3D Ultrasound versus Computed Tomography for Tumor Volume Measurement Compared to Gross Pathology-A Pilot Study on an Animal Model

Fatemeh Makouei, Caroline Ewertsen, Tina Klitmøller Agander, Mikkel Vestergaard Olesen, Bente Pakkenberg, Tobias Todsen, Fatemeh Makouei, Caroline Ewertsen, Tina Klitmøller Agander, Mikkel Vestergaard Olesen, Bente Pakkenberg, Tobias Todsen

Abstract

The margin of the removed tumor in cancer surgery has an important influence on survival. Adjuvant treatments, prognostic complications, and financial costs are required when the pathologist observes a close/positive surgical margin. Ex vivo imaging of resected cancer tissue has been suggested for margin assessment, but traditional cross-sectional imaging is not optimal in a surgical setting. Instead, three-dimensional (3D) ultrasound is a portable, high-resolution, and low-cost method to use in the operation room. In this study, we aimed to investigate the accuracy of 3D ultrasound versus computed tomography (CT) to measure the tumor volume in an animal model compared to gross pathology assessment. The specimen was formalin fixated before systematic slicing. A slice-by-slice area measurement was performed to compare the accuracy of the 3D ultrasound and CT techniques. The tumor volume measured by pathological assessment was 980.2 mm3. The measured volume using CT was 890.4 ± 90 mm3, and the volume using 3D ultrasound was 924.2 ± 96 mm3. The correlation coefficient for CT was 0.91 and that for 3D ultrasound was 0.96. Three-dimensional ultrasound is a feasible and accurate modality to measure the tumor volume in an animal model. The accuracy of tumor delineation on CT depends on the soft tissue contrast.

Keywords: 3D ultrasound imaging; animal model; computed tomography; ex vivo volume analysis; tumor volume.

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Three-dimensional ultrasound imaging of the specimen. A holder is used to keep the probe at the desired position. The height of the probe front-face in relation to the specimen surface is adjusted using the yellow elongators.
Figure 2
Figure 2
Slicing of the specimen using a specific device that allows for thin and parallel cutting.
Figure 3
Figure 3
An example of the correlation between slices for gross pathology assessment and corresponding imaging. (a) Specimen slice, (b) corresponding slice on 3D ultrasound image, (c) corresponding slice on CT image, (d) corresponding slice on segmentation, and (e) 3D segmentation of the animal model.
Figure 3
Figure 3
An example of the correlation between slices for gross pathology assessment and corresponding imaging. (a) Specimen slice, (b) corresponding slice on 3D ultrasound image, (c) corresponding slice on CT image, (d) corresponding slice on segmentation, and (e) 3D segmentation of the animal model.
Figure 4
Figure 4
Area measurement at parallel equally distanced planes corresponding to the pathological slices. The dashed blue line is the result of the pathological assessment, and the shaded gray area is the standard deviation of the three measurements. (a) 3D ultrasound results compared to the pathological assessment. The solid red line is the mean area at each slice obtained by 3D ultrasound. (b) CT results compared to the pathological assessment. The solid purple line is the mean area at each slice measured by CT.
Figure 5
Figure 5
Paired t-test for statistical evaluation of the CT and 3D ultrasound compared to gross pathology. ns stands for non-significant, and * stands for significant.

References

    1. Heidkamp J., Weijs W.L.J., Grunsven A.C.H.V.E., Vries I.D.L., Maas M.C., Rovers M.M., Fütterer J.J., Steens S.C.A., Takes R.P. Assessment of surgical tumor-free resection margins in fresh squamous-cell carcinoma resection specimens of the tongue using a clinical MRI system. Head Neck. 2020;42:2039–2049. doi: 10.1002/hed.26125.
    1. Steens S.C.A., Bekers E.M., Weijs W.L.J., Litjens G.J.S., Veltien A., Maat A., Broek G.B.V.D., van der Laak J.A.W.M., Fütterer J.J., van der Kaa C.A.H., et al. Evaluation of tongue squamous cell carcinoma resection margins using ex-vivo MR. Int. J. Comput. Assist. Radiol. Surg. 2017;12:821–828. doi: 10.1007/s11548-017-1524-6.
    1. Rogers S., Carreira J., Thompson R., Morais A., Miller C., Wein W., Ghosh J., McCollum C. An Ex Vivo Evaluation of Tomographic 3-D Ultrasound, B-Mode Ultrasound, CT And MR Imaging to Measure Artery Diameter, Length and Wall Volume. Ultrasound Med. Biol. 2019;45:2819–2829. doi: 10.1016/j.ultrasmedbio.2019.07.002.
    1. Stadler A., Schima W., Prager G., Homolka P., Heinz G., Saini S., Eisenhuber E., Niederle B. CT Density Measurements for Characterization of Adrenal Tumors Ex Vivo: Variability Among Three CT Scanners. Am. J. Roentgenol. 2004;182:671–675. doi: 10.2214/ajr.182.3.1820671.
    1. de Koning K.J., Koppes S.A., de Bree R., Dankbaar J.W., Willems S.M., van Es R.J., Noorlag R. Feasibility study of ultrasound-guided resection of tongue cancer with immediate specimen examination to improve margin control—Comparison with conventional treatment. Oral Oncol. 2021;116:105249. doi: 10.1016/j.oraloncology.2021.105249.
    1. Tang R., Buckley J.M., Fernandez L., Coopey S., Aftreth O., Michaelson J., Saksena M., Lei L., Specht M., Gadd M., et al. Micro-computed tomography (Micro-CT): A novel approach for intraoperative breast cancer specimen imaging. Breast Cancer Res. Treat. 2013;139:311–316. doi: 10.1007/s10549-013-2554-6.
    1. Nakamura S., Mori K., Iwano S., Kawaguchi K., Fukui T., Hakiri S., Ozeki N., Oda M., Yokoi K. Micro-Computed tomography images of lung adenocarcinoma: Detection of lepidic growth patterns. Nagoya J. Med. Sci. 2020;82:25–31. doi: 10.18999/nagjms.82.1.25.
    1. Neubauer C., Yilmaz J.S., Bronsert P., Pichotka M., Bamberg F., Windfuhr-Blum M., Erbes T., Neubauer J. Accuracy of cone-beam computed tomography, digital mammography and digital breast tomosynthesis for microcalcifications and margins to microcalcifications in breast specimens. Sci. Rep. 2022;12:17639. doi: 10.1038/s41598-022-21616-3.
    1. de Koning K.J., van Es R.J., Klijn R.J., Breimer G.E., Dankbaar J.W., Braunius W.W., van Cann E.M., Dieleman F.J., Rijken J.A., Tijink B.M., et al. Application and accuracy of ultrasound-guided resections of tongue cancer. Oral Oncol. 2022;133:106023. doi: 10.1016/j.oraloncology.2022.106023.
    1. de Koning S.B., Karakullukcu M., Lange C., Schreuder W., Karssemakers L., Ruers T. Ultrasound aids in intraoperative assessment of deep resection margins of squamous cell carcinoma of the tongue. Br. J. Oral Maxillofac. Surg. 2020;58:285–290. doi: 10.1016/j.bjoms.2019.11.013.
    1. Nulent T.J.K., Noorlag R., Van Cann E.M., Pameijer F.A., Willems S.M., Yesuratnam A., Rosenberg A.J., de Bree R., van Es R.J. Intraoral ultrasonography to measure tumor thickness of oral cancer: A systematic review and meta-analysis. Oral Oncol. 2018;77:29–36. doi: 10.1016/j.oraloncology.2017.12.007.
    1. Pradipta A.R., Tanei T., Morimoto K., Shimazu K., Noguchi S., Tanaka K. Emerging Technologies for Real-Time Intraoperative Margin Assessment in Future Breast-Conserving Surgery. Adv. Sci. 2020;7:1901519. doi: 10.1002/advs.201901519.
    1. Huang Q., Zeng Z. A Review on Real-Time 3D Ultrasound Imaging Technology. BioMed Res. Int. 2017;2017:6027029. doi: 10.1155/2017/6027029.
    1. Kim S.C., Kim J.H., Choi S.H., Yun T.J., Wi J.Y., Kim S.A., Sun H.Y., Ryoo I., Park S.-W., Sohn C.-H. Off-Site evaluation of three-dimensional ultrasound for the diagnosis of thyroid nodules: Comparison with two-dimensional ultrasound. Eur. Radiol. 2016;26:3353–3360. doi: 10.1007/s00330-015-4193-2.
    1. Chung D., Bandarkar A., Rana S., Tabrizi P.R., Preciado D., Jago J., Linguraru M.G., Reilly B.K. Pilot study of the potential of 3D ultrasound to measure tonsillar volume and hypertrophy. Int. J. Pediatr. Otorhinolaryngol. 2019;126:109612. doi: 10.1016/j.ijporl.2019.109612.
    1. Malago R., D’Onofrio M., Ferdeghini M., Mantovani W., Colato C., Brazzarola P., Motton M., Mucelli R.P. Thyroid volumetric quantification: Comparative evaluation between conventional and volumetric ultrasonography. J. Ultrasound Med. 2008;27:1727–1733. doi: 10.7863/jum.2008.27.12.1727.
    1. Inoue T., Tamaki Y., Sato Y., Nakamoto M., Tamura S., Tanji Y., Taguchi T., Noguchi S. Three-Dimensional ultrasound imaging of breast cancer by a real-time intraoperative navigation system. Breast Cancer. 2005;12:122–129. doi: 10.2325/jbcs.12.122.
    1. Yushkevich P.A., Piven J., Hazlett H.C., Smith R.G., Ho S., Gee J.C., Gerig G. User-Guided 3D active contour segmentation of anatomical structures: Significantly improved efficiency and reliability. Neuroimage. 2006;31:1116–1128. doi: 10.1016/j.neuroimage.2006.01.015.
    1. Henderson A. ParaView Guide, A Parallel Visualization Application. Kitware Inc.; New York, NY, USA: 2007.
    1. The MathWorks, Inc.; Natick, MA, USA: 2021.

Source: PubMed

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