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Diffusion volume (DV) measurement in endometrial and cervical cancer: A new MRI parameter in the evaluation of the tumor grading and the risk classification (360 views) (PDF restricted 61 views)

Mainenti PP, Pizzuti LM, Segreto S, Comerci M, Fronzo SD, Romano F, Crisci V, Smaldone M, Laccetti E, Storto G, Alfano B, Maurea S, Salvatore M, Pace L

Eur J Radiol (ISSN: 0720-048x, 1872-7727electronic), 2016 Jan; 85(1): 113-124.

Abstract

Purpose: A new MRI parameter representative of active tumor burden is proposed: diffusion volume (DV), defined as the sum of all the voxels within a tumor with apparent diffusion coefficient (ADC) values within a specific range.
The aims of the study were: (a) to calculate DV on ADC maps in patients with cervical/endometrial cancer; (b) to correlate DV with histological grade (G) and risk classification; (c) to evaluate intra/inter-observer agreement of DV calculation.
Materials and methods: Fifty-three patients with endometrial (n = 28) and cervical (n = 25) cancers under-went pelvic MRI with DWI sequences. Both endometrial and cervical tumors were classified on the basis of G (G1/G2/G3) and FIGO staging (low/medium/high-risk).
A semi-automated segmentation procedure was used to calculate the DV. A freehand closed ROI out-lined the whole visible tumor on the most representative slice of ADC maps defined as the slice with the maximum diameter of the solid neoplastic component. Successively, two thresholds were generated on the basis of the mean and standard deviation (SD) of the ADC values: lower threshold (LT = “mean minus three SD”) and higher threshold (HT = “mean plus one SD”). The closed ROI was expanded in 3D, including all the contiguous voxels with ADC values in the range LT-HT × 10–3 mm2/s.
A Kruskal–Wallis test was used to assess the differences in DV among G and risk groups. Intra-/inter-observer variability for DV measurement was analyzed according to the method of Bland and Altman and the intraclass-correlation–coefficient (ICC).
Results: DV values were significantly different among G and risk groups in both endometrial (p < 0.05) and cervical cancers (p ≤ 0.01). For endometrial cancer, DV of G1 (mean ± sd: 2.81 ± 3.21 cc) neoplasms were significantly lower than G2 (9.44 ± 9.58 cc) and G3 (11.96 ± 8.0 cc) ones; moreover, DV of low risk cancers (5.23 ± 8.0 cc) were significantly lower than medium (7.28 ± 4.3 cc) and high risk (14.7 ± 9.9 cc) ones.
For cervical cancer, DV of G1 (0.31 ± 0.13 cc) neoplasms was significantly lower than G3 (40.68 ± 45.65 cc) ones; moreover, DV of low risk neoplasms (6.98 ± 8.08 cc) was significantly lower than medium (21.7 ± 17.13 cc) and high risk (62.9 ± 51.12 cc) ones and DV of medium risk neoplasms was significantly lower than high risk ones.
The intra-/inter-observer variability for DV measurement showed an excellent correlation for both cancers (ICC ≥ 0.86).
Conclusions: DV is an accurate index for the assessment of G and risk classification of cervical/endometrial cancers with low intra-/inter-observer variability.



Affiliations ▼
*** IBB - CNR Affiliation

IBB CNR, Napoli, Italy

Dipartimento di Scienze Biomediche Avanzate, Sezione di Radiologia, Università di Napoli “Federico II”, Napoli, Italy

IRCCS CROB, Rionero in Vulture, Italy

IRCCS SDN, Napoli, Italy

Dipartimento di Medicina e Chirurgia, Università degli Studi di Salerno, Salerno, Italy

Details ▼
Impact factor: 2.16, 5-year impact factor: 2.304

Paper type: Journal Article,

Keywords: Mri, Dwi, Adc Maps, Diffusion Volume, Cervical Cancer, Endometrial Cancer, Adult, Aged, Article, Automation, Cancer Classification, Cancer Grading, Cancer Risk, Cancer Staging, Diffusion Weighted Imaging, Endometrium Cancer, Female, High Risk Population, Histopathology, Human, Kruskal Wallis Test, Major Clinical Study, Nuclear Magnetic Resonance Imaging, Priority Journal, Receiver Operating Characteristic, Uterine Cervix Cancer,

Url: http://dx.doi.org/10.1016/j.ejrad.2015.10.014

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[23] R. Fonti, M. Larobina, S. Del Vecchio, S. De Luca, R. Fabbricini, L. Catalano, et al., Metabolic tumor volume assessed by 18F-FDG PET/CT for the prediction of outcome in patients with multiple myeloma, J. Nucl. Med. 53 (12) (2012) 1829–1835.

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[27] A. Berkowitz, S. Basu, S. Srinivas, S. Sankaran, S. Schuster, A. Alavi, Determination of whole-body metabolic burden as a quantitative measure of disease activity in lymphoma: a novel approach with fluorodeoxyglucose-PET, Nucl. Med. Commun. 29 (6) (2008) 521–526.

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[29] G. Storto, E. Nicolai, M. Salvatore, [18F]FDG-PET-CT for early monitoring of tumor response: when and why, Q. J. Nucl. Med. Mol. Imaging 53 (2) (2009) 167–180.

[30] J.R. Olsen, J. Esthappan, T. DeWees, V.R. Narra, F. Dehdashti, B.A. Siegel, et al., Tumor volume and subvolume concordance between FDG-PET/CT and diffusion-weighted MRI for squamous cell carcinoma of the cervix, J. Magn. Reson. Imaging 37 (2) (2013) 431–434.

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[32] M. Uhl, U. Saueressig, G. Koehler, U. Kontny, C. Niemeyer, W. Reichardt, et al., Evaluation of tumour necrosis during chemotherapy with diffusion-weighted MR imaging: preliminary results in osteosarcomas, Pediatr. Radiol. 36 (12) (2006) 1306–1311.

[33] M.Y. Choi, K.M. Lee, J.K. Chung, D.S. Lee, J.M. Jeong, J.G. Park, et al., Correlation between serum CEA level and metabolic volume as determined by FDG PET in postoperative patients with recurrent colorectal cancer, Ann. Nucl. Med. 19 (2) (2005) 123–129.

[34] E.H. Dibble, A.C. Alvarez, M.T. Truong, G. Mercier, E.F. Cook, R.M. Subramaniam, 18F-FDG metabolic tumor volume and total glycolytic activity of oral cavity and oropharyngeal squamous cell cancer: adding value to clinical staging, J. Nucl. Med. 53 (5) (2012) 709–715.

[35] P. Sridhar, G. Mercier, J. Tan, M.T. Truong, B. Daly, R.M. Subramaniam, FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors, AJR Am. J. Roentgenol. 202 (5) (2014) 1114–1119.

[36] N. Withofs, C. Bernard, C. Van der Rest, P. Martinive, M. Hatt, S. Jodogne, et al., FDG PET/CT for rectal carcinoma radiotherapy treatment planning: comparison of functional volume delineation algorithms and clinical challenges, J. Appl. Clin. Med. Phys. 15 (5) (2014) 4696.

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[38] D.M. Lambregts, G.L. Beets, M. Maas, L. Curvo-Semedo, A.G. Kessels, T. Thywissen, et al., Tumour ADC measurements in rectal cancer: effect of ROI methods on ADC values and interobserver variability, Eur. Radiol. 21 (12) (2011) 2567–2574.

Koyama, T., Tamai, K., Togashi, K., Staging of carcinoma of the uterine cervix and endometrium (2007) Eur. Radiol., 17 (8), pp. 2009-201

Rechichi, G., Galimberti, S., Signorelli, M., Perego, P., Valsecchi, M.G., Sironi, S., Myometrial invasion in endometrial cancer: Diagnostic performance of diffusione weighted MR imaging at 1.5-T (2010) Eur. Radiol., 20 (3), pp. 754-762

Andreano, A., Rechichi, G., Rebora, P., Sironi, S., Valsecchi, M.G., Galimberti, S., MR diffusion imaging for preoperative staging of myometrial invasion in patients with endometrial cancer: A systematic review and meta-analysis (2014) Eur. Radiol, 24 (6), pp. 1327-1338

Rowley, H.A., Grant, P.E., Roberts, T.P., Diffusion MR imaging: Theory and applications (1999) Neuroimaging Clin. N. Am., 9 (2), pp. 343-361

Koh, D.M., Collins, D.J., Diffusion-weighted MRI in the body: Applications and challenges in oncology (2007) AJR Am. J. Roentgenol., 188 (6), pp. 1622-1635

Naganawa, S., Sato, C., Kumada, H., Ishigaki, T., Miura, S., Takizawa, O., Apparent diffusion coefficient in cervical cancer of the uterus: Comparison with the normal uterine cervix (2005) Eur. Radiol., 15 (1), pp. 71-78

McVeigh, P.Z., Syed, A.M., Milosevic, M., Fyles, A., Haiderd, M.A., Diffusion-weighted MRI in cervical cancer (2008) Eur. Radiol., 18 (5), pp. 1058-1064

Sala, E., Rockall, A., Rangarajanc, D., Kubik-Huch, R.A., The role of dynamic contrast-enhanced and diffusion weighted magnetic resonance imaging in the female pelvis (2010) Eur. J. Radiol., 76 (3), pp. 367-385

Punwani, S., Diffusion weighted imaging of female pelvic cancers: Concepts and clinical applications (2011) Eur. J. Radiol., 78 (1), pp. 21-29

Fujii, S., Matsusue, E., Kigawa, J., Sato, S., Kanasaki, Y., Nakanishi, J., Diagnostic accuracy of the apparent diffusion coefficient in differentiating benign from malignant uterine endometrial cavity lesions: Initial results (2008) Eur. Radiol., 18 (2), pp. 384-389

Shen, S.H., Chiou, Y.Y., Wang, J.H., Yen, M.S., Lee, R.C., Lai, C.R., Diffusion-weighted single-shot echo-planar imaging with parallel technique in assessment of endometrial cancer (2008) AJR Am. J. Roentgenol., 190 (2), pp. 481-488

Tamai, K., Koyama, T., Saga, T., Umeoka, S., Mikami, Y., Fujii, S., Diffusion weighted MR imaging of uterine endometrial cancer (2007) J. Magn. Reson. Imaging, 26 (3), pp. 682-687

Bharwani, N., Miquel, M.E., Sahdev, A., Narayanan, P., Malietzis, G., Reznek, R.H., Diffusion-weighted imaging in the assessment of tumour grade in endometrial cancer (2011) Br. J. Radiol., 84 (1007), pp. 997-1004

Inada, Y., Matsuki, M., Nakai, G., Tatsugami, F., Tanikake, M., Narabayashi, I., Body diffusion weighted MR imaging of uterine endometrial cancer: Is it helpful in the detection of cancer in non enhanced MR imaging? (2009) Eur. J. Radiol., 70 (1), pp. 122-127

Cao, K., Gao, M., Sun, Y.S., Li, Y.L., Sun, Y., Gao, Y.N., Apparent diffusion coefficient of diffusion weighted MRI in endometrial carcinoma-Relationship with local invasiveness (2012) Eur. J. Radiol., 81 (8), pp. 1926-1930

Beddy, P., O'Neil, A.C., Yamamoto, A.K., Addley, H.C., Reinhold, C., Sala, E., FIGO staging system for endometrial cancer: Added benefits of MR imaging (2012) Radiographics, 32 (1), pp. 241-254

Downey, K., Riches, S.F., Morgan, V.A., Giles, S.L., Attygalle, A.D., Ind, T.E., Relationship between imaging biomarkers of stage i cervical cancer and poor-prognosis histologic features: Quantitative histogram analysis of diffusion-weighted MR images (2013) AJR Am. J. Roentgenol., 200 (2), pp. 314-320

Kuang, F., Ren, J., Zhong, Q., Liyuan, F., Huan, Y., Chen, Z., The value of apparent diffusion coefficient in the assessment of cervical cancer (2013) Eur. Radiol., 23 (4), pp. 1050-1058

Bos, R., Van Der Hoeven, J.J., Van Der Wall, E., Van Der Groep, P., Van Diest, P.J., Comans, E.F., Biologic correlates of (18) fluorodeoxyglucose uptake in human breast cancer measured by positron emission tomography (2002) J. Clin. Oncol., 20 (2), pp. 379-387

Higashi, T., Tamaki, N., Torizuka, T., Nakamoto, Y., Sakahara, H., Kimura, T., FDG uptake, GLUT-1, glucose transporter and cellularity in human pancreatic tumors (1998) J. Nucl. Med., 39 (10), pp. 1727-1735

Ito, K., Kato, T., Ohta, T., Fluorine-18 fluoro-2-deoxyglucose positron emission tomography in recurrent rectal cancer: Relation to tumour size and cellularity (1996) Eur. J. Nucl. Med., 23 (10), pp. 1372-1377

Fonti, R., Larobina, M., Del Vecchio, S., De Luca, S., Fabbricini, R., Catalano, L., Metabolic tumor volume assessed by 18F-FDG PET/CT for the prediction of outcome in patients with multiple myeloma (2012) J. Nucl. Med., 53 (12), pp. 1829-1835

Colombo, N., Preti, E., Landoni, F., Carinelli, S., Colombo, A., Marini, C., Endometrial cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow up (2011) Ann. Oncol., 22, pp. 35-39. , Suppl 7: vii

Freeman, S.J., Aly, A.M., Kataoka, M.Y., Addley, H.C., Reinhold, C., Sala, E., The revised FIGO staging system for uterine malignancies: Implications for MR imaging (2012) Radiographics, 32 (6), pp. 1805-1827

Colombo, N., Carinelli, S., Colombo, A., Marini, C., Rollo, D., Sessa, C., Cervical cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up (2012) Ann. Oncol., 23, pp. 27-32. , Suppl 7: vii

Berkowitz, A., Basu, S., Srinivas, S., Sankaran, S., Schuster, S., Alavi, A., Determination of whole-body metabolic burden as a quantitative measure of disease activity in lymphoma: A novel approach with fluorodeoxyglucose-PET (2008) Nucl. Med. Commun., 29 (6), pp. 521-526

Chung, H.H., Kim, J.W., Han, K.H., Eo, J.S., Kang, K.W., Park, N.H., Prognostic value of metabolic tumor volume measured by FDG-PET/CT in patients with cervical cancer (2011) Gynecol. Oncol., 120 (2), pp. 270-274

Storto, G., Nicolai, E., Salvatore, M., [18F]FDG-PET-CT for early monitoring of tumor response: When and why (2009) Q. J. Nucl. Med. Mol. Imaging, 53 (2), pp. 167-180

Olsen, J.R., Esthappan, J., DeWees, T., Narra, V.R., Dehdashti, F., Siegel, B.A., Tumor volume and subvolume concordance between FDG-PET/CT and diffusion-weighted MRI for squamous cell carcinoma of the cervix (2013) J. Magn. Reson. Imaging, 37 (2), pp. 431-434

Sun, H., Xin, J., Zhang, S., Guo, Q., Lu, Y., Zhai, W., Anatomical and functional volume concordance between FDG PET, and T2 and diffusion-weighted MRI for cervical cancer: A hybrid PET/MR study (2014) Eur. J. Nucl. Med. Mol. Imaging, 41 (5), pp. 898-905

Uhl, M., Saueressig, U., Koehler, G., Kontny, U., Niemeyer, C., Reichardt, W., Evaluation of tumour necrosis during chemotherapy with diffusion-weighted MR imaging: Preliminary results in osteosarcomas (2006) Pediatr. Radiol., 36 (12), pp. 1306-1311

Choi, M.Y., Lee, K.M., Chung, J.K., Lee, D.S., Jeong, J.M., Park, J.G., Correlation between serum CEA level and metabolic volume as determined by FDG PET in postoperative patients with recurrent colorectal cancer (2005) Ann. Nucl. Med., 19 (2), pp. 123-129

Dibble, E.H., Alvarez, A.C., Truong, M.T., Mercier, G., Cook, E.F., Subramaniam, R.M., 18F-FDG metabolic tumor volume and total glycolytic activity of oral cavity and oropharyngeal squamous cell cancer: Adding value to clinical staging (2012) J. Nucl. Med., 53 (5), pp. 709-715

Sridhar, P., Mercier, G., Tan, J., Truong, M.T., Daly, B., Subramaniam, R.M., FDG PET metabolic tumor volume segmentation and pathologic volume of primary human solid tumors (2014) AJR Am. J. Roentgenol., 202 (5), pp. 1114-1119

Withofs, N., Bernard, C., Van Der Rest, C., Martinive, P., Hatt, M., Jodogne, S., FDG PET/CT for rectal carcinoma radiotherapy treatment planning: Comparison of functional volume delineation algorithms and clinical challenges (2014) J. Appl. Clin. Med. Phys., 15 (5), p. 4696

Zhang, S., Xin, J., Guo, Q., Ma, J., Ma, Q., Sun, H., Comparison of tumor volume between PET and MRI in cervical cancer with hybrid PET/MR (2014) Int. J. Gynecol. Cancer, 24 (4), pp. 744-750

Lambregts, D.M., Beets, G.L., Maas, M., Curvo-Semedo, L., Kessels, A.G., Thywissen, T., Tumour ADC measurements in rectal cancer: Effect of ROI methods on ADC values and interobserver variability (2011) Eur. Radiol., 21 (12), pp. 2567-2574


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3 Records (1 excluding Abstracts and Conferences).
Total impact factor: 1.735 (1.735 excluding Abstracts and Conferences).
Total 5-year impact factor: 1.493 (1.493 excluding Abstracts and Conferences).



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