Diffusion volume (DV) measurement in endometrial and cervical cancer: A new MRI parameter in the evaluation of the tumor grading and the risk classification (884 views) (PDF restricted 235 views)
Eur J Radiol (ISSN: 0720-048x, 0720-048xlinking), 2016 Jan; 85(1): 113-124.
Export to BibTeX Export to EndNote
Paper type: Journal Article,
Impact factor: 2.462, 5-year impact factor: 2.507
Url: http://dx.doi.org/10.1016/j.ejrad.2015.10.014
Keywords: Mri, Dwi, Adc Maps, Diffusion Volume, Cervical Cancer, Endometrial Cancer, Adult, Aged, Segmentation, 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, Analysis Of Variance, Diffusion Magnetic Resonance Imaging Methods, Endometrial Neoplasms Pathology, Image Interpretation, Computer-Assisted, Middle Aged, Neoplasm Grading, Observer Variation, Sensitivity And Specificity, Tumor Burden, Uterine Cervical Neoplasms Pathology,
Affiliations:
*** IBB - CNR ***
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
References:
[1] T. Koyama, K. Tamai, K. Togashi, Staging of carcinoma of the uterine cervix and endometrium, Eur. Radiol. 17 (8) (2007) 2009–2019.
[2] G. Rechichi, S. Galimberti, M. Signorelli, P. Perego, M.G. Valsecchi, S. Sironi, Myometrial invasion in endometrial cancer: diagnostic performance of diffusion weighted MR imaging at 1.5-T, Eur. Radiol. 20 (3) (2010) 754–762.
[3] A. Andreano, G. Rechichi, P. Rebora, S. Sironi, M.G. Valsecchi, S. Galimberti, MR 24 (6) (2014) 1327–1338.
[4] H.A. Rowley, P.E. Grant, T.P. Roberts, Diffusion MR imaging: theory and applications, Neuroimaging Clin. N. Am. 9 (2) (1999) 343–361.
[5] D.M. Koh, D.J. Collins, Diffusion-weighted MRI in the body: applications and challenges in oncology, AJR Am. J. Roentgenol. 188 (6) (2007) 1622–1635.
[6] S. Naganawa, C. Sato, H. Kumada, T. Ishigaki, S. Miura, O. Takizawa, Apparent diffusion coefficient in cervical cancer of the uterus: comparison with the normal uterine cervix, Eur. Radiol. 15 (1) (2005) 71–78.
[7] P.Z. McVeigh, A.M. Syed, M. Milosevic, A. Fyles, M.A. Haiderd,Diffusion-weighted MRI in cervical cancer, Eur. Radiol. 18 (5) (2008) 1058–1064.
[8] E. Sala, A. Rockall, D. Rangarajanc, R.A. Kubik-Huch, The role of dynamic contrast-enhanced and diffusion weighted magnetic resonance imaging in the female pelvis, Eur. J. Radiol. 76 (3) (2010) 367–385.
[9] S. Punwani, Diffusion weighted imaging of female pelvic cancers: concepts and clinical applications, Eur. J. Radiol. 78 (1) (2011) 21–29.
[10] G. Rechichi, S. Galimberti, M. Signorelli, C.T. Franzesi, P. Perego, M.G. Valsecchi, et al., Endometrial cancer: correlation of apparent diffusion coefficient with tumor grade, depth of myometrial invasion, and presence of lymph node metastases, AJR Am. J. Roentgenol. 197 (1) (2011) 256–262.
[11] S. Fujii, E. Matsusue, J. Kigawa, S. Sato, Y. Kanasaki, J. Nakanishi, et al., Diagnostic accuracy of the apparent diffusion coefficient in differentiating benign from malignant uterine endometrial cavity lesions: initial results, Eur. Radiol. 18 (2) (2008) 384–389.
[12] S.H. Shen, Y.Y. Chiou, J.H. Wang, M.S. Yen, R.C. Lee, C.R. Lai, et al., echo-planar imaging with parallel technique in assessment of endometrial cancer, AJR Am. J. Roentgenol. 190 (2) (2008)
[13] K. Tamai, T. Koyama, T. Saga, S. Umeoka, Y. Mikami, S. Fujii, et al., Diffusion weighted MR imaging of uterine endometrial cancer, J. Magn. Reson. Imaging 26 (3) (2007) 682–687.
[14] N. Bharwani, M.E. Miquel, A. Sahdev, P. Narayanan, G. Malietzis, R.H. Reznek, et al., Diffusion-weighted imaging in the assessment of tumour grade in endometrial cancer, Br. J. Radiol. 84 (1007) (2011) 997–1004.
[15] Y. Inada, M. Matsuki, G. Nakai, F. Tatsugami, M. Tanikake, I. Narabayashi, et al., Body diffusion weighted MR imaging of uterine endometrial cancer: is it helpful in the detection of cancer in non enhanced MR imaging? Eur. J. Radiol. 70 (1) (2009) 122–127.
[16] K. Cao, M. Gao, Y.S. Sun, Y.L. Li, Y. Sun, Y.N. Gao, et al., Apparent diffusion coefficient of diffusion weighted MRI in endometrial carcinoma-Relationship with local invasiveness, Eur. J. Radiol. 81 (8) (2012) 1926–1930.
[17] P. Beddy, A.C. O’Neil, A.K. Yamamoto, H.C. Addley, C. Reinhold, E. Sala, fiGO staging system for endometrial cancer: added benefits of MR imaging,Radiographics 32 (1) (2012) 241–254.
[18] K. Downey, S.F. Riches, V.A. Morgan, S.L. Giles, A.D. Attygalle, T.E. Ind, et al., Relationship between imaging biomarkers of stage I cervical cancer and poor-prognosis histologic features: quantitative histogram analysis of diffusion-weighted MR images, AJR Am. J. Roentgenol. 200 (2) (2013) 314–320.
[19] F. Kuang, J. Ren, Q. Zhong, F. Liyuan, Y. Huan, Z. Chen, The value of apparent diffusion coefficient in the assessment of cervical cancer, Eur. Radiol. 23 (4) (2013) 1050–1058.
[20] R. Bos, J.J. van Der Hoeven, E. van Der Wall, P. van Der Groep, P.J. van Diest, E.F.Comans, et al., Biologic correlates of (18) fluorodeoxyglucose uptake in human breast cancer measured by positron emission tomography, J. Clin. Oncol. 20 (2) (2002) 379–387.
[21] T. Higashi, N. Tamaki, T. Torizuka, Y. Nakamoto, H. Sakahara, T. Kimura, et al.,FDG uptake, GLUT-1, glucose transporter and cellularity in human pancreatic tumors, J. Nucl. Med. 39 (10) (1998) 1727–1735.
[22] K. Ito, T. Kato, T. Ohta, et al., fluorine-18 fluoro-2-deoxyglucose positron emission tomography in recurrent rectal cancer: relation to tumour size and cellularity, Eur. J. Nucl. Med. 23 (10) (1996) 1372–1377.
[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.
[24] N. Colombo, E. Preti, F. Landoni, S. Carinelli, A. Colombo, C. Marini, et al., Endometrial cancer: ESMO clinical practice guidelines for diagnosis, treatment and follow up, Ann. Oncol. 22 (2011) 35–39, Suppl 7: vii.
[25] S.J. Freeman, A.M. Aly, M.Y. Kataoka, H.C. Addley, C. Reinhold, E. Sala, The revised fiGO staging system for uterine malignancies: implications for MR imaging, Radiographics 32 (6) (2012) 1805–1827.
[26] N. Colombo, S. Carinelli, A. Colombo, C. Marini, D. Rollo, C. Sessa, et al., Cervical cancer: ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up, Ann. Oncol. 23 (2012) 27–32, Suppl 7: vii.
[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.
[28] H.H. Chung, J.W. Kim, K.H. Han, J.S. Eo, K.W. Kang, N.H. Park, et al., Prognostic value of metabolic tumor volume measured by FDG-PET/CT in patients with cervical cancer, Gynecol. Oncol. 120 (2) (2011) 270–274.
[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.
[31] H. Sun, J. Xin, S. Zhang, Q. Guo, Y. Lu, W. Zhai, et al., Anatomical and functional volume concordance between FDG PET, and T2 and diffusion-weighted MRI for cervical cancer: a hybrid PET/MR study, Eur. J. Nucl. Med. Mol. Imaging 41 (5) (2014) 898–905.
[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.
[37] S. Zhang, J. Xin, Q. Guo, J. Ma, Q. Ma, H. Sun, Comparison of tumor volume between PET and MRI in cervical cancer with hybrid PET/MR, Int. J. Gynecol. Cancer 24 (4) (2014) 744–750.
[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.
[39] Koyama, T., Tamai, K., Togashi, K., Staging of carcinoma of the uterine cervix and endometrium (2007) Eur. Radiol., 17 (8), pp. 2009-201
[40] 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
[41] 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
[42] 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
[43] 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
[44] 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
[45] 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
[46] 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
[47] 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
[48] 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
[49] 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
[50] 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
[51] 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
[52] 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
[53] 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
[54] 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
[55] 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
[56] 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
[57] 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
[58] 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
[59] 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
[60] 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
[61] 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
[62] 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
[63] 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
[64] 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
[65] 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
[66] 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
[67] 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
[68] 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
[69] 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
[70] 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
[71] 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
[72] 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
[73] 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
Eur J Radiol (ISSN: 0720-048x, 0720-048xlinking), 2016 Jan; 85(1): 113-124.
Export to BibTeX Export to EndNote
Paper type: Journal Article,
Impact factor: 2.462, 5-year impact factor: 2.507
Url: http://dx.doi.org/10.1016/j.ejrad.2015.10.014
Keywords: Mri, Dwi, Adc Maps, Diffusion Volume, Cervical Cancer, Endometrial Cancer, Adult, Aged, Segmentation, 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, Analysis Of Variance, Diffusion Magnetic Resonance Imaging Methods, Endometrial Neoplasms Pathology, Image Interpretation, Computer-Assisted, Middle Aged, Neoplasm Grading, Observer Variation, Sensitivity And Specificity, Tumor Burden, Uterine Cervical Neoplasms Pathology,
Affiliations:
*** IBB - CNR ***
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
References:
[1] T. Koyama, K. Tamai, K. Togashi, Staging of carcinoma of the uterine cervix and endometrium, Eur. Radiol. 17 (8) (2007) 2009–2019.
[2] G. Rechichi, S. Galimberti, M. Signorelli, P. Perego, M.G. Valsecchi, S. Sironi, Myometrial invasion in endometrial cancer: diagnostic performance of diffusion weighted MR imaging at 1.5-T, Eur. Radiol. 20 (3) (2010) 754–762.
[3] A. Andreano, G. Rechichi, P. Rebora, S. Sironi, M.G. Valsecchi, S. Galimberti, MR 24 (6) (2014) 1327–1338.
[4] H.A. Rowley, P.E. Grant, T.P. Roberts, Diffusion MR imaging: theory and applications, Neuroimaging Clin. N. Am. 9 (2) (1999) 343–361.
[5] D.M. Koh, D.J. Collins, Diffusion-weighted MRI in the body: applications and challenges in oncology, AJR Am. J. Roentgenol. 188 (6) (2007) 1622–1635.
[6] S. Naganawa, C. Sato, H. Kumada, T. Ishigaki, S. Miura, O. Takizawa, Apparent diffusion coefficient in cervical cancer of the uterus: comparison with the normal uterine cervix, Eur. Radiol. 15 (1) (2005) 71–78.
[7] P.Z. McVeigh, A.M. Syed, M. Milosevic, A. Fyles, M.A. Haiderd,Diffusion-weighted MRI in cervical cancer, Eur. Radiol. 18 (5) (2008) 1058–1064.
[8] E. Sala, A. Rockall, D. Rangarajanc, R.A. Kubik-Huch, The role of dynamic contrast-enhanced and diffusion weighted magnetic resonance imaging in the female pelvis, Eur. J. Radiol. 76 (3) (2010) 367–385.
[9] S. Punwani, Diffusion weighted imaging of female pelvic cancers: concepts and clinical applications, Eur. J. Radiol. 78 (1) (2011) 21–29.
[10] G. Rechichi, S. Galimberti, M. Signorelli, C.T. Franzesi, P. Perego, M.G. Valsecchi, et al., Endometrial cancer: correlation of apparent diffusion coefficient with tumor grade, depth of myometrial invasion, and presence of lymph node metastases, AJR Am. J. Roentgenol. 197 (1) (2011) 256–262.
[11] S. Fujii, E. Matsusue, J. Kigawa, S. Sato, Y. Kanasaki, J. Nakanishi, et al., Diagnostic accuracy of the apparent diffusion coefficient in differentiating benign from malignant uterine endometrial cavity lesions: initial results, Eur. Radiol. 18 (2) (2008) 384–389.
[12] S.H. Shen, Y.Y. Chiou, J.H. Wang, M.S. Yen, R.C. Lee, C.R. Lai, et al., echo-planar imaging with parallel technique in assessment of endometrial cancer, AJR Am. J. Roentgenol. 190 (2) (2008)
[13] K. Tamai, T. Koyama, T. Saga, S. Umeoka, Y. Mikami, S. Fujii, et al., Diffusion weighted MR imaging of uterine endometrial cancer, J. Magn. Reson. Imaging 26 (3) (2007) 682–687.
[14] N. Bharwani, M.E. Miquel, A. Sahdev, P. Narayanan, G. Malietzis, R.H. Reznek, et al., Diffusion-weighted imaging in the assessment of tumour grade in endometrial cancer, Br. J. Radiol. 84 (1007) (2011) 997–1004.
[15] Y. Inada, M. Matsuki, G. Nakai, F. Tatsugami, M. Tanikake, I. Narabayashi, et al., Body diffusion weighted MR imaging of uterine endometrial cancer: is it helpful in the detection of cancer in non enhanced MR imaging? Eur. J. Radiol. 70 (1) (2009) 122–127.
[16] K. Cao, M. Gao, Y.S. Sun, Y.L. Li, Y. Sun, Y.N. Gao, et al., Apparent diffusion coefficient of diffusion weighted MRI in endometrial carcinoma-Relationship with local invasiveness, Eur. J. Radiol. 81 (8) (2012) 1926–1930.
[17] P. Beddy, A.C. O’Neil, A.K. Yamamoto, H.C. Addley, C. Reinhold, E. Sala, fiGO staging system for endometrial cancer: added benefits of MR imaging,Radiographics 32 (1) (2012) 241–254.
[18] K. Downey, S.F. Riches, V.A. Morgan, S.L. Giles, A.D. Attygalle, T.E. Ind, et al., Relationship between imaging biomarkers of stage I cervical cancer and poor-prognosis histologic features: quantitative histogram analysis of diffusion-weighted MR images, AJR Am. J. Roentgenol. 200 (2) (2013) 314–320.
[19] F. Kuang, J. Ren, Q. Zhong, F. Liyuan, Y. Huan, Z. Chen, The value of apparent diffusion coefficient in the assessment of cervical cancer, Eur. Radiol. 23 (4) (2013) 1050–1058.
[20] R. Bos, J.J. van Der Hoeven, E. van Der Wall, P. van Der Groep, P.J. van Diest, E.F.Comans, et al., Biologic correlates of (18) fluorodeoxyglucose uptake in human breast cancer measured by positron emission tomography, J. Clin. Oncol. 20 (2) (2002) 379–387.
[21] T. Higashi, N. Tamaki, T. Torizuka, Y. Nakamoto, H. Sakahara, T. Kimura, et al.,FDG uptake, GLUT-1, glucose transporter and cellularity in human pancreatic tumors, J. Nucl. Med. 39 (10) (1998) 1727–1735.
[22] K. Ito, T. Kato, T. Ohta, et al., fluorine-18 fluoro-2-deoxyglucose positron emission tomography in recurrent rectal cancer: relation to tumour size and cellularity, Eur. J. Nucl. Med. 23 (10) (1996) 1372–1377.
[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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Diffusion volume (DV) measurement in endometrial and cervical cancer: A new MRI parameter in the evaluation of the tumor grading and the risk classification
Highlights
- •The DV includes all the voxels within a tumor with ADC values below a threshold.
- •The DV selects higher cellular density voxels indicating the active tumor burden.
- •The DV of cervical and endometrial cancer allows stratification of G-grade and risk groups.
- •The DV works better than the ADC values and T2 volume in the above stratification.
- •The intra- and inter-observer variability of DV is excellent.
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 underwent 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 outlined 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 mm 2/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.
Diffusion volume (DV) measurement in endometrial and cervical cancer: A new MRI parameter in the evaluation of the tumor grading and the risk classification
Diffusion volume (DV) measurement in endometrial and cervical cancer: A new MRI parameter in the evaluation of the tumor grading and the risk classification
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Impact Factor: 1.302
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Brunetti A, Postiglione A, Tedeschi E, Ciarmiello A, Quarantelli M, Covelli E, Milan G, Larobina M, Soricelli A, Sodano A, Alfano B
Measurement of global drain atrophy in Alzheimer's disease with unsupervised segmentation of spin-echo MRI studies (418 views)
J Magn Reson Imaging (ISSN: 1053-1807, 1522-2586electronic), 2000 Mar; 11(3): N/D-N/D.
Impact Factor: 1.302
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Larobina M, Quarantelli M, Tedeschi E, Brunetti A, Alfano B, Salvatore M
Validation of an automated regional brain segmentation method using a stereotactic Talairach approach (432 views)
Surgery International Congress Series Car 97 (ISSN: 0531-5131), 1999; 1191: N/D-N/D.
Impact Factor: 1.438
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Alfano B, Quarantelli M, Brunetti A, Larobina M, Covelli EM, Tedeschi E, Salvatore M
Reproducibility of intracranial volume measurement by unsupervised multispectral brain segmentation (500 views) (PDF 592 views)
Magn Reson Med (ISSN: 0740-3194, 1522-2594electronic, 0740-3194linking), 1998 Mar; 39(3): 497-499.
Impact Factor: 2.962
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Alfano B, Brunetti A, Covelli EM, Quarantelli M, Panico M, Ciarmiello A, Salvatore M
Unsupervised, automated segmentation of the normal brain using a multispectral relaxometric magnetic resonance approach (494 views) (PDF 686 views)
Magn Reson Med (ISSN: 0740-3194, 1522-2594electronic, 0740-3194linking), 1997 Jan; 37(1): 84-93.
Impact Factor: 3.012
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Alfano B, Brunetti A, Quarantelli M, Larobina M, Covelli EM, Tedeschi E, Ciarmiello A, Salvatore M
Fully-automated multispectral MR brain segmentation for detection and volumetric measurement of white matter lesions (346 views)
Surgery International Congress Series Car 97 (ISSN: 0531-5131), 1997; 1134: N/D-N/D.
Impact Factor: 1.438
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Brunetti A, Covelli E, Tedeschi E, Quarantelli M, Soricelli A, Salvatore M, Alfano B
Unsupervised multifeature MR segmentation for assessment of intracranial liquoral spaces: Comparison with conventional linear measures (338 views)
Surgery International Congress Series Car 97 (ISSN: 0531-5131), 1996; 1124: N/D-N/D.
Impact Factor: 1.438
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ALFANO B, ARPAIA M, BRUNETTI A, COVELLI E, CASTELLI L, CARACO C, SORICELLI A, TEDESCHI E, SALVATORE M
Automatic segmentation and evaluation of the volume of gray matter, white matter and cerebrospinal fluid by MRI (308 views)
Neuroradiology 1994, 1994; N/D: N/D-N/D.
Impact Factor: 0
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MRI radiomics: A machine learning approach for the risk stratification of endometrial cancer patients (15 views) (PDF 12 views)
Eur J Of Radioloy, 2022 Feb; N/D: 1-6.
Impact Factor: 2.687
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Stanzione A, Maurea S, Danzi R, Cuocolo R, Galatola R, Romeo V, Raffone A, Travaglino A, Di Spiezio SA, Insabato L, Pace L, Scaglione M, Brunetti A, Mainenti PP
* MRI to assess deep myometrial invasion in patients with endometrial cancer: A multi-reader study to evaluate the diagnostic role of different sequences (9 views)
Eur J Of Radioloy, 2022 Feb; N/D: 1-8.
Impact Factor: 2.687
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Stanzione A, Cuocolo R, Del Grosso R, Nardiello A, Romeo V, Travaglino A, Raffone A, Bifulco G, Zullo F, Insabato L, Maurea S, Mainenti PP
* Deep Myometrial Infiltration of Endometrial Cancer on MRI: A Radiomics-Powered Machine Learning Pilot Study (38 views)
Acad Radiol (ISSN: 1076-6332linking, 1878-4046electronic), 2021 May; 28(5): 737-744.
Impact Factor: 2.488
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Stanzione A, Maurea S, Danzi R, Cuocolo R, Galatola R, Romeo V, Raffone A, Travaglino A, Di Spiezio Sardo A, Insabato L, Pace L, Scaglione M, Brunetti A, Mainenti PP
* MRI to assess deep myometrial invasion in patients with endometrial cancer: A multi-reader study to evaluate the diagnostic role of different sequences (12 views)
Eur J Radiol (ISSN: 0720-048xlinking), 2021 May; 138: 109629-109629.
Impact Factor: 2.687
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Capasso D, Borbone N, Terracciano M, Di Gaetano S, Piccialli V
* Antiproliferative Activity of Mycalin A and Its Analogues on Human Skin Melanoma and Human Cervical Cancer Cells (74 views)
Mar Drugs (ISSN: 1660-3397linking), 2020 Jul 29; 18(8): N/D-N/D.
Impact Factor: 4.379
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Monti S, Cocozza S, Borrelli P, Straub S, Ladd ME, Salvatore M, Tedeschi E, Palma G
* MAVEN: An Algorithm for Multi-Parametric Automated Segmentation of Brain Veins from Gradient Echo Acquisitions (207 views) (PDF 184 views)
Ieee T Med Imaging (ISSN: 0278-0062), 2017; 36(5): 1054-1065.
Impact Factor: 6.131
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Monti S, Borrelli P, Cocozza S, Straub S, Ladd ME, Salvatore M, Mancini M, Tedeschi E, Palma G
* Assessment of an automated vein segmentation algorithm for MRI brain acquisitions at different field strengths (359 views) (PDF 179 views)
6th Annual Meeting Of The International Society For Neurovascular Disease, 2016 Apr; N/D: N/D-N/D.
Impact Factor: 0
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Monti S, Borrelli P, Cocozza S, Salvatore M, Mancini M, Tedeschi E, Palma G
* Multi-parametric algorithm for the automated segmentation of brain vein (336 views) (PDF 184 views)
6th Annual Meeting Of The International Society For Neurovascular Disease, 2016 Apr; N/D: N/D-N/D.
Impact Factor: 0
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Monti S, Palma G, Borrelli P, Tedeschi E, Cocozza S, Salvatore M, Mancini M
* A multiparametric and multiscale approach to automated segmentation of brain veins (369 views) (PDF 256 views)
Proceedings Of Engineering In Medicine And Biology Society, 2015; N/D: 3041-3044.
Impact Factor: 0
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Monti S, Palma G, Tedeschi E, Borrelli P, Cocozza S, Salvatore M, Mancini M
* MULTIPARAMETRIC AUTOMATED SEGMENTATION OF BRAIN VEINS (390 views)
Veins And Lymphatics (ISSN: 2279-7483), 2015; 4(s1): 13-13.
Impact Factor: 0
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Larobina M, Murino L, Cervo A, Alfano B
* Self-Trained Supervised Segmentation of Subcortical Brain Structures Using Multispectral Magnetic Resonance Images (339 views)
Biomed Research International, 2015; 2015: N/D-9.
Impact Factor: 2.13
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Conson M, Cella L, Pacelli R, Comerci M, Liuzzi R, Salvatore M, Quarantelli M
* Automated delineation of brain structures in patients undergoing radiotherapy for primary brain tumors: From atlas to dose-volume histograms (759 views) (PDF 368 views)
Radiother Oncol (ISSN: 0167-8140, 1879-0887, 0167-8140linking), 2014 Sep; 112(3): 326-331.
Impact Factor: 4.363
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Murino L, Granata D, Carfora MF, Selvan SE, Alfano B, Amato U, Larobina M
* Evaluation of supervised methods for the classification of major tissues and subcortical structures in multispectral brain magnetic resonance images (441 views) (PDF 222 views)
Comput Med Imag Grap (ISSN: 0895-6111), 2014 Jul; 38(5): 337-347.
Impact Factor: 1.218
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Comerci M, Elefante A, Strianese D, Senese R, Bonavolonta P, Alfano B, Bonavolonta B, Brunetti A
* Semiautomatic regional segmentation to measure orbital fat volumes in thyroid-associated ophthalmopathy. A validation study (433 views) (PDF 251 views)
Neuroradiol J (ISSN: 1971-4009, 1971-4009print, 1971-4009linking), 2013 Aug; 26(4): 373-379.
Impact Factor: 2.16
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Mainenti PP, Iodice D, Cozzolino I, Segreto S, Capece S, Sica G, Magliulo M, Ciancia G, Pace L, Salvatore M
* Tomographic imaging of the spleen: the role of morphological and metabolic features in differentiating benign from malignant diseases (277 views)
Clin Imaging (ISSN: 1873-4499, 0899-7071, 0899-7071linking), 2012 Sep; 36(5): 559-567.
Impact Factor: 0.648
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Alfano B, Comerci M, Larobina M, Prinster A, Hornak JP, Selvan SE, Amato U, Quarantelli M, Tedeschi G, Brunetti A, Salvatore M
* An MRI digital brain phantom for validation of segmentation methods (491 views) (PDF 662 views)
Med Image Anal (ISSN: 1361-8415, 1361-8423, 1361-8415linking), 2011 Jun; 15(3): 329-339.
Impact Factor: 4.424
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Ceccarelli M, Speranza A, Grimaldi D, Lamonaca F
* A Computer Vision Approach to Micro-Nucleus automatic detection and surface measurements (388 views)
Vols 1 3i2mtc (ISSN: 0018-9456), 2010 Sep 10; 59(9): 2383-2390.
Impact Factor: 1.79
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Alfano B, Comerci M, De Pietro G, Esposito A
* An ontology-based technique for validation of MRI brain segmentation methods (369 views) (PDF 242 views)
Lecture Notes In Computer Science (ISSN: 0302-9743, 0302-974335404636319783540463634, 0302-974335402975459783540297543), 2007; 4805LNCS(PART1): 566-575.
Impact Factor: 0.302
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Quarantelli M, Lanzillo R, Del Vecchio W, Mollica C, Prinster A, Iadicicco L, Iodice V, Santoro L, Salvatore M
* Modifications of brain tissue volumes in facioscapulohumeral dystrophy (476 views)
Neuroimage (ISSN: 1053-8119, 1053-8119linking), 2006 Sep; 32(3): 1237-1242.
Impact Factor: 5.559
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Berkouk K, Quarantelli M, Prinster A, Landeau B, Alfano B, Baron JC
* Mapping The Relative Contribution Of Gray Matter Activity Versus Volume In Brain Pet. A New Approach (359 views) (PDF 227 views)
J Neuroimaging (ISSN: 1051-2284, 1051-2284linking), 2006 Jul; 16(3): 224-235.
Impact Factor: 1.298
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Tedeschi G, Dinacci D, Lavorgna L, Bonavita V, Livrea P, Quattrone A, Messina C, Savettieri G, Paciello M, Reggio A, Brunetti A, Russo P, Alfano B
* Automated brain MR segmentation in a large MS population (363 views)
Neurology (ISSN: 0028-3878, 1526-632x, 1526-632xelectronic), 2004 Apr 13; 62(7): N/D-N/D.
Impact Factor: 5.973
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Amato U, Larobina M, Antoniadis A, Alfano B
* Segmentation of magnetic resonance brain images through discriminant analysis (554 views) (PDF 239 views)
J Neurosci Methods (ISSN: 0165-0270, 0165-0270linking, 1872-678xelectronic), 2003 Dec 30; 131(1-2): 65-74.
Impact Factor: 1.777
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Quarantelli M, Ciarmiello A, Morra VB, Orefice G, Larobina M, Lanzillo R, Schiavone V, Salvatore E, Alfano B, Brunetti A
* Brain tissue volume changes in relapsing-remitting multiple sclerosis: Correlation with lesion load (429 views) (PDF 231 views)
Neuroimage (ISSN: 1053-8119, 1053-8119linking), 2003 Feb; 18(2): 360-366.
Impact Factor: 6.192
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Alfano B, Brunetti A, Larobina M, Quarantelli M, Tedeschi E, Ciarmiello A, Covelli EM, Salvatore M
Automated segmentation and measurement of global white matter lesion volume in patients with multiple sclerosis (438 views) (PDF 614 views)
J Magn Reson Imaging (ISSN: 1053-1807, 1522-2586electronic, 1053-1807linking), 2000 Dec; 12(6): 799-807.
Impact Factor: 1.302
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Brunetti A, Postiglione A, Tedeschi E, Ciarmiello A, Quarantelli M, Covelli EM, Milan G, Larobina M, Soricelli A, Sodano A, Alfano B
Measurement of global brain atrophy in Alzheimer's disease with unsupervised segmentation of spin-echo MRI studies (574 views) (PDF 267 views)
J Magn Reson Imaging (ISSN: 1053-1807, 1522-2586electronic), 2000 Mar; 11(3): 260-266.
Impact Factor: 1.302
View Export to BibTeX Export to EndNote
Brunetti A, Postiglione A, Tedeschi E, Ciarmiello A, Quarantelli M, Covelli E, Milan G, Larobina M, Soricelli A, Sodano A, Alfano B
Measurement of global drain atrophy in Alzheimer's disease with unsupervised segmentation of spin-echo MRI studies (418 views)
J Magn Reson Imaging (ISSN: 1053-1807, 1522-2586electronic), 2000 Mar; 11(3): N/D-N/D.
Impact Factor: 1.302
View Export to BibTeX Export to EndNote
Larobina M, Quarantelli M, Tedeschi E, Brunetti A, Alfano B, Salvatore M
Validation of an automated regional brain segmentation method using a stereotactic Talairach approach (432 views)
Surgery International Congress Series Car 97 (ISSN: 0531-5131), 1999; 1191: N/D-N/D.
Impact Factor: 1.438
View Export to BibTeX Export to EndNote
Alfano B, Quarantelli M, Brunetti A, Larobina M, Covelli EM, Tedeschi E, Salvatore M
Reproducibility of intracranial volume measurement by unsupervised multispectral brain segmentation (500 views) (PDF 592 views)
Magn Reson Med (ISSN: 0740-3194, 1522-2594electronic, 0740-3194linking), 1998 Mar; 39(3): 497-499.
Impact Factor: 2.962
View Export to BibTeX Export to EndNote
Alfano B, Brunetti A, Covelli EM, Quarantelli M, Panico M, Ciarmiello A, Salvatore M
Unsupervised, automated segmentation of the normal brain using a multispectral relaxometric magnetic resonance approach (494 views) (PDF 686 views)
Magn Reson Med (ISSN: 0740-3194, 1522-2594electronic, 0740-3194linking), 1997 Jan; 37(1): 84-93.
Impact Factor: 3.012
View Export to BibTeX Export to EndNote
Alfano B, Brunetti A, Quarantelli M, Larobina M, Covelli EM, Tedeschi E, Ciarmiello A, Salvatore M
Fully-automated multispectral MR brain segmentation for detection and volumetric measurement of white matter lesions (346 views)
Surgery International Congress Series Car 97 (ISSN: 0531-5131), 1997; 1134: N/D-N/D.
Impact Factor: 1.438
View Export to BibTeX Export to EndNote
Brunetti A, Covelli E, Tedeschi E, Quarantelli M, Soricelli A, Salvatore M, Alfano B
Unsupervised multifeature MR segmentation for assessment of intracranial liquoral spaces: Comparison with conventional linear measures (338 views)
Surgery International Congress Series Car 97 (ISSN: 0531-5131), 1996; 1124: N/D-N/D.
Impact Factor: 1.438
View Export to BibTeX Export to EndNote
ALFANO B, ARPAIA M, BRUNETTI A, COVELLI E, CASTELLI L, CARACO C, SORICELLI A, TEDESCHI E, SALVATORE M
Automatic segmentation and evaluation of the volume of gray matter, white matter and cerebrospinal fluid by MRI (308 views)
Neuroradiology 1994, 1994; N/D: N/D-N/D.
Impact Factor: 0
View Export to BibTeX Export to EndNote
32 Records (22 excluding Abstracts).
Total impact factor: 73.087 (61.196 excluding Abstracts).
Total 5 year impact factor: 79.33 (60.928 excluding Abstracts).
Total impact factor: 73.087 (61.196 excluding Abstracts).
Total 5 year impact factor: 79.33 (60.928 excluding Abstracts).
884 views. Last view on Friday 23 September 2022, 14:43:34
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