Mean ADC Value Research Articles

Cribriform Pattern of The Prostate Adenocarcinoma: Sensitivity of Multiparametric MRI.

The aim of this study was to investigate the diagnostic performance of mpMRI for detecting cribriform pattern prostate cancer. This study retrospectively enrolled 33 patients who were reported cribriform pattern prostate cancer at final pathology. The localization, grade and volumetric properties of the dominant tumors and areas with cribriform pattern at the final pathological specimens were recorded and the diagnostic value of mpMRI was evaluated on the basis of the cribriform morphology detection rate. It was analyzed using Wilcoxon test, the Chi-square test and Fisher's Exact test. The significance level (P-value) was set at .05 in all statistical analyses. A total of 58 prostate cancer foci were (38 cribriform, 20 non-cribriform foci) identified on the final pathology. mpMRI identified 36 of the 38 cribriform morphology harboring tumor foci with a sensitivity of 94.7% (95% confidence interval 82.7-98.5%). In 17 of the 33 patients mpMRI detected single lesion and for these lesions; mpMRI identified cribriform morphology positive areas precisely in 15 patients with significantly low ADCmean and ADCmin values compared to the non-cribriform cancer areas within the primary index lesion (P < .001). For the remaining 16 patients with multiple lesions; all of the tumor foci that harboring cribriform morphology were identified by mpMRI but in none of them any ADCmean and ADCmin value divergence were detected between the cribriform and non-cribriform pattern tumor foci within the primary index lesion. Cribiform pattern should be considered in single lesions with an area of lower ADC value on mpMRI.

Comparison of conventional and higher-resolution reduced-FOV diffusion-weighted imaging of breast tissue.

Reduced FOV-diffusion-weighted imaging (rFOV-DWI) allows for acquisition of a tissue region without back-folding, and may have better fat suppression than conventional DWI imaging (c-DWI). The aim was to compare the ADCs obtained with c-DWI bilateral-breast imaging with single-breast rFOV-DWI. Breasts of 38 patients were scanned at 3T. The mean ADC values obtained for 38 lesions, and fibro-glandular (N = 35) and adipose (N = 38) tissue ROIs were compared between c-DWI and higher-resolution rFOV-DWI (Wilcoxon rank test). Also, the ADCs were compared between the two acquisitions for an oil-only phantom and a combined water/oil phantom. Furthermore, ghost artifacts were assessed. No significant difference in mean ADC was found between the acquisitions for lesions (c-DWI: 1.08 × 10-3 mm2/s, rFOV-DWI: 1.13 × 10-3 mm2/s) and fibro-glandular tissue. For adipose tissue, the ADC using rFOV-DWI (0.31 × 10-3 mm2/s) was significantly higher than c-DWI (0.16 × 10-3 mm2/s). For the oil-only phantom, no difference in ADC was found. However, for the water/oil phantom, the ADC of oil was significantly higher with rFOV-DWI compared to c-DWI. Although ghost artifacts were observed for both acquisitions, they appeared to have a greater impact for rFOV-DWI. However, no differences in mean lesions' ADC values were found, and therefore this study suggests that rFOV can be used diagnostically for single-breast DWI imaging.

Dynamic Contrast-Enhanced MRI Parameters and Normalized ADC Values Could Aid Differentiation of Skull Base Osteomyelitis from Nasopharyngeal Cancer.

The skull base osteomyelitis sometimes can be difficult to distinguish from nasopharyngeal cancer. This study aimed to investigate the differences between skull base osteomyelitis and nasopharyngeal cancer using dynamic contrast-enhanced MR imaging and normalized ADC values. This study included 8 and 12 patients with skull base osteomyelitis and nasopharyngeal cancer, respectively, who underwent dynamic contrast-enhanced MR imaging and DWI before primary treatment. Quantitative dynamic contrast-enhanced MR imaging parameters and ADC values of the ROIs were analyzed. Normalized ADC parameters were calculated by dividing the ROIs of the lesion by that of the spinal cord. The rate transfer constant between extravascular extracellular space and blood plasma per minute (Kep) was significantly lower in patients with skull base osteomyelitis than in those with nasopharyngeal cancer (median, 0.43 versus 0.57; P = .04). The optimal cutoff value of Kep was 0.48 (area under the curve, 0.78; 95% CI, 0.55-1). The normalized mean ADC was significantly higher in patients with skull base osteomyelitis than in those with nasopharyngeal cancer (median, 1.90 versus 0.87; P < .001). The cutoff value of normalized mean ADC was 1.55 (area under the curve, 0.96; 95% CI, 0.87-1). The area under the curve of the combination of dynamic contrast-enhanced MR imaging parameters (Kep and extravascular extracellular space volume per unit tissue volume) was 0.89 (95% CI, 0.73-1), and the area under the curve of the combination of dynamic contrast-enhanced MR imaging parameters and normalized mean ADC value was 0.98 (95% CI, 0.93-1). Quantitative dynamic contrast-enhanced MR imaging parameters and normalized ADC values may be useful in differentiating skull base osteomyelitis and nasopharyngeal cancer. The combination of dynamic contrast-enhanced MR imaging parameters and normalized ADC values outperformed each measure in isolation.

Magnetic Resonance Imaging Appearance of Giant Intracerebral Tuberculoma: A Retrospective Analysis

Background: Giant intracerebral tuberculomas are rare lesions but should be considered in the differential diagnosis of intracranial space-occupying lesion in an endemic region.Objective: The purpose of this study is to analyze the clinical data and magnetic resonance imaging (MRI) findings of giant intracerebral tuberculomas to improve the diagnostic precision.Material and Methods: The clinical and MRI findings of 22 patients of giant intracerebral tuberculoma were analyzed retrospectively. For the statistical analysis independent sample Student t-test was used.Results: For 22 patients included in this sample the giant intracerebral tuberculoma was of size more than 2.5cm. The majority of the giant tuberculomas (19 patients (86.4%))was located in the supratentorial area.T2-weighted hypointense core of giant tuberculoma was observed in 12 patients (54.5%) and T1 hyperintensities were observed in peripheral (wall) of the giant tuberculoma in 14 patients (63.6%). The mean ADC value of the peripheral (wall) of the giant tuberculoma was 1.034± 0.466[SD] x 10-3mm2/s and the core was 0.994± 0.455[SD] x 10-3mm2/s with a statistically significant difference (p-value &lt;0.0005) in between. MR spectroscopy showed raised lipid peak at 0.9 to 1.33 ppm in 10 patients (45.5%),raised lipid-lactate peak in 12 patients (54.5%),raised Choline/Cr ratio more than 1.2 in 14 patients(63.6%) and Choline/Cr ratio less than 1.2 in 5 patients (22.7%). Associated involvement of lung was observed in the 6patients (27.3%), cervical lymph node in 1 patient (4.5%) and spine in 1patient (4.5%).Conclusions: MRI plays a vital role in distinguishing giant intracerebral tuberculomas from other intracranial space-occupying lesions, thereby allows the early institution of anti-tubercular treatment (ATT), decreased patient morbidity, mortality, and prevents unnecessary neurosurgical excision.

The role of ADC value and Ki-67 index in predicting the response to neoadjuvant chemotherapy in advanced stages of olfactory neuroblastoma.

To investigate the efficacy of pretreatment ADC and Ki-67 index in the prediction of the response to neoadjuvant chemotherapy (NACT) in advanced olfactory neuroblastoma (ONB) patients. A total of 21 advanced ONB patients (mean 43.48 years ± 14.26; range 25-69 years; 13 men and 8 women) with diffusion-weighted imaging (DWI) before NACT between June 2015 and October 2021 were retrospectively analyzed. Patients were categorized into responders and non-responders according to RECIST 1.1 after two cycles of NACT. The clinical data, ADCmean value, and Ki-67 index were analyzed. Kadish stage, ADCmean value, and Ki-67 index showed statistical significance between responders and non-responders. Patients with Kadish C stage were more likely to respond to platinum-based NACT (p = 0.035). Patients with the lower ADCmean value showed response to NACT (p = 0.002) and the cutoff point was 1.04 × 10-3 mm2/s. Patients with the higher Ki-67 index showed response to NACT (p = 0.003) and the cutoff point was 17.5%. Predictive performance of Ki-67 index and ADCmean value showed no significance between responders and non-responders (p = 0.865). A significant negative correlation was found between ADCmean value and Ki-67 index (r = -0.539, p = 0.038). The pretreatment ADCmean value, Ki-67 index and Kadish stage have the potential to predict the response to NACT in advanced ONB patients. This is the first study that investigated the feasibility of DWI in predicting the response to NACT in ONB patients and showed that Kadish stage, pretreatment ADCmean and Ki-67 index may play an important role in the prediction.

Diffusion weighted hyperpolarized 129 Xe MRI of the lung with 2D and 3D (FLORET) spiral.

To enable efficient hyperpolarized 129 Xe diffusion imaging using 2D and 3D (Fermat Looped, ORthogonally Encoded Trajectories, FLORET) spiral sequences and demonstrate that 129 Xe ADCs obtained using these sequences are comparable to those obtained using a conventional, 2D gradient-recalled echo (GRE) sequence. Diffusion-weighted 129 Xe MRI (b-values=0, 7.5, 15 s/cm2 ) was performed in four healthy volunteers and one subject with lymphangioleiomyomatosis using slice-selective 2D-GRE (scan time=15 s), slice-selective 2D-Spiral (4 s), and 3D-FLORET (16 s) sequences. Experimental SNRs from b-value=0 images ( ) and mean ADC values were compared across sequences. In two healthy subjects, a second b=0 image was acquired using the 2D-Spiral sequence to map flip angle and correct RF-induced, hyperpolarized signal decay at the voxel level, thus improving regional ADC estimates. Diffusion-weighted images from spiral sequences displayed image quality comparable to 2D-GRE and produced sufficient (16.8 ± 3.8 for 2D-GRE, 21.2 ± 3.5 for 2D-Spiral, 20.4 ± 3.5 for FLORET) to accurately calculate ADC. Whole-lung means and SDs of ADC obtained via spiral were not significantly different (P > 0.54) from those obtained via 2D-GRE. Finally, 2D-Spiral images were corrected for signal decay, which resulted in a whole-lung mean ADC decrease of ˜15%, relative to uncorrected images. Relative to GRE, efficient spiral sequences allow 129 Xe diffusion images to be acquired with isotropic lung coverage (3D), higher (2D and 3D), and three-fold faster (2D) within a single breath-hold. In turn, shortened breath-holds enable flip-angle mapping, and thus, allow RF-induced signal decay to be corrected, increasing ADC accuracy.

Value of diffusion-weighted magnetic resonance imaging (DWI) in differentiating orbital lymphoma from idiopathic orbital inflammatory pseudotumor

BackgroundDiffusion-weighted MR imaging can provide physiological information complementing morphological findings from conventional MRI. It detects early tissue changes associated with changes in water content, such as changes in the permeability of cell membranes, cell swelling or cell lysis. Areas of diseased tissue are highlighted with increased signal intensity on diffusion-weighted MR imaging. A decrease in the ADC is expected with increased intracellular tissue caused by either cell swelling or increased cellular density. DWI can be performed without the need for the administration of exogenous contrast medium, so it may of use when contrast administration is contraindicated. It yields quantitative and qualitative information that reflects changes at the cellular level and indicates the integrity of cell membranes. The purpose of this study was mainly to assess the diagnostic value of DWI for the discrimination of orbital lymphoma from idiopathic orbital inflammatory pseudotumor.ResultsOf our 53 cases presented with proptosis or visual disturbances, 32 cases (60.4%) had found to be present with idiopathic orbital inflammatory pseudotumor and 21 cases (39.6%) had orbital lymphoma. On conventional MR imaging, ill-defined tumor margin and orbital preseptal space involvement had a significant association with orbital lymphoma, whereas intense post-contrast enhancement of lesion and radiologic evidence of sinusitis were associated with orbital inflammatory pseudotumor. The mean ADC value of orbital lymphoma was significantly lower than those of benign inflammatory pseudotumor, yielding 100% sensitivity, 99% specificity, and 90.5% accuracy for differentiating both entities.ConclusionsDiffusion-weighted MR imaging (DWI) is valuable in discriminating orbital inflammatory pseudotumor from malignant orbital lymphoma that help patients to initial management.

Early Prediction Model of Radiation-Induced Xerostomia Based on Radiomics during Radiotherapy for Nasopharyngeal Carcinoma

<h3>Purpose/Objective(s)</h3> Radiation-induced xerostomia remains one of common side effects for radiotherapy (RT) of nasopharyngeal carcinoma (NPC) and severely affects the quality of life. Early prediction of xerostomia is extremely important, but few studies mention it. We aim to build the early prediction model of xerostomia based on radiomics during RT by artificial intelligence for NPC patients. <h3>Materials/Methods</h3> Seventy-five pathologically confirmed squamous NPC patients were prospectively enrolled in our institution. All patients received a total radiation dose of 66 to 70Gy in 33 fractions at 5 fractions per week using Image-guided intensity modulated radiotherapy (IGRT). The patients received 3-5 cycles of cisplatin-based chemotherapy. MR images with T2-weighted (T2WI), contrast-enhanced T1-weighted (CE-T1WI) and diffusion-weighted imaging (DWI) (b = 0, 500, 800 s/mm²) were acquired on 3.0T MRI. RTOG criteria was used to evaluate xerostomia at 3 months after the completion of radiation. Delivered radiation dose of bilateral parotid and submandibular glands, MR images were collected at pre-RT, 5^th, 15^th fractions and immediately post-RT, respectively. Bilateral parotid and submandibular glands were delineated as the regions of interest (ROI) on CE-T1WI, T2WI, and DWI. We extracted a variety of features from all the images, and selected the optimal features combination by variance analysis. We built the prediction model by support vector machine (SVM). Receiver-operating characteristic (ROC) curve was used to evaluate predictive performance. <h3>Results</h3> The average age was 44.88 years (23-79 years). 24 were female and 51 were male. The mean ADC values of parotid and submandibular glands increased gradually during radiotherapy. Furthermore, the mean ADC values of salivary glands began to increase at 5^th fractions with minimal volume change. For xerostomia, 34 patients with G3-5 were categorized as toxicity cases, and 41 patients with G0-2 were classified as non-toxicity cases. Based on radiomics, clinical characteristics (sex, age, 8^th TNM staging) and radiation dose, we built 15 prediction models. Among them, the best prediction model consists of radiation dose, clinical parameters and ΔRF (the delta-radiomics features from pre-RT to 5^th fractions) which includes 6 ipsilateral parotid features, 8 contralateral parotid features, 7 ipsilateral submandibular features, and 7 contralateral submandibular features. The area under ROC curve is 0.7641, with a precision of 0.7444, a sensitivity of 0.7238, and a specificity of 0.8424. <h3>Conclusion</h3> Early prediction model including delta-radiomics, radiation dose, and clinical parameters exhibits superior sensitivity and specificity. This is an effective model for predicting xerostomia during the early stage of RT, and the clinicians could use it to adjust the treatment strategy and reduce the damage to salivary glands.

Mean and Normalized Apparent Diffusion Coefficient Values and Mean Metabolic Ratios in Cerebral Metastases in Central Indian Rural Hospital Setup

Background: To evaluate mean metabolite ratios and Apparent diffusion co-efficient value with normalization in cerebral metastases using MRS in rural hospital setup in Central India. Method: A cross sectional hospital based observational study conducted over a time period of 2 years. All the cases registered with Acharya Vinoba Bhave Rural Hospital, Sawangi, Wardha, diagnosed on histopathological findings as cerebral metastases were included in this present study. All patients were examined on GE Brivo MRI machine with 1.5 Tesla magnetic field strength in the Department of Radiodiagnosis using b value of 1000 s/sq. mm, slice thickness 5mm, interslice gap 2mm applied in the x, y and z axes, central as well as peripheral portions of the tumor were manually sampled, preferably getting rid of cystic or necrotic areas. Histopathological diagnostic acumen was augmented with ADC values with normalization. Result: Range of ADC values observed was from 0.683 10-3 mm2/s to 0.873 10-3 mm2/s. Normalized ADC values were calculated on basis of observed ADC values and were in range of 0.8537510-3 mm2/s to 1.09125 10-3 mm2/s. Mean ADC value was calculated as 0.749 x 10-3 mm2/s. Mean normalised ADC value was calculated to be 0.9372 x 10-3 mm2/s. Observed metabolite ratios were derived from metabolic values obtained on MRS for Choline, Creatinine, Lipid lactate, myoinositol and n-acetyl aspartate. Range for Choline:Creatinine, Choline:n-acetyl aspartate, choline : myoinositol and choline : lipid lactate was 3.97 to 5.73, 3.24 to 5.76, 4.35 to 5.49 and 0.32 to 0.997 respectively. Mean values for Choline:Creatinine, Choline:n-acetyl aspartate, choline : myoinositol and choline : lipid lactate were 4.1289, 3.7838, 4.1256 and 0.9095 respectively. Conclusion: Research gap analysis towards which research question was framed stands filled up by the generated new knowledge in terms of 'Mean metabolite ratios','Apparent Diffusion Coefficient' and 'Normalised Apparent Diffusion Coefficient' values for cerebral metastases in the present study.

High-risk breast lesions: role of multi-parametric DCE-MRI in detection and histopathological upgrade prediction

BackgroundHigh-risk breast lesions represent 3–21% of all breast lesions and are non-obligate precursors of malignancy. Various studies have evaluated the value of DCE-MRI including DWI and ADC mapping in the detection of high-risk breast lesions, differentiating them from malignant lesions and predicting upgrade risk after surgical excision reducing misdiagnosis and overtreatment. This study is a retrospective review of all image-guided breast biopsy procedures performed in 2021 at our institution, identified 68 patients with histopathologically proven high-risk breast and available MRI examinations with no concurrent ipsilateral malignancy. Image analysis of MRI examinations included morphological criteria, enhancement pattern, dynamic curves, DWI and ADC mapping assessment. Since our knowledge of high-risk breast lesions is still growing, this study is important to evaluate the merits of DCE-MRI in the assessment of high-risk breast lesions, to allow optimization of treatment, better limit it to those women at risk, and avoid overtreatment in women at low risk.ResultsThe mean ADC value of high-risk breast lesions was not significantly different from that of malignant breast lesions (p value = 0.015). Non-mass enhancement and type III enhancing curve proved to be significant indicators of high-risk breast lesions upgrade in surgical pathology. Cut-off average ADC value for differentiating upgraded high-risk lesions from non-upgraded high-risk lesions proved 1.24 mm2/sec with sensitivity and specificity of 94 & 100%, respectively.DiscussionManagement of high-risk breast lesions is important in the screening setting, as they are non-obligate precursors of malignancy, and also function as risk indicators. Frequency and upgrade rates of high-risk lesions detected by MRI provide a reference for clinical management. DCE-MRI has a high negative predictive value in predicting the upgrade risk of high-risk lesions. In this study, non-mass enhancement and type III curve were proven to be indicators of high-risk lesion upgrade. Limitations of the study included small number of patients and limited follow-up period.ConclusionsThe use of multi-parametric DCE-MRI including DWI and ADC mapping provides complementary information to detect high-risk breast lesions and predict their upgrade rate.

Differentiation between atypical sinonasal non-Hodgkin's lymphoma and inverted papilloma

To seek additional magnetic resonance imaging (MRI) features to improve the accuracy of differentiation between atypical sinonasal non-Hodgkin's lymphoma (NHL) and inverted papilloma (IP) using conventional MRI and apparent diffusion coefficient (ADC) maps. MRI examinations from 44 atypical cases (21 NHLs and 23 IPs) in sinonasal regions were reviewed retrospectively. Imaging features included tumour laterality, extension, T1-weighted imaging (WI)/T2WI signal intensity homogeneity and ratios, enhancement homogeneity and ratios, and ADCmean. In cases of NHL, homogeneous signal intensity was often observed on T2WI, which was homogeneous and significantly less enhanced than the turbinate, with lower ADCmean. Whereas in IPs, heterogeneous signal intensity was seen on T2WI, which was heterogeneous and of comparable enhancement to the turbinate, and higher ADCmean values were commonly seen. An ADCmean cut-off point of 1.10×10-3 mm2/s achieved 100% sensitivity, 90% specificity, and 90% accuracy. In addition, special features were observed that support the distinction between the two tumours, including intestinal pattern enhancement in NHL and spot-like appearance on T2WI and enhancement in IP. ADCmean was the most valuable metric for differentiating between the atypical sinonasal NHLs and IPs.

Preoperative Assessment and Prediction of Consistency of Intracranial Meningioma Utilizing the Apparent Diffusion Coefficient Values

Abstract Objectives Consistency of meningioma is important for preoperative planning, surgical resection, and predicting surgical outcomes. We prospectively evaluated the utility of the apparent diffusion coefficient (ADC) values to assess the consistency of meningioma. Methods Preoperative magnetic resonance imaging (MRI) was performed on 23 patients with meningioma before undergoing surgical resection and the average/mean of ADC minimum (ADCmin), maximum (ADCmax), and mean (ADCmean) values were calculated. Intraoperatively, the meningiomas were characterized as firm or soft and correlated with ADC values. Results ADCmin, ADCmax, and ADCmean values of soft and firm meningiomas were significantly different with a p-value of &lt; 0.05. ADCmin value of &lt; 691.3 × 10−6 mm2/s had 80% sensitivity and 84.6% specificity for identifying firm from the soft tumors with the area under the curve (AUC) = 0.862, p-value of 0.004, positive predictive value (PPV) 80, and negative predictive value (NPV) 84.6. ADCmax value of &lt; 933.6 × 10−6 mm2/s had 70% sensitivity and 84.6% specificity for identifying firm from the soft tumors with AUC = 0.823, p-value of 0.009, PPV 77.8, and NPV 78.6. ADCmean value of &lt; 840.8 × 10−6 mm2/s had 90% sensitivity and 76.9% specificity for identifying firm from the soft tumors with AUC = 0.900, p-value of 0.001, PPV 75, and NPV 90.9. Conclusion Diffusion-weighted MRI using ADC minimum, ADC maximum, and ADC mean values can be used to differentiate firm from soft meningiomas. Meningiomas with hard consistency showed relatively low ADC values.

Histogram-based diffusion metrics for differentiation of benign &amp;malignant gynecologic lesions

Purpose: To evaluate the ability of ADC based histogram parameters to differentiate between benign and malignant gynecologic lesions. Results: The study was performed on 100 cases having 66 benign lesions &amp;34 malignant lesions which were pathologically proved. There was statistically significant difference between benign and malignant lesions on qualitative diffusion weighted. The range of traditional partial slice mean ADC parameter for benign masses was (1.095 ± 0.315 x 10−3 mm2/s) and for malignant lesions was (0.791 ± 0.244 x 10−3 mm2/s) which was lower than the values of the benign lesions. there was statistically significant difference as regard mean and minimum ADC values (P = 0.01*, ) The cutoff mean &amp;minimum ADC values used to differentiate benign lesions from malignant lesions were 0.905 &amp; 0.680 x 10-3 mm2/s, respectively. We found that The sensitivity, specificity and accuracy of partial slice mean ADC were higher than histogram mean ADC. Conclusions: Mean &amp; minimum ADC can differentiate between benign and malignant gynecologic lesions with less diagnostic performance than traditional partial slice mean ADC.

Impact of Adding Mean Apparent Diffusion Coefficient (ADCmean) Measurements to O-RADS MRI Scoring For Adnexal Lesions Characterization: A Combined O-RADS MRI/ADCmean Approach

Evaluate the impact of adding mean apparent diffusion coefficient (ADCmean) measurements to the Ovarian-Adnexal Imaging Reporting and Data System MRI (O-RADS MRI) scoring for adnexal lesion characterization using a combined O-RADS MRI/ADCmean reading approach. This prospective study included 90 women who underwent pelvic MRI for adnexal lesions diagnosis and characterization. Two readers scored the adnexal lesions using the O-RADS MRI scoring independently and in consensus. A third reader calculated ADCmean measurements. The final diagnoses were determined by histo-pathology (n = 77) or follow-up imaging (n = 13). Areas under the curves (AUCs) and diagnostic performance metrics were calculated for the O-RADS MRI scoring, ADCmean, and combined O-RADS MRI/ADCmean thresholds. P-value <0.05 was significant. 116 adnexal lesions (71 benign, 45 malignant) were analyzed. The optimal thresholds to predict malignant adnexal lesions were O-RADS MRI score >3 and ADCmean value ≤1.08×10-3 mm2/s (AUC 0.926 and 0.823; sensitivity 97.7% and 95.5%; specificity 87.3% and 68%; positive predictive value (PPV) 83% and 66.2%; positive likelihood ratio (PLR) 7.7 and 3.08, respectively). Compared to the O-RADS MRI scoring, a combined threshold of O-RADS MRI >3/ADCmean ≤1.08×10-3 mm2/s, yielded a reduction of false positives, a significant increase in the specificity (97.1%, p=0.005), PPV (95.4%, p=0.002), and PLR (33.1, p <0.0001), and non-significant change in the AUC (0.953, p=0.252), and sensitivity (93.3%, p=0.467). The diagnostic performance of O-RADS MRI scoring to characterize adnexal lesions could be improved by adding the ADCmean values through reducing false positives, increasing specificity, and maintaining good sensitivity.

The Role of Multidirectional Diffusion Weighted Imaging in the diagnosis of breast carcinoma in Magnetic Resonance Imaging.

Background: Magnetic resonance imaging (MRI) is increasingly used in breast imaging. Diffusion imaging (DWI) is used in conjunction with contrast enhanced series. There will be a signal difference between the stationary and moving water molecules in DWI, due to the fact that all molecules will receive a first gradient pulse and then another pulse at the 180 degree-reverse direction of the first one. The stationary molecules will have zero signal after the two of the pulses and show restriction (low signal). Whereas, the moving molecule will not be at the same location and escape from the 180 degree pulse and have an energy in the end of the gradients. Multidirectional Diffusion-Weighted Imaging (MDDWI) gives information signifying water’s capacity to move freely in a direction according to its physiological and pathological boundaries, which is referred to as fractional anisotropy (FA). This study aimed to determine the usefulness of FA maps in in differentiating benign and malignant breast lesions. Methods: The patients had breast MRI including MDDWI series and went through pathological evaluation (Seventy-nine patients with 86 lesions) were included in the study. The FA values were measured in addition to the conventional Diffusion-ADC values. Also, diffusion restriction and pathology results were noted. The lesion FA and ADC values, diffusion assessment, and pathology results were compared using the Student t-test. Results: The patients were between 23 and 76 years and mean age for benign lesions was 43.9 whereas, it was 50.4 for the malignant lesions. Fourty-five patients had benign lesions and 41 had malignant. Mean ADC values were significant between benign and malignant lesions (correspondingly; 1256.5x10–3 mm²/s. and 978.7x10–3 mm²/s.) The FASD value of each lesion was found to be significant for malignant lesions (100x10–3), especially those with restricted diffusion. In addition, for lesions with restricted diffusion, the maximum FA (75x10–3) and mean FA(200x10–3 ) values were found to be significant for malignancy. A cut-off point of 500×10–3 of FA max was found to be a value that could be used to increase the specificity of suspicious lesions with restricted diffusion Conclusion: Restricted diffusion is used as a supporting finding for biopsy indication. But due to its lower specificity DWI cannot be very helpful in the aspect of increasing specificity of conventional breast MRI. In the search of finding a tool to increase the specificity of breast MRI, FA values seem to have the potential in differentiating benign lesions.

Apparent Diffusion Coefficient (ADC) Histogram Analysis in Parotid Gland Tumors: Evaluating a Novel Approach for Differentiation between Benign and Malignant Parotid Lesions Based on Full Histogram Distributions.

The aim of this study was to assess the diagnostic value of ADC distribution curves for differentiation between benign and malignant parotid gland tumors and to compare with mean ADC values. 73 patients with parotid gland tumors underwent head-and-neck MRI on a 1.5 Tesla scanner prior to surgery and histograms of ADC values were extracted. Histopathological results served as a reference standard for further analysis. ADC histograms were evaluated by comparing their similarity to a reference distribution using Chi2-test-statistics. The assumed reference distribution for benign and malignant parotid gland lesions was calculated after pooling the entire ADC data. In addition, mean ADC values were determined. For both methods, we calculated and compared the sensitivity and specificity between benign and malignant parotid gland tumors and three subgroups (pleomorphic adenoma, Warthin tumor, and malignant lesions), respectively. Moreover, we performed cross-validation (CV) techniques to estimate the predictive performance between ADC distributions and mean values. Histopathological results revealed 30 pleomorphic adenomas, 22 Warthin tumors, and 21 malignant tumors. ADC histogram distribution yielded a better specificity for detection of benign parotid gland lesions (ADChistogram: 75.0% vs. ADCmean: 71.2%), but mean ADC values provided a higher sensitivity (ADCmean: 71.4% vs. ADChistogram: 61.9%). The discrepancies are most pronounced in the differentiation between malignant and Warthin tumors (sensitivity ADCmean: 76.2% vs. ADChistogram: 61.9%; specificity ADChistogram: 81.8% vs. ADCmean: 68.2%). Using CV techniques, ADC distribution revealed consistently better accuracy to differentiate benign from malignant lesions (“leave-one-out CV” accuracy ADChistogram: 71.2% vs. ADCmean: 67.1%). ADC histogram analysis using full distribution curves is a promising new approach for differentiation between primary benign and malignant parotid gland tumors, especially with respect to the advantage in predictive performance based on CV techniques.

Apparent diffusion coefficient histogram analysis for differentiating solid ovarian tumors.

ObjectiveTo evaluate the utility of apparent diffusion coefficient (ADC) histogram analysis to differentiate between three types of solid ovarian tumors: granulosa cell tumors (GCTs) of the ovary, ovarian fibromas, and high-grade serous ovarian carcinomas (HGSOCs).MethodsThe medical records of 11 patients with GCTs of the ovary (regions of interest [ROI-cs], 137), 61 patients with ovarian fibromas (ROI-cs, 161), and 14 patients with HGSOCs (ROI-cs, 113) confirmed at surgery and histology who underwent diffusion-weighted imaging were retrospectively reviewed. Histogram parameters of ADC maps (ADCmean, ADCmax, ADCmin) were estimated and compared using the Kruskal-WallisH test and Mann-Whitney U test. The area under the curve of receiver operating characteristic curves was used to assess the diagnostic performance of ADC parameters for solid ovarian tumors.ResultsThere were significant differences in ADCmean, ADCmax and ADCmin values between GCTs of the ovary, ovarian fibromas, and HGSOCs. The cutoff ADCmean value for differentiating a GCT of the ovary from an ovarian fibroma was 0.95×10-3 mm2/s, for differentiating a GCT of the ovary from an HGSOC was 0.69×10-3 mm2/s, and for differentiating an ovarian fibroma from an HGSOC was 1.24×10-3 mm2/s.ConclusionADCmean derived from ADC histogram analysis provided quantitative information that allowed accurate differentiation of GCTs of the ovary, ovarian fibromas, and HGSOCs before surgery.

Diffusion-weighted magnetic resonance imaging in differentiation between different vertebral lesions using ADC mapping as a quantitative assessment tool

BackgroundDiffusion-weighted imaging is one of the most useful clinical MRI techniques. Including this technique with other sequences used for routine spine scanning improves sensitivity and the capacity to characterize lesions. This study aims to evaluate the utility of apparent diffusion coefficient obtained from diffusion-weighted MR imaging in differentiating between benign and malignant vertebral lesions according to the optimal cutoff ADC value.ResultsThis study included 30 patients at Ain Shams University hospitals; all of them were subjected to full clinical assessment and magnetic resonance imaging. Patients were classified into 4 groups: inflammatory lesions (12 cases) followed by malignant lesions (7 cases), then benign neoplastic lesions (6 cases), then traumatic lesions (3 cases) and osteoporosis (two cases). Inflammatory lesions revealed restricted diffusion. Benign neoplastic lesions/hemangioma showed low signal at DWIs due to free diffusion, while malignant/metastatic lesions showed restricted diffusion. Traumatic lesions showed restricted diffusion. The osteoporotic lesions showed iso- to hyper-intense signal at DWIs. The mean ADC value of the benign lesions was 1.8 ± 0.43 mm2/s, while metastatic tumors was 0.96 ± 0.5 × 10–3 mm2/s; however, overlapping values may be present.ConclusionsCompared with benign tumors, malignant tumors have lower ADC values; nevertheless, some lesions, such as tuberculosis, have low ADC values that are like those of malignant tumors. Diffusion MRI and ADC values should always be analyzed in conjunction with standard MRI sequences as well as a thorough clinical history and examination.

“DIFFERENTIATING BENIGN FROM MALIGNANT BREAST LESIONS- CLINICAL, HISTOPATHOLOGICAL AND IMAGING CORRELATION”

Introduction: Breast cancer is the second most common cancer in Indian women. Breast cancer is a signicant cause of worldwide morbidity and mortality. Mammography and ultrasound are used as the rst line of investigation for the early detection and localization of breast tumors. Mammography has high sensitivity in case of patients with fatty parenchyma however low sensitivity in case of patients with dense breasts, implants, and post-surgical scar, thus breast MRI with higher sensitivity and specicity due to its ability to depict excellent soft-tissue contrast has become increasingly important in the detection of breast cancer. DCE-MRI has improved specicity in characterizing breast lesions by analysis of time-intensity curves. Diffusion-weighted imaging can improve the sensitivity and specicity of MRI in the evaluation of breast lesions by calculating the ADC values a quantitative measure that is a useful tool for tumor detection and differentiating between benign and malignant breast lesions. To evaluate the role of diffusion-weighted MRI andObjective: dynamic contrast-enhanced MRI in differentiating benign from malignant breast lesions and to compare the ndings of diffusion-weighted MRI and dynamic enhanced MRI with histopathological or FNAC ndings. A totalMaterial And Methods: of 30 patients with palpable breast lumps with either positive or negative ndings on mammography and ultrasound were included in this study. All patients included in this study rst underwent lm-screen mammography. Ultrasonography was done with convex and linear probes. This was followed by MRI. T1W axial, T2W axial, SPAIR/ Fat Saturated T2 weighted axial images were acquired in appropriate imaging planes. Diffusion-weighted images were obtained using b values of 0 and 1000 and ADC values were calculated. Dynamic contrast-enhanced MR was performed using fat-suppressed 3D T1 weighted images after injection of gadolinium and time-intensity curves were generated. A single precontrast scan was followed by 4 post- contrast scans which were obtained for a total duration of 4 min 24 seconds. Findings of the MRI (Diffusion-weighted and dynamic contrast enhancement) were analyzed and correlated with histopathological and FNAC ndings to evaluate their use as a diagnostic modality. A total of 30 female patients presenting with palpable breast lumps were included in theResults: study. Out of 30 patients, 20 cases were malignant (66.67%) and 10 cases were benign (33.3%). Fibroadenoma accounted for a majority of benign lesions (4 out of 10 benign lesions) while IDC accounted for the majority of malignant lesions (15 out of 20 malignant lesions). Dynamic CE-MR is a reliable tool for differentiating between benign and malignant lesions based on kinetic curves. 7 out of 10 benign lesions showed a type I curve while the rest showed a type II curve while the majority (15/20) of malignant lesions showed a type III curve. 8 out of 10 benign breast lesions did not show restricted diffusion on DWI while all malignant lesions showed restricted diffusion on DWI. In our study, the mean ADC value for benign lesions was 1.59 x 10 mm/s while the mean ADC value for malignant lesions was 0.88 x 10 mm/s. Using the ROC curve, the cut-off value of ADC was calculated to be 1.19 x 10 mm/s which gives sensitivity and specicity of 95% and 90% respectively. The individual sensitivity for DCE-MRI and DWI was calculated to be 95% and 95% while the individual specicity for DCE-MRI and DWI was calculated to be 70% and 90% respectively. After a combined analysis of DCE-MRI and DWI using a positive result from any of the two techniques as malignancy, the sensitivity and specicity were 95% and 80% respectively.

IMG-05 Imaging characteristics of CNS NB-FOXR2 – a retrospective and MULTI-INSTITUTIONAL DESCRIPTION OF 25 CASES

BACKGROUND: The CNS neuroblastoma with forkhead box R2 (CNS NB-FOXR2) activation is one of the new embryonal tumor entities in the WHO CNS tumor classification 2021. The data currently available suggest a comparably favourable outcome after craniospinal irradiation and chemotherapy. The entity is poorly characterized on imaging. We therefore aimed to describe imaging features in a multi-center patient cohort. MATERIAL AND METHODS: Molecularly and histologically confirmed CNS NB-FOXR2 tumors were retrospectively collected at six pediatric oncology centers. The imaging features on preoperative MRI and CT data were recorded by 8 experienced pediatric (neuro)radiologists in consensus. RESULTS: Twenty-five patients were identified (13 females). The majority of tumors were large at presentation (mean 115 ± SD 83 ml), showed mostly none or little perifocal edema, enhanced only partly, were often calcified and/or hemorrhagic, were always T2w hyperintense to gray matter, and often had cystic and/or necrotic components. The min. mean ADC values were relatively low (mean 687.8 ± SD 136.3 in 10-6mm2/s). The tumors originated never infratentorial and were never centered in the midline. Metastases were rare. CONCLUSIONS: For the first time, imaging characteristics of the recently described CNS NB-FOXR2 are described in a multi-center cohort. The results of this study may assist in diagnosing these tumors preoperatively. Collaborative pooling of cases is important to gain insight into typical imaging features of rare tumors, especially in view of the increasing molecular-driven subtyping.