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. 2021 Apr;34(2):351-356.
doi: 10.1007/s10278-020-00416-z. Epub 2021 Feb 9.

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

Michael Y Chen  1   2   3 , Maria A Woodruff  4 , Boon Kua  5 , Nicholas J Rukin  6   4
Affiliations

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

Michael Y Chen et al. J Digit Imaging. 2021 Apr.

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.

Keywords: Diagnosis; Organ volume; Prognosis; Renal cancer.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1
a CT scan of superior pole left renal tumour with threshold density values adjusted to between − 46 and 159 Hounsfeld units (HU); b MRI scan of left midpole renal tumour with threshold density values adjusted to between 182 and 571 Gy value (GV). These values can be adjusted as needed with visual feedback. The green and red crosshairs are centred on the renal tumour in each image
Fig. 2
Fig. 2
Highlighting the tumour in axial, coronal and sagittal planes (red) with the 3D interpolation tool creates a 3D digital model in combination with the threshold density information creates a digital 3D model of the tumour (green) from the CT scan
Fig. 3
Fig. 3
Bland-Altman plots for RSV and REV when compared to PEV
See this image and copyright information in PMC

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