.style.position='absolute';a.style.top=0;a.style.left=0;a.style.border='none';a.style.visibility='hidden';document.body.appendChild(a);if('loading'!==document.readyState)c();else if(window.addEventListener)document.addEventListener('DOMContentLoaded',c);else{var e=document.onreadystatechange||function(){};document.onreadystatechange=function(b){e(b);'loading'!==document.readyState&&(document.onreadystatechange=e,c())}}}})();