Papillary renal cell carcinoma showing high signal intensity on T2-weighted magnetic resonance images: radiological-pathological correlation

Pericardial cysts are uncommon and caused by an incomplete coalescence of fetal lacunae forming the pericardium. The paper presents two cases of pericardial cyst and literature review. The first is a case of a female patient with progressive dispnoa and spherical mass located in the right cardiophrenic angle on a chest x-ray. A pericardial cyst with low signal intensity was noted on T1w, high signal intensity on T2w in TSE (turbo spin echo) sequence on magnetic resonance images (MRI) which was suggestive of serous content. The patient underwent pericardial puncture and was thereafter free of symptoms. Histological study of the cyst confirmed hydatid cyst diagnosis. Another patient is with echocardiographic evidence of cystic formation which was confirmed on MRI, with high signal intensity on SSFP (steady state free precession) sequence. The cyst was without septa and without communication with pericardial space. Since there were no significant hemodynamic changes, the patient is on regular follow up.

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Colobomas of the Iris and Choroid and High Signal Intensity Cerebral Foci on T2-Weighted Magnetic Resonance Images in Klinefelter's Syndrome

Journal of Pediatric Ophthalmology & Strabismus ◽

10.3928/0191-3913-20040701-17 ◽

2004 ◽

Vol 41 (4) ◽

pp. 247-248 ◽

Cited By ~ 6

Author(s):

Melanie Barbara Boettger ◽

Klaus Kirchhof ◽

Consolato Sergi ◽

Christiane Sakmann ◽

Peter Meyer

Keyword(s):

Magnetic Resonance ◽

Signal Intensity ◽

Magnetic Resonance Images ◽

High Signal Intensity ◽

High Signal ◽

Klinefelter’S Syndrome ◽

Klinefelter's Syndrome

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Functional magnetic resonance imaging for distinguishing type of papillary renal cell carcinoma: a preliminary study

British Journal of Radiology ◽

10.1259/bjr.20201315 ◽

2021 ◽

Vol 94 (1126) ◽

pp. 20201315

Author(s):

Qingqiang Zhu ◽

Jing Ye ◽

Wenrong Zhu ◽

Jingtao Wu ◽

Wenxin Chen ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Magnetic Resonance ◽

Cell Carcinoma ◽

Renal Cell ◽

Mean Diffusivity ◽

Papillary Renal Cell Carcinoma ◽

Diffusion Kurtosis Imaging ◽

D Values

Objective: To investigate the feasibility of magnetic resonance diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) for distinguishing Type 1 and 2 of papillary renal cell carcinoma (PRCC). Methods: A total of Type 1 (n = 20) and Type 2 (n = 16) of PRCC were examined by pathology. For DKI and IVIM, mean diffusivity (MD), fractional anisotropy (FA), mean kurtosis (MK), kurtosis anisotropy (KA), radial kurtosis (RK), diffusivity (D), pseudodiffusivity (D*) and perfusion fraction (f) were performed in assessment of type of PRCC. Results: The mean SNRs of IVIM and DKI images at b = 1500 and 2000 s/mm2 were 8.6 ± 0.8 and 7.8 ± 0.6. Statistically significant differences were observed in MD and D values (1.11 ± 0.23 vs 0.73 ± 0.13, 0.91 ± 0.24 vs 0.49 ± 0.13, p < 0.05) between Type 1 and Type 2 of PRCC, while comparable FA, RK, D* and f values were found between Type 1 and Type 2 of PRCC (p > 0.05). Statistically significant differences were observed in MK and KA values (1.23 ± 0.16 vs 1.91 ± 0.26, 1.49 ± 0.19 vs 2.36 ± 0.39, p < 0.05) between Type 1 and Type 2 of PRCC. Areas of MD, MK, KA and D values under ROC curves for differentiating Type 1 and Type 2 of PRCC were 0.836, 0.818, 0.881 and 0.766, respectively. Using MD, MK, KA and D values of 0.93, 1.64, 1.94, 0.68 as the threshold value for differentiating Type 1 from Type 2 of PRCC, the best result obtained had a sensitivity of 85.0%, 80.0%, 90.0%, 85.0%, a specificity 75.0%, 68.7%, 87.5%, 81.2%, and an accuracy of 83.3%, 80.5%, 88.9%, 86.1%, respectively. Conclusion: DKI and IVIM are feasible techniques for distinguishing type of PRCC, given an adequate SNR of IVIM and DKI images. Advances in knowledge: 1. MD and D values are higher for Type 1 of PRCC and lower for Type 2 of PRCC. 2. MK and KA values are higher for Type 2 of PRCC and lower for Type 1 of PRCC. 3. DKI and IVIM can be used as clinical biomarker for PRCC type’s differential diagnosis, given an adequate SNR.

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Use of Histogram Analysis in Diffusion-Weighted Magnetic Resonance Imaging for Differentiation of Renal Tumor Subgroups

Iranian Journal of Radiology ◽

10.5812/iranjradiol.110963 ◽

2021 ◽

Vol In Press (In Press) ◽

Author(s):

Gurcan Erbay ◽

Mehmet Resit Goren ◽

Elif Karadeli ◽

Burcak Pekoz ◽

Zafer Koc ◽

...

Keyword(s):

Renal Cell Carcinoma ◽

Magnetic Resonance ◽

Cell Carcinoma ◽

Renal Cell ◽

Magnetic Resonance Images ◽

Histogram Analysis ◽

Renal Tumors ◽

Diffusion Weighted ◽

Adc Values ◽

The Mean

Background: The histopathological differentiation of renal neoplasms can be challenging via imaging. Objectives: To evaluate differences in histogram parameters on apparent diffusion coefficient (ADC) maps and to investigate the efficacy of histogram analysis in differentiation of oncocytomas from malignant renal neoplasm (MRN) subgroups. Patients and Methods: In this cross-sectional, retrospective study, the texture parameters of diffusion-weighted magnetic resonance images (DW-MRI) were evaluated in 65 patients with renal tumors (nine cases of oncocytoma and 59 cases of MRN) for a histological analysis. Results: A total of 68 lesions from 50 male and 15 female patients, with a median age of 55.4 years, were examined in this study. There were significant differences in the mean, median, and peak ADC values, as well as ADC percentiles, between the oncocytoma and MRN subgroups. Regarding the histopathological features of the lesions, 9 (11.5%) cases of oncocytomas, 23 (29.5%) cases of clear cell renal carcinoma (ccRCC), 14 (17.9%) cases of papillary renal cell carcinoma (pRCC), 12 (15.4%) cases of chromophobe renal cell carcinoma (chRCC), and 10 (12.8%) other tumors (including four cases of transitional cell carcinoma, four cases of non-Hodgkin’s lymphoma, and two cases of primitive neuroectodermal tumor) were identified. Significant differences were found in the mean and median ADC values between the oncocytoma, pRCC, chRCC, and other MRN subgroups. Moreover, significant differences were found in the mean and median ADC values between the ccRCC, pRCC, and chRCC subgroups. There were also significant differences in the percentiles of mean and median ADCs between oncocytomas and pRCC, chRCC, and other MRN subgroups. However, there were no significant differences in the mean and median ADCs (including the percentile histogram analysis) or the peak ADC between the oncocytoma and ccRCC groups. The mean, median, and percentile of ADC for renal masses were superior to kurtosis, skewness, and entropy. Conclusion: Although differentiation between ccRCC and oncocytoma was not possible by only measuring the mean, median, and peak ADC values, the histogram analysis of ADCs may improve differentiation between the MRN subgroups. Clearly, ADC cannot be used to differentiate between oncocytomas and MRNs.

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