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Das CJ, Malagi AV, Sharma R, Mehndiratta A, Kumar V, Khan MA, Seth A, Kaushal S, Nayak B, Kumar R, Gupta AK. Intravoxel incoherent motion and diffusion kurtosis imaging and their machine-learning-based texture analysis for detection and assessment of prostate cancer severity at 3 T. NMR IN BIOMEDICINE 2024; 37:e5144. [PMID: 38556777 DOI: 10.1002/nbm.5144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 02/01/2024] [Accepted: 02/20/2024] [Indexed: 04/02/2024]
Abstract
OBJECTIVES To evaluate the role of combined intravoxel incoherent motion and diffusion kurtosis imaging (IVIM-DKI) and their machine-learning-based texture analysis for the detection and assessment of severity in prostate cancer (PCa). MATERIALS AND METHODS Eighty-eight patients underwent MRI on a 3 T scanner after giving informed consent. IVIM-DKI data were acquired using 13 b values (0-2000 s/mm2) and analyzed using the IVIM-DKI model with the total variation (TV) method. PCa patients were categorized into two groups: clinically insignificant prostate cancer (CISPCa) (Gleason grade ≤ 6) and clinically significant prostate cancer (CSPCa) (Gleason grade ≥ 7). One-way analysis-of-variance, t test, and receiver operating characteristic analysis was performed to measure the discriminative ability to detect PCa using IVIM-DKI parameters. A chi-square test was used to select important texture features of apparent diffusion coefficient (ADC) and IVIM-DKI parameters. These selected texture features were used in an artificial neural network for PCa detection. RESULTS ADC and diffusion coefficient (D) were significantly lower (p < 0.001), and kurtosis (k) was significantly higher (p < 0.001), in PCa as compared with benign prostatic hyperplasia (BPH) and normal peripheral zone (PZ). ADC, D, and k showed high areas under the curves (AUCs) of 0.92, 0.89, and 0.88, respectively, in PCa detection. ADC and D were significantly lower (p < 0.05) as compared with CISPCa versus CSPCa. D for detecting CSPCa was high, with an AUC of 0.63. A negative correlation of ADC and D with GS (ADC, ρ = -0.33; D, ρ = -0.35, p < 0.05) and a positive correlation of k with GS (ρ = 0.22, p < 0.05) were observed. Combined IVIM-DKI texture showed high AUC of 0.83 for classification of PCa, BPH, and normal PZ. CONCLUSION D, f, and k computed using the IVIM-DKI model with the TV method were able to differentiate PCa from BPH and normal PZ. Texture features of combined IVIM-DKI parameters showed high accuracy and AUC in PCa detection.
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Affiliation(s)
- Chandan J Das
- Department of Radio-Diagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Archana Vadiraj Malagi
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Raju Sharma
- Department of Radio-Diagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
| | - Amit Mehndiratta
- Centre for Biomedical Engineering, Indian Institute of Technology Delhi, New Delhi, India
| | - Virendra Kumar
- Department of Nuclear Magnetic Resonance, All India Institute of Medical Sciences, New Delhi, India
| | - Maroof A Khan
- Department of Biostatistics, All India Institute of Medical Sciences, New Delhi, India
| | - Amlesh Seth
- Department of Urology, All India Institute of Medical Sciences, New Delhi, India
| | - Seema Kaushal
- Department of Pathology, All India Institute of Medical Sciences, New Delhi, India
| | - Baibaswata Nayak
- Department of Gastroenterology (Molecular Biology Division), All India Institute of Medical Sciences, New Delhi, India
| | - Rakesh Kumar
- Department of Nuclear Medicine, All India Institute of Medical Sciences, New Delhi, India
| | - Arun Kumar Gupta
- Department of Radio-Diagnosis and Interventional Radiology, All India Institute of Medical Sciences, New Delhi, India
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Zou J, Ye J, Zhu W, Wu J, Chen W, Chen R, Zhu Q. Diffusion-weighted and diffusion kurtosis imaging analysis of microstructural differences in clear cell renal cell carcinoma: a comparative study. Br J Radiol 2023; 96:20230146. [PMID: 37393526 PMCID: PMC10546464 DOI: 10.1259/bjr.20230146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2023] [Revised: 06/12/2023] [Accepted: 06/13/2023] [Indexed: 07/03/2023] Open
Abstract
OBJECTIVE To quantitatively compare the diagnostic values of conventional diffusion-weighted imaging (DWI) and diffusion kurtosis imaging (DKI) analysis of microstructural differences for clear cell renal cell carcinoma (CRCC). METHODS A total of 108 patients with pathologically confirmed CRCC, including 38 Grade I, 37 Grade II, 18 Grade III and 15 Grade IV, were enrolled and divided into groups according to tumor grade [low grade (Ⅰ+Ⅱ, n = 75) and high grade (Ⅲ+Ⅳ, n = 33)]. Apparent diffusion coefficient (ADC), mean diffusivity (MD), mean kurtosis (MK), kurtosis anisotropy (KA) and radial kurtosis (RK) were performed. RESULTS Both the ADC (r = -0.803) and MD (-0.867) values showed a negative correlation with tumor grading (p < 0.05) and MK (r = 0.812), KA (0.816) and RK (0.853) values a positive correlation with tumor grading (p < 0.05). Mean FA values showed no significant differences among CRCC grades (p > 0.05). ROC curve analyses showed that MD values had the highest diagnostic efficacy in differentiating low/high and Ⅱ/Ⅲ tumor grading. MD values gave AUC: 0.937 (0.896); sensitivity: 92.0% (86.5%); specificity: 78.8% (77.8%) and accuracy: 90.7% (87.3%). ADC performed worse than MD, MK, KA or RK (all p < 0.05) during pair-wise comparisons of ROC curves to show diagnostic efficacy. CONCLUSION DKI analysis performs better than ADC in differentiating CRCC grading. ADVANCES IN KNOWLEDGE Both the ADC and MD values correlated negatively with CRCC grading.The MK, KA and RK values correlated positively with CRCC grading.MD values had the highest diagnostic efficacy in differentiating low/high and Ⅱ/Ⅲ CRCC grading.
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Affiliation(s)
- Jinzhao Zou
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Jing Ye
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Wenrong Zhu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Jingtao Wu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Wenxin Chen
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Rui Chen
- Department of Kidney internal medicine, Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Qingqiang Zhu
- Department of Medical Imaging, Clinical Medical College, Yangzhou University, Yangzhou, China
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Zhou KP, Huang HB, Bu C, Luo ZX, Huang WS, Xie LZ, Liu QY, Bian J. Sub-differentiation of PI-RADS 3 lesions in TZ by advanced diffusion-weighted imaging to aid the biopsy decision process. Front Oncol 2023; 13:1092073. [PMID: 36845749 PMCID: PMC9950630 DOI: 10.3389/fonc.2023.1092073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/26/2023] [Indexed: 02/12/2023] Open
Abstract
Background Performing biopsy for intermediate lesions with PI-RADS 3 has always been controversial. Moreover, it is difficult to differentiate prostate cancer (PCa) and benign prostatic hyperplasia (BPH) nodules in PI-RADS 3 lesions by conventional scans, especially for transition zone (TZ) lesions. The purpose of this study is sub-differentiation of transition zone (TZ) PI-RADS 3 lesions using intravoxel incoherent motion (IVIM), stretched exponential model, and diffusion kurtosis imaging (DKI) to aid the biopsy decision process. Methods A total of 198 TZ PI-RADS 3 lesions were included. 149 lesions were BPH, while 49 lesions were PCa, including 37 non-clinical significant PCa (non-csPCa) lesions and 12 clinical significant PCa (csPCa) lesions. Binary logistic regression analysis was used to examine which parameters could predict PCa in TZ PI-RADS 3 lesions. The ROC curve was used to test diagnostic efficiency in distinguishing PCa from TZ PI-RADS 3 lesions, while one-way ANOVA analysis was used to examine which parameters were statistically significant among BPH, non-csPCa and csPCa. Results The logistic model was statistically significant (χ2 = 181.410, p<0.001) and could correctly classify 89.39% of the subjects. Parameters of fractional anisotropy (FA) (p=0.004), mean diffusion (MD) (p=0.005), mean kurtosis (MK) (p=0.015), diffusion coefficient (D) (p=0.001), and distribute diffusion coefficient (DDC) (p=0.038) were statistically significant in the model. ROC analysis showed that AUC was 0.9197 (CI 95%: 0.8736-0.9659). Sensitivity, specificity, positive predictive value and negative predictive value were 92.1%, 80.4%, 93.9% and 75.5%, respectively. FA and MK of csPCa were higher than those of non-csPCa (all p<0.05), while MD, ADC, D, and DDC of csPCa were lower than those of non-csPCa (all p<0.05). Conclusion FA, MD, MK, D, and DDC can predict PCa in TZ PI-RADS 3 lesions and inform the decision-making process of whether or not to perform a biopsy. Moreover, FA, MD, MK, D, DDC, and ADC may have ability to identify csPCa and non-csPCa in TZ PI-RADS 3 lesions.
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Affiliation(s)
- Kun-Peng Zhou
- Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Hua-Bin Huang
- Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Chao Bu
- Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Zhong-Xing Luo
- Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Wen-Sheng Huang
- Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | | | - Qing-Yu Liu
- Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Jie Bian
- Radiology, Second Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China,*Correspondence: Jie Bian,
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Liu G, Lu Y, Dai Y, Xue K, Yi Y, Xu J, Wu D, Wu G. Comparison of mono-exponential, bi-exponential, kurtosis, and fractional-order calculus models of diffusion-weighted imaging in characterizing prostate lesions in transition zone. Abdom Radiol (NY) 2021; 46:2740-2750. [PMID: 33388809 DOI: 10.1007/s00261-020-02903-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Revised: 12/01/2020] [Accepted: 12/06/2020] [Indexed: 12/16/2022]
Abstract
PURPOSE To compare various models of diffusion-weighted imaging including mono-exponential, bi-exponential, diffusion kurtosis (DK) and fractional-order calculus (FROC) models in diagnosing prostate cancer (PCa) in transition zone (TZ) and distinguish the high-grade PCa [Gleason score (GS) ≥ 7] lesions from the total of low-grade PCa (GS ≤ 6) lesions and benign prostatic hyperplasia (BPH) in TZ. METHODS 80 Patients with 103 lesions were included in this study. Nine metrics [including apparent diffusion coefficient (ADC) derived from mono-exponential model, slow diffusion coefficient (Ds), fast diffusion coefficient (Df),, and f (the fraction of fast diffusion) from bi-exponential model; mean diffusivity (MD) and mean kurtosis (MK) from DK model; diffusion coefficient (D), fractional-order derivative in space (β), and spatial metric (μ) from FROC model] were calculated. Comparisons between BPH and PCa lesions as well as between clinically significant PCa (CsPCa) (GS ≥ 7, n = 31) and clinically insignificant lesions (Cins) (GS ≤ 6 and BPH, n = 72) of these metrics were conducted. Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were used for statistical evaluations. RESULTS The areas under the ROC curve (AUC) values of β derived from FROC model were 0.778 and 0.853 in differentiating PCa from BPH and in differentiating CS (GS ≥ 7) from Cins (GS ≤ 6 and BPH), both were the highest compared to other metrics. The AUC value of β was significantly higher than that of ADC (P = 0.009) in differentiating CS from Cins, while the differentiation between BPH and PCa did not reach the statistical significance when comparing with ADC (P = 0.089). CONCLUSION Although no significant difference was found in distinguishing PCa from BPH, the metric β derived from FROC model was superior to other diffusion metrics in differentiation between CS and Cins in TZ.
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Affiliation(s)
- Guiqin Liu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China
| | - Yang Lu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China
| | | | - Ke Xue
- United Imaging Healthcare, Shanghai, China
| | | | - Jianrong Xu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China
| | - Dongmei Wu
- Shanghai Key Laboratory of Magnetic Resonance, School of Physics and Electronics Science, East China Normal University, 3663 N. Zhongshan Road, Shanghai, 200062, China.
| | - Guangyu Wu
- Department of Radiology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, 160 Pujian Road, Shanghai, 200127, China.
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Franiel T, Asbach P, Beyersdorff D, Blondin D, Kaufmann S, Mueller-Lisse UG, Quentin M, Rödel S, Röthke M, Schlemmer HP, Schimmöller L. mpMRI of the Prostate (MR-Prostatography): Updated Recommendations of the DRG and BDR on Patient Preparation and Scanning Protocol. ROFO-FORTSCHR RONTG 2021; 193:763-777. [PMID: 33735931 DOI: 10.1055/a-1406-8477] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The Working Group Uroradiology and Urogenital Diagnosis of the German Roentgen Society (DRG) revised and updated the recommendations for preparation and scanning protocol of the multiparametric MRI of the Prostate in a consensus process and harmonized it with the managing board of German Roentgen Society and Professional Association of the German Radiologist (BDR e. V.). These detailed recommendation define the referenced "validated quality standards" of the German S3-Guideline Prostate Cancer and describe in detail the topic 1. anamnestic datas, 2. termination of examinations and preparation of examinations, 3. examination protocol and 4. MRI-(in-bore)-biopsy. KEY POINTS:: · The recommendations for preparation and scanning protocol of the multiparametric MRI of the Prostate were revised and updated in a consensus process and harmonized with the managing board of German Roentgen Society (DRG) and Professional Asssociation of the German Radiologist (BDR).. · Detailed recommendations are given for topic 1. anamnestic datas, 2. termination and preparation of examinations, 3. examination protocoll and 4. MRI-(in-bore)-biopsy.. · These recommendations define the referenced "validated quality standards" of the German S3-Guideline Prostate Cancer.. CITATION FORMAT: · Franiel T, Asbach P, Beyersdorff D et al. mpMRI of the Prostate (MR-Prostatography): Updated Recommendations of the DRG and BDR on Patient Preparation and Examination Protocol. Fortschr Röntgenstr 2021; 193: 763 - 776.
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Affiliation(s)
- Tobias Franiel
- Institut für diagnostische und interventionelle Radiologie, Universitätsklinikum Jena, Deutschland
| | - Patrick Asbach
- Klinik für Radiologie, Charité Campus Benjamin Franklin, Charité-Universitätsmedizin Berlin, Deutschland
| | - Dirk Beyersdorff
- Klinik und Poliklinik für Diagnostische und Interventionelle Radiologie und Nuklearmedizin, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Dirk Blondin
- Klinik für Radiologie, Gefäßradiologie und Nuklearmedizin, Städtische Kliniken Mönchengladbach GmbH Elisabeth-Krankenhaus Rheydt, Mönchengladbach, Germany.,Klinik für Radiologie, Gefäßradiologie und Nuklearmedizin, Städtische Kliniken Mönchengladbach, Germany
| | - Sascha Kaufmann
- Institut für Diagnostische und Interventionelle Radiologie, Siloah St. Trudpert Klinikum, Pforzheim, Deutschland
| | | | - Michael Quentin
- Centrum für Diagnostik und Therapie GmbH, Medizinisches Versorgungszentrum CDT Strahleninstitut GmbH, Köln, Germany
| | - Stefan Rödel
- Radiologische Klinik, Städtisches Klinikum Dresden, Germany
| | - Matthias Röthke
- Conradia Radiologie und Nuklearmedizin, Conradia Hamburg MVZ GmbH, Hamburg, Germany
| | | | - Lars Schimmöller
- Institut für Diagnostische und Interventionelle Radiologie, Universitätsklinikum Düsseldorf, Düsseldorf, Germany
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Park H, Kim SH, Lee Y, Son JH. Comparison of diagnostic performance between diffusion kurtosis imaging parameters and mono-exponential ADC for determination of clinically significant cancer in patients with prostate cancer. Abdom Radiol (NY) 2020; 45:4235-4243. [PMID: 32965517 DOI: 10.1007/s00261-020-02776-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 09/09/2020] [Accepted: 09/10/2020] [Indexed: 01/09/2023]
Abstract
PURPOSE To compare the diagnostic performance between diffusion kurtosis imaging (DKI) parameters and mono-exponential apparent diffusion coefficient (ADC) for determination of clinically significant cancer (CSC, Gleason score (GS) ≥ 7) in patients with histologically proven prostate cancer (PCa). METHODS A total of 92 patients (mean age: 71.5 years, range: 47-89 years) who had been diagnosed as PCa and undergone 3 T-MRI including DWI (b values, 0, 100, 1000, 2000s/mm2) were included in this study. The DKI parameters, namely apparent diffusion for non-Gaussian distribution (Dapp) and apparent kurtosis coefficient (Kapp), were calculated by dedicated software using mono-exponential and diffusion kurtosis models for quantitation. The measurement was performed for a whole tumor after segmentation, and pathologic topographic maps or systemic biopsy results served as the reference standard for segmentation. To compare the diagnostic performance of each parameter for determination of CSC, pair-wise comparison of receiver operating characteristic (ROC) curves was performed. RESULTS The study population consisted of GS 6 (n = 18), GS 7 (n = 31), GS 8 (n = 25), GS 9 (n = 15) and GS 10 (n = 3) patients. The area under the ROC curve of Kapp (0.707, 95% CI 0.603-0.798) for discriminating CSC from non-CSC was not significantly different from those of mono-exponential ADC (0.725, 0.622-0.813, P = 0.2175) or Dapp (0.726, 0.623-0.814, P = 0.9628). Diagnostic predictive values of Kapp were estimated to a maximum accuracy of 78%, a sensitivity of 86%, and a specificity of 47%, while those of mono-exponential ADC were 75, 81, and 53%, respectively. CONCLUSION The DKI parameters showed a diagnostic performance comparable to mono-exponential ADC for determination of CSC in patients with PCa.
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Affiliation(s)
- Hyungin Park
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Korea
| | - Seung Ho Kim
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Korea.
| | - Yedaun Lee
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Korea
| | - Jung Hee Son
- Department of Radiology, Haeundae Paik Hospital, Inje University College of Medicine, Haeundae-ro 875, Haeundae-gu, Busan, 48108, Korea
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