OBJECTIVE: A valid method for accurate quantification of abdominal fat distribution (AFD) using both CT and MRI is described. This method will be primarily useful in the prospective risk stratification of patients undergoing reconstructive breast surgery. Secondary applications in many other clinical specialities are foreseen. METHODS: 15 sequential patients who had undergone breast reconstruction following both CT and MRI (30 scans) were retrospectively identified at our single centre. The AFD was quantified at the level of the L3 vertebra. Image analysis was performed by at least two independent operators using free software. Intra- and interobserver differences were assessed using Bland-Altman plots. Data were validated between imaging modalities by Pearson's correlation. Linear regression analyses were used to mathematically normalize results between imaging modalities. RESULTS: The method was statistically independent of rater bias (intra: Pearson's R-0.954-1.00; inter: 0.799-0.999). Strong relationships between imaging modalities were demonstrated and are independent of time between imaging (Pearson's R 0.625-0.903). Interchangeable mathematical models to normalize between imaging modality are shown. CONCLUSION: The method described is highly reproducible and independent of rater bias. A strong interchangeable relationship exists between calculations of AFD on retrospective CT and MRI. Advances in knowledge: This is the first technique to be applicable to scans that are not performed sequentially or in a research setting. Analysis is semi-automated and results can be compared directly, regardless of imaging modality or patient position. This method has clinical utility in prospective risk stratification and will be applicable to many clinical specialities.
OBJECTIVE: A valid method for accurate quantification of abdominal fat distribution (AFD) using both CT and MRI is described. This method will be primarily useful in the prospective risk stratification of patients undergoing reconstructive breast surgery. Secondary applications in many other clinical specialities are foreseen. METHODS: 15 sequential patients who had undergone breast reconstruction following both CT and MRI (30 scans) were retrospectively identified at our single centre. The AFD was quantified at the level of the L3 vertebra. Image analysis was performed by at least two independent operators using free software. Intra- and interobserver differences were assessed using Bland-Altman plots. Data were validated between imaging modalities by Pearson's correlation. Linear regression analyses were used to mathematically normalize results between imaging modalities. RESULTS: The method was statistically independent of rater bias (intra: Pearson's R-0.954-1.00; inter: 0.799-0.999). Strong relationships between imaging modalities were demonstrated and are independent of time between imaging (Pearson's R 0.625-0.903). Interchangeable mathematical models to normalize between imaging modality are shown. CONCLUSION: The method described is highly reproducible and independent of rater bias. A strong interchangeable relationship exists between calculations of AFD on retrospective CT and MRI. Advances in knowledge: This is the first technique to be applicable to scans that are not performed sequentially or in a research setting. Analysis is semi-automated and results can be compared directly, regardless of imaging modality or patient position. This method has clinical utility in prospective risk stratification and will be applicable to many clinical specialities.
Authors: J Kullberg; J Brandberg; J-E Angelhed; H Frimmel; E Bergelin; L Strid; H Ahlström; L Johansson; L Lönn Journal: Br J Radiol Date: 2009-02 Impact factor: 3.039
Authors: Stephen S Lim; Theo Vos; Abraham D Flaxman; Goodarz Danaei; Kenji Shibuya; Heather Adair-Rohani; Markus Amann; H Ross Anderson; Kathryn G Andrews; Martin Aryee; Charles Atkinson; Loraine J Bacchus; Adil N Bahalim; Kalpana Balakrishnan; John Balmes; Suzanne Barker-Collo; Amanda Baxter; Michelle L Bell; Jed D Blore; Fiona Blyth; Carissa Bonner; Guilherme Borges; Rupert Bourne; Michel Boussinesq; Michael Brauer; Peter Brooks; Nigel G Bruce; Bert Brunekreef; Claire Bryan-Hancock; Chiara Bucello; Rachelle Buchbinder; Fiona Bull; Richard T Burnett; Tim E Byers; Bianca Calabria; Jonathan Carapetis; Emily Carnahan; Zoe Chafe; Fiona Charlson; Honglei Chen; Jian Shen Chen; Andrew Tai-Ann Cheng; Jennifer Christine Child; Aaron Cohen; K Ellicott Colson; Benjamin C Cowie; Sarah Darby; Susan Darling; Adrian Davis; Louisa Degenhardt; Frank Dentener; Don C Des Jarlais; Karen Devries; Mukesh Dherani; Eric L Ding; E Ray Dorsey; Tim Driscoll; Karen Edmond; Suad Eltahir Ali; Rebecca E Engell; Patricia J Erwin; Saman Fahimi; Gail Falder; Farshad Farzadfar; Alize Ferrari; Mariel M Finucane; Seth Flaxman; Francis Gerry R Fowkes; Greg Freedman; Michael K Freeman; Emmanuela Gakidou; Santu Ghosh; Edward Giovannucci; Gerhard Gmel; Kathryn Graham; Rebecca Grainger; Bridget Grant; David Gunnell; Hialy R Gutierrez; Wayne Hall; Hans W Hoek; Anthony Hogan; H Dean Hosgood; Damian Hoy; Howard Hu; Bryan J Hubbell; Sally J Hutchings; Sydney E Ibeanusi; Gemma L Jacklyn; Rashmi Jasrasaria; Jost B Jonas; Haidong Kan; John A Kanis; Nicholas Kassebaum; Norito Kawakami; Young-Ho Khang; Shahab Khatibzadeh; Jon-Paul Khoo; Cindy Kok; Francine Laden; Ratilal Lalloo; Qing Lan; Tim Lathlean; Janet L Leasher; James Leigh; Yang Li; John Kent Lin; Steven E Lipshultz; Stephanie London; Rafael Lozano; Yuan Lu; Joelle Mak; Reza Malekzadeh; Leslie Mallinger; Wagner Marcenes; Lyn March; Robin Marks; Randall Martin; Paul McGale; John McGrath; Sumi Mehta; George A Mensah; Tony R Merriman; Renata Micha; Catherine Michaud; Vinod Mishra; Khayriyyah Mohd Hanafiah; Ali A Mokdad; Lidia Morawska; Dariush Mozaffarian; Tasha Murphy; Mohsen Naghavi; Bruce Neal; Paul K Nelson; Joan Miquel Nolla; Rosana Norman; Casey Olives; Saad B Omer; Jessica Orchard; Richard Osborne; Bart Ostro; Andrew Page; Kiran D Pandey; Charles D H Parry; Erin Passmore; Jayadeep Patra; Neil Pearce; Pamela M Pelizzari; Max Petzold; Michael R Phillips; Dan Pope; C Arden Pope; John Powles; Mayuree Rao; Homie Razavi; Eva A Rehfuess; Jürgen T Rehm; Beate Ritz; Frederick P Rivara; Thomas Roberts; Carolyn Robinson; Jose A Rodriguez-Portales; Isabelle Romieu; Robin Room; Lisa C Rosenfeld; Ananya Roy; Lesley Rushton; Joshua A Salomon; Uchechukwu Sampson; Lidia Sanchez-Riera; Ella Sanman; Amir Sapkota; Soraya Seedat; Peilin Shi; Kevin Shield; Rupak Shivakoti; Gitanjali M Singh; David A Sleet; Emma Smith; Kirk R Smith; Nicolas J C Stapelberg; Kyle Steenland; Heidi Stöckl; Lars Jacob Stovner; Kurt Straif; Lahn Straney; George D Thurston; Jimmy H Tran; Rita Van Dingenen; Aaron van Donkelaar; J Lennert Veerman; Lakshmi Vijayakumar; Robert Weintraub; Myrna M Weissman; Richard A White; Harvey Whiteford; Steven T Wiersma; James D Wilkinson; Hywel C Williams; Warwick Williams; Nicholas Wilson; Anthony D Woolf; Paul Yip; Jan M Zielinski; Alan D Lopez; Christopher J L Murray; Majid Ezzati; Mohammad A AlMazroa; Ziad A Memish Journal: Lancet Date: 2012-12-15 Impact factor: 79.321
Authors: A Romero-Corral; V K Somers; J Sierra-Johnson; R J Thomas; M L Collazo-Clavell; J Korinek; T G Allison; J A Batsis; F H Sert-Kuniyoshi; F Lopez-Jimenez Journal: Int J Obes (Lond) Date: 2008-02-19 Impact factor: 5.095
Authors: Mohammed Abdul Waduud; Awais Ul-Hassan; Talha Naveed; Pratik Adusumilli; Thomas Alexander Slater; Sam Straw; Christopher Hammond; David Julian Ashbridge Scott Journal: Br J Radiol Date: 2020-05-27 Impact factor: 3.039
Authors: An Fu Pan; Nan Xin Zheng; Jin Wang; Jean Luc Tshibangu Kabemba; Kuo Zheng; Fu Shen; Wei Zhang; Xian Hua Gao Journal: J Oncol Date: 2022-03-22 Impact factor: 4.375