Literature DB >> 33564999

Rapid Segmentation of Renal Tumours to Calculate Volume Using 3D Interpolation.

Michael Y Chen1,2,3, Maria A Woodruff4, Boon Kua5, Nicholas J Rukin6,4.   

Abstract

Small renal masses are commonly diagnosed with modern medical imaging. Renal tumour volume has been explored as a prognostic tool to help decide when intervention is needed and appears to provide additional prognostic information for smaller tumours compared with tumour diameter. However, the current method of calculating tumour volume in clinical practice uses the ellipsoid equation (π/6 × length × width × height) which is an oversimplified approach. Some research groups trace the contour of the tumour in every image slice which is impractical for clinical use. In this study, we demonstrate a method of using 3D segmentation software and the 3D interpolation method to rapidly calculate renal tumour volume in under a minute. Using this method in 27 patients that underwent radical or partial nephrectomy, we found a 10.07% mean absolute difference compared with the traditional ellipsoid method. Our segmentation volume was closer to the calculated histopathological tumour volume than the traditional method (p = 0.03) with higher Lin's concordance correlation coefficient (0.79 vs 0.72). 3D segmentation has many uses related to 3D printing and modelling and is becoming increasingly common. Calculation of tumour volume is one additional benefit it provides. Further studies on the association between segmented tumour volume and prognosis are needed.
© 2021. Society for Imaging Informatics in Medicine.

Entities:  

Keywords:  Diagnosis; Organ volume; Prognosis; Renal cancer

Mesh:

Year:  2021        PMID: 33564999      PMCID: PMC8289983          DOI: 10.1007/s10278-020-00416-z

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  22 in total

1.  Three-dimensional tumour volume and cancer-specific survival for patients undergoing nephrectomy to treat pT1 clear-cell renal cell carcinoma.

Authors:  Jacob Jorns; David D Thiel; Christine M Lohse; Adrienne Williams; Michelle L Arnold; John C Cheville; Bradley C Leibovich; Alexander S Parker
Journal:  BJU Int       Date:  2012-02-02       Impact factor: 5.588

2.  A simple method to estimate renal volume from computed tomography.

Authors:  Rodney H Breau; Edward Clark; Bryan Bruner; Patrick Cervini; Thomas Atwell; Greg Knoll; Bradley C Leibovich
Journal:  Can Urol Assoc J       Date:  2013 May-Jun       Impact factor: 1.862

3.  Changing trends in surgical management of renal tumours from 2000 to 2016: a nationwide study of Medicare claims data.

Authors:  Stephen Ali; Thomas Ahn; Nathan Papa; Marlon Perera; Patrick Teloken; Geoffrey Coughlin; Simon T Wood; Matthew J Roberts
Journal:  ANZ J Surg       Date:  2019-09-02       Impact factor: 1.872

4.  Incidental finding of renal masses at unenhanced CT: prevalence and analysis of features for guiding management.

Authors:  Stacy D O'Connor; Perry J Pickhardt; David H Kim; M Raquel Oliva; Stuart G Silverman
Journal:  AJR Am J Roentgenol       Date:  2011-07       Impact factor: 3.959

Review 5.  Current applications of three-dimensional printing in urology.

Authors:  Michael Y Chen; Jacob Skewes; Mathilde Desselle; Cynthia Wong; Maria A Woodruff; Prokar Dasgupta; Nicholas J Rukin
Journal:  BJU Int       Date:  2019-11-06       Impact factor: 5.588

Review 6.  Small renal masses progressing to metastases under active surveillance: a systematic review and pooled analysis.

Authors:  Marc C Smaldone; Alexander Kutikov; Brian L Egleston; Daniel J Canter; Rosalia Viterbo; David Y T Chen; Michael A Jewett; Richard E Greenberg; Robert G Uzzo
Journal:  Cancer       Date:  2011-07-15       Impact factor: 6.860

7.  Maximum tumor diameter is not an accurate predictor of renal cell carcinoma tumor volume.

Authors:  David D Thiel; Jacob Jorns; Christine M Lohse; John C Cheville; R Houston Thompson; Alexander S Parker
Journal:  Scand J Urol       Date:  2013-07-24       Impact factor: 1.612

8.  Three-dimensional virtual imaging of renal tumours: a new tool to improve the accuracy of nephrometry scores.

Authors:  Francesco Porpiglia; Daniele Amparore; Enrico Checcucci; Matteo Manfredi; Ilaria Stura; Giuseppe Migliaretti; Riccardo Autorino; Vincenzo Ficarra; Cristian Fiori
Journal:  BJU Int       Date:  2019-09-27       Impact factor: 5.588

9.  Gross tumor volume segmentation for head and neck cancer radiotherapy using deep dense multi-modality network.

Authors:  Zhe Guo; Ning Guo; Kuang Gong; Shun'an Zhong; Quanzheng Li
Journal:  Phys Med Biol       Date:  2019-10-16       Impact factor: 3.609

10.  A comparison of radiologic tumor volume and pathologic tumor volume in renal cell carcinoma (RCC).

Authors:  See Min Choi; Don Kyoung Choi; Tae Heon Kim; Byong Chang Jeong; Seong Il Seo; Seong Soo Jeon; Hyun Moo Lee; Han-Yong Choi; Hwang Gyun Jeon
Journal:  PLoS One       Date:  2015-03-23       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.