Diagnostic performance of diffusion-weighted magnetic resonance imaging in differentiating human renal lesions (benignity or malignancy): a meta-analysis

Zhang, Hanmei; Gan, Qi; Wu, Yinghua; Liu, Rongbo; Liu, Xijiao; Huang, Zixing; Yuan, Fang; Kuang, Min

doi:10.1007/s00261-016-0790-z

Cited by 24 publications

(11 citation statements)

References 47 publications

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“…Die Überschneidungsbereiche der ADC-Werte zwischen Nierenläsionen sindje nach Studieunterschiedlich groß. In einer Metaanalyse aus dem Jahr 2016 wurden die höchsten mittleren ADC-Werte für Zysten gemessen (mittlerer ADC-Wert 2,97), gefolgt von ▪ normalem Gewebe (mittlerer ADC-Wert 2,48), ▪ Onkozytomen (mittlerer ADC-Wert 2,04), ▪ Transitionalzellkarzinomen (mittlerer ADC-Wert 1,94), ▪ Nierenzellkarzinomen (mittlerer ADC-Wert 1,80) und ▪ Angiomyolipomen (mittlerer ADC-Wert 1,37) [28].…”

Section: Merkeunclassified

Diffusionsbildgebung: Technik und klinische Anwendung

Kukuk¹,

Greschus²,

Goldstein³

et al. 2017

Radiologie up2date

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Section: Merkeunclassified

Diffusionsbildgebung: Technik und klinische Anwendung

Kukuk¹,

Greschus²,

Goldstein³

et al. 2017

Radiologie up2date

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“…DWI is effective for the detection and differential (10,11). Low-b-value DWI has a high sensitivity for lesion detection (12,13), and the ADC is an important parameter reflecting the characteristics of a lesion.…”

Section: Discussionmentioning

confidence: 99%

The value of multiparametric histogram features based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for the differential diagnosis of liver lesions

Han

Huang

et al. 2020

Ann Transl Med

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Background: The present study analyzed whole-lesion histogram parameters from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) to explore the clinical value of IVIM histogram features in the differentiation of liver lesions.Methods: In this retrospective study, 33 cases of hepatic hemangioma (HH), 22 cases of hepatic cysts (HC), and 34 cases of hepatocellular carcinoma (HCC) were underwent IVIM-DWI (b =0-600 s/mm 2 ), which were confirmed pathologically and clinically. The data were processed by IVIM model to obtain the following quantitative indicators: perfusion fraction (f), slow diffusion coefficient (D), and pseudo-diffusion coefficient (or fast diffusion coefficient, D*). The region of interest in the largest solid part of the lesion was delineated for histogram analysis of the correlation between tissue image and lesion type. The relevant histogram parameters were obtained and statistically analyzed. The characteristic histogram parameters for HH, HC, and HCC were compared to find significantly different parameters. The diagnostic efficacies of these parameters for HH, liver cysts, and HCC were assessed using the receiver operating characteristic (ROC) curves.Results: There were significant differences in the maximum diameter, maximum value, minimum value, mean, median, standard deviation, uniformity, skewness, kurtosis, volume, 10th percentile (P10) of D, and 90th percentile (P90) of D between the three groups (P<0.05). The maximum diameter, minimum value, entropy, and volume of D* differed significantly between the three groups (P<0.05). The maximum diameter, minimum value, mean, median, skewness, kurtosis, volume, P10, and P90 of f differed significantly between the three groups (P<0.05). The largest area under the ROC curve (AUC) for both D* and f was that of volume (AUC =0.883 for both). When 1438.802 was used as the volume cut-off, the sensitivity and specificity of volume in differentiating between HH and HC were 87.88 and 77.27, respectively, and the sensitivity and specificity of volume in differentiating between HC and HCC were 77.27 and 85.29. Conclusions:A multiparametric histogram from IVIM-DWI magnetic resonance imaging (MRI) is an effective means of identifying HH, HC, and HCC that provides valuable reference information for clinical diagnosis.

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“…Several studies have investigated the role of this imaging method in characterizing RCC. A meta-analysis of nine studies of DWI's ability to differentiate benign from malignant renal masses [29] demonstrated the significant difference of ADC, with pooled weighted sensitivity and specificity of 88% and 72%, respectively.…”

Section: Renal Cell Carcinomamentioning

confidence: 99%

Advances in medical imaging for the diagnosis and management of common genitourinary cancers

Bagheri

Ahlman

Lindenberg

et al. 2017

Urologic Oncology: Seminars and Original Investigations

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Medical imaging of the three most common genitourinary (GU) cancers—prostate adenocarcinoma, clear cell renal cell carcinoma (RCC), and urothelial carcinoma of the bladder—has evolved significantly during the past decades. The most commonly used imaging modalities for the diagnosis, staging, and follow-up of GU cancers are computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET). Multiplanar multidetector CT and multiparametric MRI (mpMRI) with diffusion-weighted imaging are the main imaging modalities for RCC and urothelial carcinoma, and while mpMRI is rapidly becoming the main imaging tool in the evaluation of prostate adenocarcinoma, biopsy is still required for diagnosis. Functional and molecular imaging using 18-fluorodeoxyglucose (FDG)-PET, and sodium fluoride (NaF)-PET are essential for the diagnosis, and especially follow-up, of metastatic GU tumors. This review will provide an overview of the latest advances in the imaging of these three major GU cancers.

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Diagnostic performance of diffusion-weighted magnetic resonance imaging in differentiating human renal lesions (benignity or malignancy): a meta-analysis

Cited by 24 publications

References 47 publications

Diffusionsbildgebung: Technik und klinische Anwendung

Diffusionsbildgebung: Technik und klinische Anwendung

The value of multiparametric histogram features based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) for the differential diagnosis of liver lesions

Advances in medical imaging for the diagnosis and management of common genitourinary cancers

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