scholarly journals MR imaging characteristics of uveal melanoma with histopathological validation

2021 ◽  
Author(s):  
Teresa A. Ferreira ◽  
Myriam G. Jaarsma-Coes ◽  
Marina Marinkovic ◽  
Berit Verbist ◽  
Robert M. Verdijk ◽  
...  
Keyword(s):  
Uveal Melanoma ◽  
Time Intensity Curve ◽  
Basal Diameter ◽  
Imaging Characteristics ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Good Technique ◽  
Perfusion Time ◽  
Magnetic Resonance Imaging Mri ◽  
Mri Characteristics

Abstract Purpose To evaluate the magnetic resonance imaging (MRI) characteristics of uveal melanoma (UM), to compare them with fundoscopy and ultrasound (US), and to validate them with histopathology. Methods MR images from 42 UM were compared with US and fundoscopy, and on 14 enucleated cases with histopathology. Results A significant relationship between the signal intensity on T1 and pigmentation on histopathology was found (p=0.024). T1 hyperintense UM were always moderately or strongly pigmented on histopathology, while T1-hypointense UM were either pigmented or non-pigmented. Mean apparent diffusion coefficient (ADC) of the UM was 1.16 ± 0.26 × 10−3 mm2/s. Two-thirds of the UM had a wash-out and the remaining a plateau perfusion time-intensity curve (TIC). MRI was limited in evaluating the basal diameter of flat tumors. US tends to show larger tumor prominence (0.5mm larger, p=0.008) and largest basal diameter (1.4mm larger, p<0.001). MRI was good in diagnosing ciliary body involvement, extrascleral extension, and optic nerve invasion, but limited on identifying scleral invasion. An increase of tumor prominence was associated with lower ADC values (p=0.030) and favored a wash-out TIC (p=0.028). An increase of tumor ADC correlated with a plateau TIC (p=0.011). Conclusions The anatomical and functional MRI characteristics of UM were comprehensively assessed. Knowing the MRI characteristics of UM is important in order to confirm the diagnosis and to differentiate UM from other intra-ocular lesions and because it has implications for treatment planning. MRI is a good technique to evaluate UM, being only limited in case of flat tumors or on identifying scleral invasion.

Characterization of tumefactive demyelinating lesions using MR imaging and in-vivo proton MR spectroscopy

2008 ◽  
Vol 15 (2) ◽  
pp. 193-203 ◽  
Author(s):  
HS Malhotra ◽  
KK Jain ◽  
A Agarwal ◽  
MK Singh ◽  
SK Yadav ◽  
...  
Keyword(s):  
Resonance Spectroscopy ◽  
Post Contrast ◽  
Open Ring ◽  
Apparent Diffusion ◽  
Demyelinating Lesions ◽  
Fluid Attenuated Inversion Recovery ◽  
Adc Values ◽  
Mri Characteristics

Background and Objectives Diagnosis of tumefactive demyelinating lesions (TDLs) is challenging to both clinicians and radiologists. Our objective in this study was to analyze and characterize these lesions clinically, biochemically, electrophysiologically, and on imaging. Methods A retrospective analysis with prospective follow-up of 18 cases of TDLs was performed. Imaging included T2-, T1-weighted, fluid-attenuated inversion recovery (FLAIR), post-contrast T1-weighted, diffusion weighted imaging (DWI), and proton magnetic resonance spectroscopy (PMRS). Results All the lesions appeared hyperintense on T2 and FLAIR images. Increased Apparent diffusion coefficient (ADC) (0.93–2.21 × 10−3 mm2/s) in centre of the lesion was seen in 14/18 cases; however, peripheral restriction (ADC values 0.55–0.64 × 10−3 mm2/s) was noted in 11/18 cases. In all, 13/18 cases showed contrast enhancement with open ring ( n = 5), complete ring ( n = 1), minimal ( n = 4), and infiltrative ( n = 3) pattern of enhancement. Nine of these 13 cases also showed venular enhancement. On PMRS, nine showed glutamate/glutamine (Glx) at 2.4 ppm. Conclusion Clinical features along with several MRI characteristics such as open ring enhancement, peripheral restriction on DWI, venular enhancement, and presence of Glx on spectroscopy may be rewarding in differentiating TDLs from neoplastic lesions.

Differentiation of prostate cancer and stromal hyperplasia in the transition zone with histogram analysis of the apparent diffusion coefficient

2017 ◽  
Vol 58 (12) ◽  
pp. 1528-1534 ◽  
Author(s):  
Liu Xiaohang ◽  
Zhou Bingni ◽  
Zhou Liangping ◽  
Peng Weijun ◽  
Yang Xiaoqun ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Transition Zone ◽  
B Value ◽  
Histogram Analysis ◽  
Apparent Diffusion ◽  
Adc Values ◽  
The Mean ◽  
Magnetic Resonance Imaging Mri

Background Prostate cancer and stromal hyperplasia (SH) in the transition zone (TZ) are difficult to discriminate by conventional magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI). Purpose To investigate the apparent diffusion coefficient (ADC) of prostate cancer and SH in the TZ with histogram analysis and the ability of ADC metrics to differentiate between these two tissues. Material and Methods Thirty-three cancer and 29 SH lesions in the TZ of 54 patients undergoing preoperative DWI (b-value 0, 1000 s/mm2) were analyzed. All the lesions on the MR images were localized based on histopathologic correlations. The 10th, 25th, and 50th percentiles, and the mean ADC values were calculated for the two tissues and compared. The efficiencies of the 10th, 25th, and 50th ADC percentiles in differentiating the two tissues were compared with that of the mean ADC with receiver operating characteristic (ROC) analysis. Results The 10th, 25th, and 50th percentiles and mean ADC values (×10−3 mm2/s) were 0.86 ± 0.15, 0.89 ± 0.16, 0.94 ± 0.16, and 1.03 ± 0.17 in SH and 0.64 ± 0.12, 0.69 ± 0.12, 0.72 ± 0.16, and 0.83 ± 0.15 in TZ cancer, respectively. The parameters were all significantly lower in cancer than SH. The 10th ADC percentile yielded an area under the ROC curve (AUC) of 0.87 for the differentiation of carcinomas from SH, which was higher than the mean ADC (0.80) ( P < 0.05), and the AUCs of the 25th (0.82) and 50th (0.83) percentiles exhibited no differences from those of the mean ADC ( P > 0.05). Conclusion Histogram analysis of ADC values may potentially improve the differentiation of prostate cancer from SH in the TZ.

Histogram analysis of volume-based apparent diffusion coefficient in breast cancer

2017 ◽  
Vol 58 (11) ◽  
pp. 1294-1302 ◽  
Author(s):  
Ga Eun Park ◽  
Sung Hun Kim ◽  
Eun Jeong Kim ◽  
Bong Joo Kang ◽  
Mi Sun Park
Keyword(s):  
Breast Cancer ◽  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Ductal Carcinoma ◽  
Histogram Analysis ◽  
Invasive Ductal Cancer ◽  
Diffusion Weighted Images ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Magnetic Resonance Imaging Mri

Background Breast cancer is a heterogeneous disease. Recent studies showed that apparent diffusion coefficient (ADC) values have various association with tumor aggressiveness and prognosis. Purpose To evaluate the value of histogram analysis of ADC values obtained from the whole tumor volume in invasive ductal cancer (IDC) and ductal carcinoma in situ (DCIS). Material and Methods This retrospective study included 201 patients with confirmed DCIS (n = 37) and IDC (n = 164). The IDC group was divided into two groups based on the presence of a DCIS component: IDC–DCIS (n = 76) and pure IDC (n = 88). All patients underwent preoperative breast magnetic resonance imaging (MRI) with diffusion-weighted images at 3.0 T. Histogram parameters of cumulative ADC values, skewness, and kurtosis were calculated and statistically analyzed. Results The differences between DCIS, IDC–DCIS, and pure IDC were significant in all percentiles of ADC values, in descending order of DCIS, IDC–DCIS, and pure IDC. IDC showed significantly lower ADC values than DCIS, and ADC50 was the best indicator for discriminating IDC from DCIS, with a threshold of 1.185 × 10–3 mm2/s (sensitivity of 82.9%, specificity of 75.7%). However, multivariate analysis of obtained ADC values showed no significant differences between DCIS, IDC–DCIS, and pure IDC ( P > 0.05). Conclusion Volume-based ADC values showed association with heterogeneity of breast cancer. However, there was no additional diagnostic performance in histogram analysis for differentiating between DCIS, IDC–DCIS, and pure IDC.

scholarly journals Two-kidney one-clip is a pertinent approach to integrate arterial hypertension in animal models of stroke: Serial magnetic resonance imaging studies of brain lesions before and during cerebral ischemia

2017 ◽  
Vol 38 (10) ◽  
pp. 1769-1780 ◽  
Author(s):  
Benjamin Ménard ◽  
Laurent Chazalviel ◽  
Simon Roussel ◽  
Myriam Bernaudin ◽  
Omar Touzani
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Arterial Hypertension ◽  
Brain Lesions ◽  
Cortical Lesions ◽  
Resonance Imaging ◽  
Spontaneously Hypertensive ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Magnetic Resonance Imaging Mri

Although chronic arterial hypertension (CAH) represents the major comorbid factor in stroke, it is rarely integrated in preclinical studies of stroke. The majority of those investigations employ spontaneously hypertensive rats (SHR) which display a susceptibility to ischemic damage independent of hypertension. Here, we used a renovascular model of hypertension (RH) to examine, with magnetic resonance imaging (MRI), brain alterations during the development of hypertension and after brain ischemia. We also examined whether MRI-derived parameters predict the extent of ischemia-induced brain damage. RH was induced according to the two-kidney one-clip model and multiparametric MRI was performed at 3, 6, 9, and 12 weeks after hypertension and also at 10, 50, and 60 min following stroke. Blood pressure values increased progressively and reached a plateau at 6 weeks after RH induction. At 12 weeks, all hypertensive animals displayed spontaneous brain lesions (hemorrhages, deep and cortical lesions, ventricular dilatation), increased apparent diffusion coefficient (ADC) values in the corpus callosum and higher fractional anisotropy in the cortex. Following ischemia, these animals showed larger brain lesions (406 ± 82 vs. 179 ± 36 mm3, p < 0.002) which correlated with ADC values at chronic stage of hypertension. This model of hypertension displays many characteristics of the neuropathology of human CAH. The use of this model in stroke studies is relevant and desirable.

scholarly journals Systematic review of imaging tests to predict the development of rheumatoid arthritis in people with unclassified arthritis

2021 ◽  
Author(s):  
Paola de Pablo ◽  
Jacqueline Dinnes ◽  
Sarah Berhane ◽  
Aya Osman ◽  
Zhia Lim ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Meta Analysis ◽  
Clinical Findings ◽  
Reference Standards ◽  
Imaging Characteristic ◽  
Diagnostic Thresholds ◽  
Imaging Characteristics ◽  
Study Heterogeneity ◽  
Magnetic Resonance Imaging Mri ◽  
Mri Characteristics

Objectives. To estimate and compare the diagnostic accuracy of magnetic resonance imaging (MRI) and ultrasound, for the prediction of rheumatoid arthritis (RA) in unclassified arthritis (UA). Methods. MEDLINE, Embase and BIOSIS were searched from 1987 to May 2019. Studies evaluating any imaging test in participants with UA were eligible. Reference standards were RA classification criteria or methotrexate initiation. Two authors independently extracted data and assessed validity using QUADAS-2. Sensitivities and specificities were calculated for each imaging characteristic and joint area. Summary estimates with 95% confidence intervals (CI) were estimated where possible. Results. Nineteen studies were included; 13 evaluated MRI (n=1,143; 454 with RA) and 6 evaluated ultrasound (n=531; 205 with RA). Studies were limited by unclear recruitment procedures, inclusion of patients with RA at baseline, differential verification, lack of blinding and consensus grading. Study heterogeneity largely precluded meta-analysis, however summary sensitivity and specificity for MRI synovitis in at least one joint were 93% (95% CI 88%, 96%) and 25% (95% CI 13%, 41%) (3 studies). Specificities may be higher for other MRI characteristics but data are limited. Ultrasound results were difficult to synthesise due to different diagnostic thresholds and reference standards. Conclusions. The evidence for MRI or ultrasound as single tests for predicting RA in people with UA is heterogeneous and of variable methodological quality. Larger studies using consensus grading and consistently defined RA diagnosis are needed to identify whether combinations of imaging characteristics, either alone or in combination with other clinical findings, can better predict RA in this population.

Benign and malignant skull-involved lesions: discriminative value of conventional CT and MRI combined with diffusion-weighted MRI

2018 ◽  
Vol 60 (7) ◽  
pp. 880-886 ◽  
Author(s):  
Zhanhai Tu ◽  
Zebin Xiao ◽  
Yingyan Zheng ◽  
Hongjie Huang ◽  
Libin Yang ◽  
...  
Keyword(s):  
Roc Curve ◽  
Mri Findings ◽  
Adc Value ◽  
Diffusion Weighted ◽  
Apparent Diffusion ◽  
Discriminative Value ◽  
Magnetic Resonance Imaging Mri ◽  
Mri Characteristics ◽  
Conventional Ct ◽  
Ct And Mri

Background Little is known about the value of computed tomography (CT) and magnetic resonance imaging (MRI) combined with diffusion-weighted imaging (DWI) in distinguishing malignant from benign skull-involved lesions. Purpose To evaluate the discriminative value of DWI combined with conventional CT and MRI for differentiating between benign and malignant skull-involved lesions. Material and Methods CT and MRI findings of 58 patients with pathologically proven skull-involved lesions (43 benign and 15 malignant) were retrospectively reviewed. Conventional CT and MRI characteristics and apparent diffusion coefficient (ADC) value of the two groups were evaluated and compared. Multivariate logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter separately and together. Results The presence of cortical defects or break-through and ill-defined margins were associated with malignant skull-involved lesions (both P < 0.05). Malignant skull-involved lesions demonstrated a significantly lower ADC ( P = 0.016) than benign lesions. ROC curve analyses indicated that a combination of CT, MRI, and DWI with an ADC ≤ 0.703 × 10–3 mm2/s showed optimal sensitivity, while DWI along showed optimal specificity of 88.4% in differentiating between benign and malignant skull-involved lesions. Conclusion The combination of CT, MRI, and DWI can help to differentiate malignant from benign skull-involved lesions. CT + MRI + DWI offers optimal sensitivity, while DWI offers optimal specificity.

scholarly journals Diffusion Weighted and Dynamic Contrast Enhanced Magnetic Resonance Imaging in Carcinoma of Cervix: Role of Apparent Diffusion Coefficient Value and Time Intensity Curve Pattern in Chemoradiotherapeutic Response Evaluation

2022 ◽  
Vol 9 (1) ◽  
pp. 17-27
Author(s):  
Raghavendra H K ◽  
Alpana Manchanda ◽  
Anju Garg
Keyword(s):  
Residual Tumor ◽  
Resonance Imaging ◽  
Intensity Curve ◽  
Time Intensity Curve ◽  
Dynamic Contrast Enhanced ◽  
Diffusion Weighted ◽  
Contrast Enhanced ◽  
Carcinoma Of Cervix ◽  
Apparent Diffusion ◽  
Adc Values

Introduction: Magnetic resonance imaging (MRI) is a widely used imaging modality in the imaging evaluation of carcinoma of cervix. The aim of our study was to evaluate the response in carcinoma cervix patients following chemoradiotherapy by Diffusion weighted (DW-MRI) and Dynamic contrast enhanced-MRI (DCE-MRI). Methods: 21 inoperable biopsy proven patients (mean age 48.43 years) of carcinoma cervix were included in the study. All patients underwent MRI (conventional, DW and DCE) of the pelvis thrice. Baseline MRI, Post chemotherapy MRI after neoadjuvant chemotherapy and Post chemoradiotherapy MRI after completion of concurrent chemoradiotherapy. Post treatment apparent diffusion coefficient(ADC) values and Time intensity curve(TIC) pattern were compared with baseline values. Results: Baseline meanADC value of all patients was 0.82 x10-3 mm2/s. After completion of treatment, 18 patients showed complete resolution of tumor and showed 0.50 x10-3 mm2/s increase in meanADC value from baseline MRI which was significantly higher than remaining 3 patients with residual tumor (0.50 x10-3 mm2/s v/s 0.17 x10-3 mm2/s). ADC threshold value of 1.15 x10-3 mm2/s was defined, differentiating the residual tumor from the healthy cervical tissue after chemoradiation. On post treatment MRI, 17 out of 18 patients with complete resolution of tumor showed increasing trend of enhancement on TIC and only one patient showed plateau pattern. 2 of the 3 patients with residual tumor showed washout pattern and one patient showed plateau pattern. Conclusion: ADC values and TIC pattern differ in patients with complete response to chemoradiotherapy from patients with residual tumor, so helps in differentiating residual tumor from cancer free cervix. Keywords: Carcinoma of cervix; Chemoradiotherapy; Diffusion weighted MRI; Dynamic contrast enhanced MRI; Time intensity curve.

scholarly journals Measurement of Apparent Diffusion Coefficient (ADC) Values of Ependymoma and Medulloblastoma Tumors: a Patient-based Study

2019 ◽  
Author(s):  
H Taheri ◽  
M B Tavakoli
Keyword(s):  
Diffusion Coefficient ◽  
Apparent Diffusion Coefficient ◽  
Pediatric Patients ◽  
Clinical Images ◽  
Adc Value ◽  
Conventional Mri ◽  
Apparent Diffusion ◽  
Adc Values ◽  
The Mean ◽  
Magnetic Resonance Imaging Mri

Background: aimed to compare the apparent diffusion coefficient (ADC) of two different cerebellar pediatric tumors, including ependymoma and medulloblastoma which have shown similar clinical images in conventional magnetic resonance imaging (MRI) methods.Material and Methods: Thirty six pediatric patients who were suspected to have the mentioned tumors according to their CT image findings were included in this study. The patients were subjected to conventional MRI protocols followed by diffusion weighted imaging (DWI) and ADC values of the tumors were calculated automatically using MRI scanner software.Results: The mean (± SD) ADC value for ependymoma (1.2± 0.06 ×10-3 mm2/s) was significantly higher than medulloblastoma (0.87 ± 0.02 ×10-3 mm2/s) (p = 0.041). Moreover, the maximum ADC value of ependymoma was considerably different in comparison with medulloblastoma (1.4 ×10-3 mm2/s and 0.96×10-3 mm2/s, respectively; p = 0.035) Furthermore, the minimum ADC value of ependymoma was higher compared to medulloblastoma (1.0 ×10-3 mm2/s and 0.61×10-3 mm2/s, respectively), but it was not significant (p = 0.067).Conclusion: Evaluation of ADC values for ependymoma and medulloblastoma is a reliable method to differentiate these two malignancies. This is due to different ADC values reflected during the evaluation.

Role of MRI in osteosarcoma for chemotherapy response evaluation and prediction: Correlation with histological necrosis

2009 ◽  
Vol 27 (15_suppl) ◽  
pp. 10540-10540
Author(s):  
J. Bajpai ◽  
S. Gamnagatti ◽  
V. Sreenivas ◽  
R. Phulia ◽  
M. Sharma ◽  
...  
Keyword(s):  
Multivariable Analysis ◽  
Relative Size ◽  
Chemotherapy Response ◽  
Response Evaluation ◽  
Time Intensity Curve ◽  
Dce Mri ◽  
Receiver Operating Characteristic Curves ◽  
Apparent Diffusion ◽  
Treatment Naïve ◽  
Magnetic Resonance Imaging Mri

10540 Background:Histologic necrosis (HN), the current gold standard for response evaluation in osteosarcoma (OS), is accessible only after neoadjuvant chemotherapy (NACT) and may get affected by confounding factors. Thus, it would be useful to have surrogate markers of response evaluation and prognostication using magnetic resonance imaging (MRI) to individualize therapy. Method:Thirty-one treatment naïve OS patients received 3 cycles of NACT followed by surgery during 2006–2008. All patients underwent baseline and post-NACT conventional(C), diffusion-weighted (DW) and dynamic contrast enhanced (DCE) MRI. Taking ‘Huvos grading’ (good response >/= 90% HN) as reference standard, various parameters of MRI were compared with it. Tumor considered as ellipsoidal; volume (V), average tumor plane (ATP) and relative(r)-ATP (ATP/body surface area) were calculated using standard formula for ellipse. Receiver operating characteristic curves were generated to assess the best threshold and predictability. Sensitivity and specificity were calculated along with 95% confidence limits. After deriving thresholds for each parameter in univariable analysis, multivariable analysis was carried out. Results: Both pre-and post NACT, absolute and relative size parameters were well correlated with HN, though post NACT change in parameters did not. Apparent diffusion coefficient (ADC), either pre-and post NACT measurements or change following chemotherapy were not correlating well. However, on adjusting for volume, significant correlation was found. Thus, we could derive a new parameter diffusion per unit volume (DV= ADC /V). Change in shape of time intensity curve did not show significant correlation. Conclusions: In OS, NACT response can be assessed and predicted by conventional and DW- MRI early in the disease course which correlates well with HN. DV seems to be a sensitive substitute for response evaluation. For DCE-MRI, more sophisticated models in future studies might be useful. [Table: see text] No significant financial relationships to disclose.

scholarly journals Accuracy of apparent diffusion coefficient values and magnetic resonance imaging in differentiating suprasellar germinomas from chiasmatic/hypothalamic gliomas

2020 ◽  
Vol 33 (3) ◽  
pp. 201-209
Author(s):  
Theeraphol Panyaping ◽  
Piyakarn Taebunpakul ◽  
Oranan Tritanon
Keyword(s):  
Magnetic Resonance Imaging ◽  
Diffusion Coefficient ◽  
Magnetic Resonance ◽  
Apparent Diffusion Coefficient ◽  
Pituitary Gland ◽  
Contrast Enhancement ◽  
Resonance Imaging ◽  
Apparent Diffusion ◽  
Adc Values ◽  
Mri Characteristics

Objective The aim of this study was to differentiate suprasellar germinomas from chiasmatic/hypothalamic gliomas (CHGs) using apparent diffusion coefficient (ADC) values and magnetic resonance imaging (MRI) characteristics. Materials and methods A cross-sectional study was conducted on 11 patients with suprasellar germinomas and 11 patients with CHGs who underwent pretreatment MRI. The ADC values (minimum and average ADC values) of the tumors were measured and the MRI characteristics were evaluated. Results The average and minimum ADC values of suprasellar germinomas were significantly lower than those of CHGs ( p = 0.016 and 0.004 respectively). The selection of 941.15 × 10−6 mm2/s as a cutoff value of the minimum ADC value was used to differentiate suprasellar germinomas and CHGs; the best results were obtained with area under the curve of 0.889, sensitivity of 87.5%, specificity of 77.8% and accuracy of 82.4%. MRI characteristics suggested the diagnosis of suprasellar germinomas were T2W hypointensity and involvement of pituitary gland and/or stalk. MRI characteristics suggested the diagnosis of CHGs was higher degree of contrast enhancement and presence of macrocysts. Conclusion ADC values have a role in differentiating suprasellar germinomas and CHGs, especially when imaging findings on conventional MRI are inconclusive. Furthermore, some MRI features are in favor of differentiation between these tumor entities including tumor location, cyst pattern, T2W hypointensity, degree of contrast enhancement, stalk and pituitary gland involvement.

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