The Diagnostic Performance of Magnetic Resonance Texture Analysis in Histological Subtyping and Grading of the Renal Cell Carcinoma

Nusret Seher; Mustafa Koplay; Abidin Kılınçer; Lütfi Saltuk Demir; Mehmet Kaynar; Kadir Böcü; Serdar Göktaş

Article Details

The Diagnostic Performance of Magnetic Resonance Texture Analysis in Histological Subtyping and Grading of the Renal Cell Carcinoma

Authors:

Nusret Seher | Mustafa Koplay | Abidin Kılınçer | Lütfi Saltuk Demir | Mehmet Kaynar | Kadir Böcü | Serdar Göktaş

Publisher:

Selcuk University

Main Topics:

Radyoloji ve Organ Görüntüleme

Journal:

Genel Tıp Dergisi Vol.35 Issue 2, pp.255-263

Document Type:

Article

Publication Date:

4/2025

Document Language:

English

Document ID (Org No.):

2001345135

pISSN:

2602-3741

Keywords:

Abstract:

 Backgrounds-Aims: To evaluate the efficiency of MRTA in distinguishing RCC types and in the distinction of tumor grade. Methods: 62 patients were analyzed retrospectively and grouped as 40 clear cell-RCC, 11 papillary-RCC and 11 chromophobe-RCC. In the MRI 1.5-T protocol, the axial T2 weighted W, axial T1W in-phase IP and apparent diffusion coefficient ADC images were used. Additionally, postcontrast images obtained in the corticomedullary CM phase and nephrogram NG phase of the axial fat-suppressed T1W VIBE sequence were used. In MRTA were used parameters as mean, median, entropy, skewness, kurtosis, variance, uniformity. Statistical analysis was performed to compare CC-RCC NC-RCC, and high-grade low-grade tumors and between the subtypes. Results: Tissue parameters that perform best in separating CC-RCC from NC-RCC AUC in brackets: Values obtained included entropy 0.67 in CM phase, mean 0.75 and median 0.76 in ADC, entropy 0,66 and variance 0.66 in NG phase were obtained. The p values in IP and T2W images in the distinction between the high and low degrees were significant. Conclusion: Several MR texture parameters performed well AUC 0.75 in separating CC-RCC from NC-RCC. MRTA can be a useful noninvasive tool for this purpose. The first order parameters that we used in TA can be used to evaluate the prognosis in RCC patients.

 Backgrounds-Aims: To evaluate the efficiency of MRTA in distinguishing RCC types and in the distinction of tumor grade. Methods: 62 patients were analyzed retrospectively and grouped as 40 clear cell-RCC, 11 papillary-RCC and 11 chromophobe-RCC. In the MRI 1.5-T protocol, the axial T2 weighted W, axial T1W in-phase IP and apparent diffusion coefficient ADC images were used. Additionally, postcontrast images obtained in the corticomedullary CM phase and nephrogram NG phase of the axial fat-suppressed T1W VIBE sequence were used. In MRTA were used parameters as mean, median, entropy, skewness, kurtosis, variance, uniformity. Statistical analysis was performed to compare CC-RCC NC-RCC, and high-grade low-grade tumors and between the subtypes. Results: Tissue parameters that perform best in separating CC-RCC from NC-RCC AUC in brackets: Values obtained included entropy 0.67 in CM phase, mean 0.75 and median 0.76 in ADC, entropy 0,66 and variance 0.66 in NG phase were obtained. The p values in IP and T2W images in the distinction between the high and low degrees were significant. Conclusion: Several MR texture parameters performed well AUC 0.75 in separating CC-RCC from NC-RCC. MRTA can be a useful noninvasive tool for this purpose. The first order parameters that we used in TA can be used to evaluate the prognosis in RCC patients.

 Backgrounds-Aims: To evaluate the efficiency of MRTA in distinguishing RCC types and in the distinction of tumor grade. Methods: 62 patients were analyzed retrospectively and grouped as 40 clear cell-RCC, 11 papillary-RCC and 11 chromophobe-RCC. In the MRI 1.5-T protocol, the axial T2 weighted W, axial T1W in-phase IP and apparent diffusion coefficient ADC images were used. Additionally, postcontrast images obtained in the corticomedullary CM phase and nephrogram NG phase of the axial fat-suppressed T1W VIBE sequence were used. In MRTA were used parameters as mean, median, entropy, skewness, kurtosis, variance, uniformity. Statistical analysis was performed to compare CC-RCC NC-RCC, and high-grade low-grade tumors and between the subtypes. Results: Tissue parameters that perform best in separating CC-RCC from NC-RCC AUC in brackets: Values obtained included entropy 0.67 in CM phase, mean 0.75 and median 0.76 in ADC, entropy 0,66 and variance 0.66 in NG phase were obtained. The p values in IP and T2W images in the distinction between the high and low degrees were significant. Conclusion: Several MR texture parameters performed well AUC 0.75 in separating CC-RCC from NC-RCC. MRTA can be a useful noninvasive tool for this purpose. The first order parameters that we used in TA can be used to evaluate the prognosis in RCC patients.

 Backgrounds-Aims: To evaluate the efficiency of MRTA in distinguishing RCC types and in the distinction of tumor grade. Methods: 62 patients were analyzed retrospectively and grouped as 40 clear cell-RCC, 11 papillary-RCC and 11 chromophobe-RCC. In the MRI 1.5-T protocol, the axial T2 weighted W, axial T1W in-phase IP and apparent diffusion coefficient ADC images were used. Additionally, postcontrast images obtained in the corticomedullary CM phase and nephrogram NG phase of the axial fat-suppressed T1W VIBE sequence were used. In MRTA were used parameters as mean, median, entropy, skewness, kurtosis, variance, uniformity. Statistical analysis was performed to compare CC-RCC NC-RCC, and high-grade low-grade tumors and between the subtypes. Results: Tissue parameters that perform best in separating CC-RCC from NC-RCC AUC in brackets: Values obtained included entropy 0.67 in CM phase, mean 0.75 and median 0.76 in ADC, entropy 0,66 and variance 0.66 in NG phase were obtained. The p values in IP and T2W images in the distinction between the high and low degrees were significant. Conclusion: Several MR texture parameters performed well AUC 0.75 in separating CC-RCC from NC-RCC. MRTA can be a useful noninvasive tool for this purpose. The first order parameters that we used in TA can be used to evaluate the prognosis in RCC patients.

Article Details

The Diagnostic Performance of Magnetic Resonance Texture Analysis in Histological Subtyping and Grading of the Renal Cell Carcinoma

Authors:

Nusret Seher | Mustafa Koplay | Abidin Kılınçer | Lütfi Saltuk Demir | Mehmet Kaynar | Kadir Böcü | Serdar Göktaş

Publisher:

Selcuk University

Main Topics:

Radyoloji ve Organ Görüntüleme

Journal:

Genel Tıp Dergisi Vol.35 Issue 2, pp.255-263

Document Type:

Article

Publication Date:

4/2025

Document Language:

English

Document ID (Org No.):

2001345135

pISSN:

2602-3741

Renal cell carcinoma

texture analysis

Fuhrman

grade

MRI

Issues

Article Details

The Diagnostic Performance of Magnetic Resonance Texture Analysis in Histological Subtyping and Grading of the Renal Cell Carcinoma

Authors: Nusret Seher | Mustafa Koplay | Abidin Kılınçer | Lütfi Saltuk Demir | Mehmet Kaynar | Kadir Böcü | Serdar Göktaş

Publisher: Selcuk University

Main Topics: Radyoloji ve Organ Görüntüleme

Journal: Genel Tıp Dergisi Vol.35 Issue 2, pp.255-263

Document Type: Article

Publication Date: 4/2025

Document Language: English

Document ID (Org No.): 2001345135

pISSN: 2602-3741

Renal cell carcinoma

texture analysis

Fuhrman

grade

MRI

Issues

Authors:

Nusret Seher | Mustafa Koplay | Abidin Kılınçer | Lütfi Saltuk Demir | Mehmet Kaynar | Kadir Böcü | Serdar Göktaş

Publisher:

Selcuk University

Main Topics:

Radyoloji ve Organ Görüntüleme

Journal:

Genel Tıp Dergisi Vol.35 Issue 2, pp.255-263

Document Type:

Article

Publication Date:

4/2025

Document Language:

English

Document ID (Org No.):

2001345135

pISSN:

2602-3741