Top

Published in:

01-07-2014 | Oncology

Evaluating the agreement between tumour volumetry and the estimated volumes of tumour lesions using an algorithm

Authors: Ruediger P. Laubender, Julia Lynghjem, Melvin D’Anastasi, Volker Heinemann, Dominik P. Modest, Ulrich R. Mansmann, Ute Sartorius, Michael Schlichting, Anno Graser

Published in: European Radiology | Issue 7/2014

Abstract

Objectives

To evaluate the agreement between tumour volume derived from semiautomated volumetry (SaV) and tumor volume defined by spherical volume using longest lesion diameter (LD) according to Response Evaluation Criteria In Solid Tumors (RECIST) or ellipsoid volume using LD and longest orthogonal diameter (LOD) according to World Health Organization (WHO) criteria.

Materials and methods

Twenty patients with metastatic colorectal cancer from the CIOX trial were included. A total of 151 target lesions were defined by baseline computed tomography and followed until disease progression. All assessments were performed by a single reader. A variance component model was used to compare the three volume versions.

Results

There was a significant difference between the SaV and RECIST-based tumour volumes. The same model showed no significant difference between the SaV and WHO-based volumes. Scatter plots showed that the RECIST-based volumes overestimate lesion volume. The agreement between the SaV and WHO-based relative changes in tumour volume, evaluated by intraclass correlation, showed nearly perfect agreement.

Conclusions

Estimating the volume of metastatic lesions using both the LD and LOD (WHO) is more accurate than those based on LD only (RECIST), which overestimates lesion volume. The good agreement between the SaV and WHO-based relative changes in tumour volume enables a reasonable approximation of three-dimensional tumour burden.

Key Points

• Tumour response in patients undergoing chemotherapy is assessed using CT images

• Measurements are based on RECIST (unidimensional)-based or WHO (bidimensional)-based criteria

• We calculated tumour volume from bidimensional target lesion measurements

• This formula provides good tumour volume approximation, based on semiautomated volumetry

Eisenhauer EA, Therasse P, Bogaerts J et al (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 45:228–247PubMedCrossRef

World Health Organization (1979) WHO handbook for reporting results of cancer treatment. World Health Organization, Geneva

Maitland ML (2010) Volumes to learn: advancing therapeutics with innovative computed tomography image data analysis. Clin Cancer Res 16:4493–4495PubMedCentralPubMedCrossRef

Altorki N, Lane ME, Bauer T et al (2010) Phase II proof-of-concept study of pazopanib monotherapy in treatment-naive patients with stage I/II resectable non-small-cell lung cancer. J Clin Oncol 28:3131–3137PubMedCrossRef

Zhao B, Oxnard GR, Moskowitz CS et al (2010) A pilot study of volume measurement as a method of tumor response evaluation to aid biomarker development. Clin Cancer Res 16:4647–4653PubMedCentralPubMedCrossRef

Zhao B, Schwartz LH, Moskowitz CS, Ginsberg MS, Rizvi NA, Kris MG (2006) Lung cancer: computerized quantification of tumor response–initial results. Radiology 241:892–898PubMedCrossRef

Fabel M, Bolte H, von Tengg-Kobligk H et al (2011) Semi-automated volumetric analysis of lymph node metastases during follow-up–initial results. Eur Radiol 21:683–692PubMedCrossRef

Fabel M, von Tengg-Kobligk H, Giesel FL et al (2008) Semi-automated volumetric analysis of lymph node metastases in patients with malignant melanoma stage III/IV–a feasibility study. Eur Radiol 18:1114–1122PubMedCrossRef

Revel MP, Bissery A, Bienvenu M, Aycard L, Lefort C, Frija G (2004) Are two-dimensional CT measurements of small noncalcified pulmonary nodules reliable? Radiology 231:453–458PubMedCrossRef

10.

Schwartz LH, Curran S, Trocola R et al (2007) Volumetric 3D CT analysis – an early predictor of response to therapy. J Clin Oncol 25:4576CrossRef

11.

Moosmann N, von Weikersthal LF, Vehling-Kaiser U et al (2011) Cetuximab plus capecitabine and irinotecan compared with cetuximab plus capecitabine and oxaliplatin as first-line treatment for patients with metastatic colorectal cancer: AIO KRK-0104—a randomized trial of the German AIO CRC study group. J Clin Oncol 29:1050–1058PubMedCrossRef

12.

Bland JM, Altman DG (1986) Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1:307–310PubMedCrossRef

13.

Carstensen B, Simpson J, Gurrin LC (2008) Statistical models for assessing agreement in method comparison studies with replicate measurements. Int J Biostat 4, Article 16

14.

Bland JM, Altman DG (1999) Measuring agreement in method comparison studies. Stat Methods Med Res 8:135–160PubMedCrossRef

15.

Cleveland WS (1979) Robust locally weighted regression and smoothing scatterplots. J Am Stat Assoc 74:829–836CrossRef

16.

Ercolani G, Grazi GL, Ravaioli M et al (2002) Liver resection for multiple colorectal metastases: influence of parenchymal involvement and total tumor volume, vs number or location, on long-term survival. Arch Surg 137:1187–1192PubMedCrossRef

17.

Piessevaux H, Buyse M, De Roock W et al (2009) Radiological tumor size decrease at week 6 is a potent predictor of outcome in chemorefractory metastatic colorectal cancer treated with cetuximab (BOND trial). Ann Oncol 20:1375–1382PubMedCrossRef

18.

Piessevaux H, Buyse M, Schlichting M et al (2013) Use of early tumor shrinkage to predict long-term outcome in metastatic colorectal cancer treated with cetuximab. J Clin Oncol 31:3764–3775PubMedCrossRef

19.

Suzuki C, Blomqvist L, Sundin A et al (2012) The initial change in tumor size predicts response and survival in patients with metastatic colorectal cancer treated with combination chemotherapy. Ann Oncol 23:948–954PubMedCrossRef

20.

Levine ZH, Galloway BR, Peskin AP, Heussel CP, Chen JJ (2011) Tumor volume measurement errors of RECIST studied with ellipsoids. Med Phys 38:2552–2557PubMedCrossRef

Title: Evaluating the agreement between tumour volumetry and the estimated volumes of tumour lesions using an algorithm
Authors: Ruediger P. Laubender
Julia Lynghjem
Melvin D’Anastasi
Volker Heinemann
Dominik P. Modest
Ulrich R. Mansmann
Ute Sartorius
Michael Schlichting
Anno Graser
Publication date: 01-07-2014
Publisher: Springer Berlin Heidelberg
Published in: European Radiology / Issue 7/2014
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-014-3195-9

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Evaluating the agreement between tumour volumetry and the estimated volumes of tumour lesions using an algorithm

Abstract

Objectives

Materials and methods

Results

Conclusions

Key Points

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Objectives

Materials and methods

Results

Conclusions

Key Points

Please log in to get access to this content

Other articles of this Issue 7/2014

Application of localized 31P MRS saturation transfer at 7 T for measurement of ATP metabolism in the liver: reproducibility and initial clinical application in patients with non-alcoholic fatty liver disease

Hepatic magnetic resonance imaging with T2* mapping of ovariectomized rats: correlation between iron overload and postmenopausal osteoporosis

Effect of radiation dose level on the detectability of pulmonary nodules in chest tomosynthesis

Cardiac valve calcifications on low-dose unenhanced ungated chest computed tomography: inter-observer and inter-examination reliability, agreement and variability

Topogram-based automated selection of the tube potential and current in thoraco-abdominal trauma CT – a comparison to fixed kV with mAs modulation alone

Pixel-by-pixel analysis of DCE-MRI curve shape patterns in knees of active and inactive juvenile idiopathic arthritis patients