Accuracy Of Apparent Diffusion Coefficient Research Articles

Vendor-Specific Correction Software for Apparent Diffusion Coefficient Bias Due to Gradient Nonlinearity in Breast Diffusion-Weighted Imaging Using Ice-Water Phantom.

This study aimed to evaluate a vendor-specific correction software for apparent diffusion coefficient (ADC) bias due to gradient nonlinearity in breast diffusion-weighted magnetic resonance imaging using an ice-water phantom. The phantom consists of 5 plastic tubes with a length of 100 mm and a diameter of 15 mm, filled with distilled water and immersed in an ice-water bath. Diffusion-weighted images were acquired by echo-planar imaging sequence on a 3.0-T scanner. ADC maps with and without correction were calculated using 4 b -values (0, 100, 600, and 800 s/mm 2 ). The mean ADCs were measured using a rectangular profile with 5 × 40 pixels in the anterior-posterior (AP) and a square region of interest with 5 × 5 pixels in the right-left (RL) and superior-inferior (SI) directions on the ADC map. ADC was compared with and without correction using a paired t test. Additionally, ADC of the ice-water phantom was measured at the magnet isocenter. ADC increased in the AP and RL directions and decreased in the SI direction with increasing distance from the isocenter before correction. After the correction, ADC at the off-center positions in the AP, RL, and SI directions was reduced to within 5% of the expected value. There were significant differences in the ADC at the off-center positions without and with correction ( P < 0.001); however, ADC at the magnet isocenter did not vary after correction (1.08 ± 0.02 × 10 -3 mm 2 /s). The vendor-specific software corrected the ADC bias due to gradient nonlinearity at the off-center positions in the AP, RL, and SI directions. Therefore, the software will contribute to the accurate ADC assessment in breast DWI.

Apparent Diffusion Coefficient in the Diagnosis and Follow-up of Multiple Sclerosis: Role of Magnetic Resonance Imaging

Background: Chronic Multiple Sclerosis (MS) modifies the apparent diffusion coefficient (ADC) value due to severe pathological changes. After trauma, it is the second most common cause of brain injury in healthy young adults. MRI is considered the initial imaging modality for MS diagnosis and follow-up. Objective: To assess the significance of the ADC in the diagnosis and follow-up of MS plaques across various disease subtypes. Methods: Forty MS patients were included in a case-control study at Ibn-Sina Teaching Hospital, Mosul Province, between June 1, 2022 and February 28, 2023. The patients had diffusion-weighted and traditional MR imaging with ADC measurement in plaques, and the normal white matter value of controls was compared to the patients' results. Results: The ADC values were higher in cases that were acute or secondary-progressive than in relapsing-remitting cases or normal white matter. In both types of newly generated plaques, there was an initial non-significant increase in ADC values compared to existing plaques. Overall, the ADC sensitivity, specificity, and accuracy in diagnosing MS were 85.7%, 95.2%, and 90.5% in acute cases, and 85.7%, 83.3%, and 84.6% in chronic cases, respectively, with no significant difference between active and inactive lesions. Conclusions: The apparent diffusion coefficient value can be included in the imaging protocol for the diagnosis and follow-up of various subtypes of MS.

Utility of Echo-planar Imaging with Compressed Sensitivity Encoding (EPICS) in the Evaluation of Small Breast Cancers Using Diffusion-weighted Imaging with Background Suppression (DWIBS).

High b-value acquisition and diffusion-weighted imaging with background suppression (DWIBS) are desirable in high-specificity breast cancer diagnosis on non-contrast-enhanced magnetic resonance imaging; however, this inherently results in a lower signal-to-noise ratio (SNR). Compressed sensitivity encoding (C-SENSE), which combines SENSE with compressed sensing, improves the SNR by reducing noise. Recent technological improvements allow us to incorporate this acceleration technique into echo-planar imaging, called echo-planar imaging with C-SENSE (EPICS). This study aimed to compare image quality and reliability of the apparent diffusion coefficient (ADC) between DWIBS obtained using SENSE and EPICS in patients with small breast cancers. Thirty-seven patients with pathologically confirmed breast cancer underwent DWIBS, and images were reconstructed using both conventional SENSE (SENSE-DWIBS) and EPICS (EPICS-DWIBS). Two board-certified radiologists independently evaluated lesion conspicuity (LC) and noise using a 5-point grading scale. The same 2 radiologists independently measured SNR, contrast-to-noise ratio (CNR), and the mean cancer ADC. The Pearson coefficient and Bland-Altman plot were applied to assess the accuracy of ADCs. LC scores were higher with EPICS than with SENSE, reaching significance for one reviewer but not the other reviewer. Noise ratings on visual evaluation were significantly lower with EPICS than with SENSE (P < 0.001 for both reviewers). SNR was significantly higher with EPICS than with SENSE (P < 0.005 for both reviewers). CNR was significantly higher with EPICS than with SENSE (P < 0.001 for both reviewers). Bland-Altman plots of cancer ADCs using EPICS-DWIBS and SENSE-DWIBS showed excellent concordance, with a bias of 0.026 × 10-3 mm2/s and limits of agreement ranging 0.054 × 10-3 mm2/s; the Pearson's correlation coefficient was 0.997 (P < 0.0001). EPICS enhances breast DWIBS image quality, with improved SNR and CNR and reduced noise levels. The ADCs of breast cancers obtained using EPICS were almost perfectly correlated with those obtained using conventional SENSE.

Diagnostic Accuracy of Apparent Diffusion Coefficient in Differentiating Malignant from Benign Endometrial Lesions, Taking Histopathology as Gold Standard

Diagnostic Accuracy of Apparent Diffusion Coefficient in Differentiating Malignant from Benign Endometrial Lesions, Taking Histopathology as Gold Standard

MRI based evaluation of carcinoma gallbladder using apparent diffusion coefficient (ADC) and diffusion weighted imaging (DWI)

Background Carcinoma of the gallbladder is a malignant neoplasm, which is associated with a poor prognosis due to its often-asymptomatic nature and late-stage diagnosis. Non-invasive imaging techniques play a key role in the early detection and characterization of gallbladder carcinoma. This thesis presents a comprehensive analysis of the utility of Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) mapping in the magnetic resonance imaging (MRI) evaluation of carcinoma of the gallbladder. The primary objective of this research was to investigate the exact diagnostic accuracy and potential clinical applications of DWI and ADC in assessing carcinoma of the gallbladder and related tumour aggressiveness. A systematic review of existing literature was conducted to establish a foundation for this study with efforts to acquire relevant imaging data. The results of this study demonstrate the efficacy of DWI and ADC in the detection of carcinoma of the gallbladder when compared to conventional MRI sequences. These advanced imaging techniques hold promise in increasing the accuracy of diagnosis, ultimately leading to improved patient outcomes and more informed clinical decision making. The potential of Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) mapping in the evaluation of gallbladder cancer using magnetic resonance imaging (MRI) is thoroughly analysed in this thesis. Methods A descriptive prospective study will be done at Acharya Vinoba Bhave Rural Hospital, Sawangi, involving 20 patients with clinically suspected carcinoma gallbladder, who are referred to the department of Radiodiagnosis. These patients will be subjected to study-purposive sampling. Conclusion After an appropriate statistical analysis, we expect to assess the role of Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) mapping in the magnetic resonance imaging (MRI) evaluation of carcinoma of the gallbladder. CTRI registration This trial has been submitted to Clinical Trials Registry-India (CTRI) for Review. Registration Number: REF/2023/09/072780 Registration date:01/05/2023 URL of trial: https://www.ctri.nic.in/

The role of apparent diffusion coefficient in the grading of adult isocitrate dehydrogenase-mutant astrocytomas: relationship with the Ki-67 proliferation index.

The grading of adult isocitrate dehydrogenase (IDH)-mutant astrocytomas is a crucial prognostic factor. To investigate the value of conventional magnetic resonance imaging (MRI) features and apparent diffusion coefficient (ADC) in the grading of adult IDH-mutant astrocytomas, and to analyze the correlation between ADC and the Ki-67 proliferation index. The clinical and MRI data of 82 patients with adult IDH-mutant astrocytoma who underwent surgical resection and molecular genetic testing with IDH and 1p/19q were retrospectively analyzed. The conventional MRI features, ADCmin, ADCmean, and nADC of the tumors were compared using the Kruskal-Wallis single factor ANOVA and chi-square tests. Receiver operating characteristic (ROC) curves were drawn to evaluate conventional MRI and ADC accuracy in differentiating tumor grades. Pearson correlation analysis was performed to determine the correlation between ADC and the Ki-67 proliferation index. The difference in enhancement, ADCmin, ADCmean, and nADC among WHO grade 2, 3, and 4 tumors was statistically significant (all P <0.05). ADCmin showed the preferable diagnostic accuracy for grading WHO grade 2 and 3 tumors (AUC=0.724, sensitivity=63.4%, specificity=80%, positive predictive value (PPV)=62.0%; negative predictive value (NPV)=82.5%), and distinguishing grade 3 from grade 4 tumors (AUC=0.764, sensitivity=70%, specificity=76.2%, PPV=75.0%, NPV=71.4%). Enhancement + ADC model showed an optimal predictive accuracy (grade 2 vs. 3: AUC = 0.759; grade 3 vs. 4: AUC = 0.799). The Ki-67 proliferation index was negatively correlated with ADCmin, ADCmean, and nADC (all P <0.05), and positively correlated with tumor grade. Conventional MRI features and ADC are valuable to predict pathological grading of adult IDH-mutant astrocytomas.

High-resolution prostate diffusion MRI using eddy current-nulled convex optimized diffusion encoding and random matrix theory-based denoising.

To develop and evaluate a technique combining eddy current-nulled convex optimized diffusion encoding (ENCODE) with random matrix theory (RMT)-based denoising to accelerate and improve the apparent signal-to-noise ratio (aSNR) and apparent diffusion coefficient (ADC) mapping in high-resolution prostate diffusion-weighted MRI (DWI). MATERIALS ANDMETHODS: Eleven subjects with clinical suspicion of prostate cancer were scanned at 3T with high-resolution (HR) (in-plane: 1.0 × 1.0 mm2) ENCODE and standard-resolution (1.6 × 2.2 mm2) bipolar DWI sequences (both had 7 repetitions for averaging, acquisition time [TA] of 5 min 50 s). HR-ENCODE was retrospectively analyzed using three repetitions (accelerated effective TA of 2 min 30 s). The RMT-based denoising pipeline utilized complex DWI signals and Marchenko-Pastur distribution-based principal component analysis to remove additive Gaussian noise in images from multiple coils, b-values, diffusion encoding directions, and repetitions. HR-ENCODE with RMT-based denoising (HR-ENCODE-RMT) was compared with HR-ENCODE in terms of aSNR in prostate peripheral zone (PZ) and transition zone (TZ). Precision and accuracy of ADC were evaluated by the coefficient of variation (CoV) between repeated measurements and mean difference (MD) compared to the bipolar ADC reference, respectively. Differences were compared using two-sided Wilcoxon signed-rank tests (P < 0.05 considered significant). HR-ENCODE-RMT yielded 62% and 56% higher median aSNR than HR-ENCODE (b = 800 s/mm2) in PZ and TZ, respectively (P < 0.001). HR-ENCODE-RMT achieved 63% and 70% lower ADC-CoV than HR-ENCODE in PZ and TZ, respectively (P < 0.001). HR-ENCODE-RMT ADC and bipolar ADC had low MD of 22.7 × 10-6 mm2/s in PZ and low MD of 90.5 × 10-6 mm2/s in TZ. HR-ENCODE-RMT can shorten the acquisition time and improve the aSNR of high-resolution prostate DWI and achieve accurate and precise ADC measurements in the prostate.

Diffusion weighted imaging with reverse encoding distortion correction: Improvement of image quality and distortion for accurate ADC evaluation in in vitro and in vivo studies

PurposeThe purpose of this in vivo study was to determine the effect of reverse encoding direction (RDC) on apparent diffusion coefficient (ADC) measurements and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign tumors on head and neck diffusion-weighted imaging (DWI). MethodsForty-eight patients with head and neck tumors underwent DWI with and without RDC and pathological examinations. Their tumors were then divided into two groups: malignant (n = 21) and benign (n = 27). To determine the utility of RDC for DWI, the difference in the deformation ratio (DR) between DWI and T2-weighted images of each tumor was determined for each tumor area. To compare ADC measurement accuracy of DWIs with and without RDC for each patient, ADC values for tumors and spinal cord were determined by using ROI measurements. To compare DR and ADC between two methods, Student’s t-tests were performed. Then, ADC values were compared between malignant and benign tumors by Student’s t-test on each DWI. Finally, sensitivity, specificity and accuracy were compared by means of McNemar’s test. ResultsDR of DWI with RDC was significantly smaller than that without RDC (p < 0.0001). There were significant differences in ADC between malignant and benign lesions on each DWI (p < 0.05). However, there were no significant difference of diagnostic accuracy between the two DWIs (p > 0.05). ConclusionRDC can improve image quality and distortion of DWI and may have potential for more accurate ADC evaluation and differentiation of malignant from benign head and neck tumors.

Role of Apparent Diffusion Coefficient Map-Based First- and High-Order Radiomic Features for the Discrimination of Sacral Chordomas and Chondrosarcomas With Overlapping Conventional Imaging Features.

Chondrosarcomas arise from the lateral pelvis; however, midline chondrosarcomas (10%) display similar imaging features to chordoma, causing a diagnostic challenge. This study aims to determine the diagnostic accuracy of apparent diffusion coefficient (ADC)-based radiomic features and two novel diffusion indices for differentiating sacral chordomas and chondrosarcomas. A retrospective, multireader review was performed of 82 pelvic MRIs (42 chordomas and 40 chondrosarcomas) between December 2014 and September 2021, split into training (n = 69) and validation (n = 13) data sets. Lesions were segmented on a single slice from ADC maps. Eight first-order features (minimum, mean, median, and maximum ADC, standard deviation, skewness, kurtosis, and entropy) and two novel indices: restriction index (RI, proportion of lesions with restricted diffusion) and facilitation index (FI, proportion of lesions with facilitated diffusion) were estimated. One hundred seven radiomic features comparing patients with chondrosarcoma versus chordoma were sorted based on mean group differences. There was good to excellent interobserver reliability for eight of the 10 ADC metrics on the training data set. Significant differences were observed (P < .005) for RI, FI, median, mean, and skewness using the training data set. Optimal cutpoints for diagnosis of chordoma were RI > 0.015; FI < 0.25; mean ADC < 1.7 × 10-3 mm2/s; and skewness >0.177. The optimal decision tree relied on FI. In a secondary analysis, significant differences (P < .00047) in chondrosarcoma versus chordoma were found in 18 of 107 radiomic features, including six first-order and 12 high-order features. The novel ADC index, FI, in addition to ADC mean, skewness, and 12 high-order radiomic features, could help differentiate sacral chordomas from chondrosarcomas.

Efficiency and Accuracy Evaluation of Multiple Diffusion-Weighted MRI Techniques Across Different Scanners.

The choice between different diffusion-weighted imaging (DWI) techniques is difficult as each comes with tradeoffs for efficient clinical routine imaging and apparent diffusion coefficient (ADC) accuracy. To quantify signal-to-noise-ratio (SNR) efficiency, ADC accuracy, artifacts, and distortions for different DWI acquisition techniques, coils, and scanners. Phantom, in vivo intraindividual biomarker accuracy between DWI techniques and independent ratings. NIST diffusion phantom. 51 Patients: 40 with prostate cancer and 11 with head-and-neck cancer at 1.5 T FIELD STRENGTH/SEQUENCE: Echo planar imaging (EPI): 1.5 T and 3 T Siemens; 3 T Philips. Distortion-reducing: RESOLVE (1.5 and 3 T Siemens); Turbo Spin Echo (TSE)-SPLICE (3 T Philips). Small field-of-view (FOV): ZoomitPro (1.5 T Siemens); IRIS (3 T Philips). Head-and-neck and flexible coils. SNR Efficiency, geometrical distortions, and susceptibility artifacts were quantified for different b-values in a phantom. ADC accuracy/agreement was quantified in phantom and for 51 patients. In vivo image quality was independently rated by four experts. QIBA methodology for accuracy: trueness, repeatability, reproducibility, Bland-Altman 95% Limits-of-Agreement (LOA) for ADC. Wilcoxon Signed-Rank and student tests on P < 0.05 level. The ZoomitPro small FOV sequence improved b-image efficiency by 8%-14%, reduced artifacts and observer scoring for most raters at the cost of smaller FOV compared to EPI. The TSE-SPLICE technique reduced artifacts almost completely at a 24% efficiency cost compared to EPI for b-values ≤500 sec/mm2 . Phantom ADC 95% LOA trueness were within ±0.03 × 10-3 mm2 /sec except for small FOV IRIS. The in vivo ADC agreement between techniques, however, resulted in 95% LOAs in the order of ±0.3 × 10-3 mm2 /sec with up to 0.2 × 10-3 mm2 /sec of bias. ZoomitPro for Siemens and TSE SPLICE for Philips resulted in a trade-off between efficiency and artifacts. Phantom ADC quality control largely underestimated in vivo accuracy: significant ADC bias and variability was found between techniques in vivo. 3 TECHNICAL EFFICACY STAGE: 2.

Diagnostic accuracy of apparent diffusion coefficient to differentiate intrapancreatic accessory spleen from pancreatic neuroendocrine tumors

Diagnostic accuracy of apparent diffusion coefficient to differentiate intrapancreatic accessory spleen from pancreatic neuroendocrine tumors

Diagnostic accuracy of apparent diffusion coefficient (ADC) in differentiating low- and high-grade gliomas, taking histopathology as the gold standard

Gliomas are known to be one of the most grievous malignant central nervous system (CNS) tumors and have a high mortality rate with a low survival rate severe disability and increase risk of recurrence. Aim of his study is to determine the diagnostic accuracy of apparent diffusion coefficient (ADC) in differentiating low-grade and high-grade gliomas, taking histopathology as the gold standard. It is a Cross-sectional validation study conducted at the Armed Forces Institute of Radiology and Imaging, (AFIRI) Rawalpindi, Pakistan from 28th February 2022 to 27th August 2022. Materials and methods: A total of 215 patients with focal brain lesions of age 25-65 years of either gender were included. Patients with a cardiac pacemaker, breastfeeding females, de-myelinating lesions and malignant infiltrates, and renal failure were excluded. Then diffusion-weighted magnetic resonance imaging was performed on each patient by using a 1.5 Tesla MR system. The area of greatest diffusion restriction (lowest ADC) within the solid tumor component was identified while avoiding areas of peritumoral edema. Results of ADC were interpreted by a consultant radiologist (at least 5 years of post-fellowship experience) for high or low-grade glioma. After this, each patient has undergone a biopsy in the concerned ward, and histopathology results were compared with ADC findings. Results: Overall sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy of apparent diffusion coefficient (ADC) in differentiating low- and high-grade gliomas, taking histopathology as the gold standard was 93.65%, 87.64%, 91.47%, 90.70% and 91.16% respectively. Conclusion: This study concluded that apparent diffusion coefficient (ADC) is the non-invasive modality of choice with high diagnostic accuracy in differentiating low- and high-grade gliomas.

The role of diffusion magnetic resonance imaging in determining tumor aggressiveness during preoperative surgical planning in early-stage endometrial cancer.

The present study aimed to evaluate the relationship between tumor volume and apparent diffusion coefficient (ADC) in preoperative magnetic resonance imaging and deep myometrial invasion, tumor grade, and lymphovascular space invasion (LVSI) in patients with early-stage endometrial cancer. The study included 73patients diagnosed with early-stage endometrial cancer based on histopathological examination between May 2014 and July 2019. Receiver operating characteristic (ROC) curve analysis was used to estimate the accuracy of ADC and tumor volume in predicting the LVSI, the depth of myometrial invasion (DMI), and the histopathological tumor grade in these patients. The areas under the ROC curves (AUCs) of ADC and tumor volume in predicting LVI, DMI, and high tumor grade were significantly greater than those for superficial myometrial invasion and low-grade tumors. The ROC analysis revealed that higher tumor volume was significantly associated with the prediction of DMI and tumor grade (p = 0.002 and p = 0.015). The corresponding cut-off values of tumor volume were > 7.12 and > 9.38 mL. The sensitivity of ADC in predicting DMI was higher than its sensitivity in predicting LVSI and grade1 tumors. Furthermore, tumor volume was significantly associated with the prediction of DMI and tumor grade. In the absence of pathological pelvic lymph nodes in early-stage endometrial cancer, tumor volume in DWI sequences determines the active tumor load and tumor aggressiveness. Furthermore, alow ADC indicates deep myometrial invasion and helps differentiate stage IA and stage IB tumors.

3D variable flip angle T1 mapping for differentiating benign and malignant liver lesions at 3T: comparison with diffusion weighted imaging

BackgroundDifferent methods have been used to improve the imaging diagnosis of focal liver lesions (FLL). Among them, magnetic resonance imaging (MRI) has received more attention since it provides significant amount of information without radiation exposure. However, atypical imaging characteristics of FLL on MRI may complicate the differential diagnosis between benign and malignant FLL. This study aimed to compare the diagnostic value of T1 mapping and diffusion-weighted imaging (DWI) for differentiating of benign and malignant FLLs.MethodsThis retrospective study enrolled 294 FLLs, including 150 benign and 144 malignant lesions. Whole liver T1 mapping sequences were obtained before and 2 min after the administration of Gd-DTPA to acquire native T1 and enhanced T1 and ΔT1%. Additionally, DWI sequence was conducted to generate apparent diffusion coefficient (ADC) maps. These quantitative parameters were compared using one-way analysis of variance, and the diagnostic accuracy of T1 mapping and ADC for FLLs was calculated by area under the curve (AUC).ResultsSignificant differences were observed regarding the native T1, enhanced T1, ΔT1%, and ADC between benign and malignant FLLs. Furthermore, the sensitivity and specificity of the parameters are as follows: native T1 0.797/0.702 (cut off value 1635.5 ms); enhanced T1, 0.911/0.976 (cutoff value 339.2 ms); ΔT1%, 0.901/0.905 (cutoff value 70.8%); and ADC, 0.975/0.952 (cutoff value 1.21 × 10−3 mm2/s). The ideal cutoff values for native T1 and ADC in identifying cyst and haemangioma were 2422.9 ms (AUC 0.990, P < 0.01) and 2.077 × 10–3 mm2/s (AUC 0.949, P < 0.01), respectively, with a sensitivity and specificity of 0.963/1 and 0.852/0.892, respectively. ADC was significantly positively correlated with T1 and ΔT1%, and significantly negatively correlated with enhanced T1.ConclusionThe 3D Variable flip angle T1 mapping technique with Gd-DTPA has a high clinical potential for identifying benign and malignant FLLs. The enhanced T1 and ΔT1% values have similar diagnostic accuracy compared with DWI in evaluating FLLs. Native T1 shows better performance than DWI in distinguishing benign liver lesions, specifically, cysts, and haemangioma.

Developing quality assurance tests for simultaneous Positron Emission Tomography - Magnetic Resonance imaging for radiotherapy planning.

Background and purpose Simultaneous Positron Emission Tomography – Magnetic Resonance (PET-MR) imaging can potentially improve radiotherapy by enabling more accurate tumour delineation and dose painting. The use of PET-MR imaging for radiotherapy planning requires a comprehensive Quality Assurance (QA) programme to be developed. This study aimed to develop the QA tests required and assess their repeatability and stability. Materials and methods QA tests were developed for: MR image quality, MR geometric accuracy, electromechanical accuracy, PET-MR alignment accuracy, Diffusion Weighted (DW)-MR Apparent Diffusion Coefficient (ADC) accuracy and PET Standard Uptake Value (SUV) accuracy. Each test used a dedicated phantom and was analysed automatically or semi-automatically, with in–house software. Repeatability was evaluated by three same-day measurements with independent phantom positions. Stability was assessed through 12 monthly measurements. Results The repeatability Standard Deviations (SDs) of distortion for the MR geometric accuracy test were . The repeatability SDs in ADC difference from reference were for the DW-MR accuracy test. The PET SUV difference from reference repeatability SD was . The stability SDs agreed within , 1 percentage point and 1.4 percentage points of the repeatability SDs for the geometric, ADC and SUV accuracy tests respectively. There were no monthly trends apparent. These results were representative of the other tests. Conclusions QA Tests for radiotherapy planning PET-MR have been developed. The tests appeared repeatable and stable over a 12-month period. The developed QA tests could form the basis of a QA programme that enables high-quality, robust PET-MR imaging for radiotherapy planning.

Radiomics improves the utility of ADC for differentiation between renal oncocytoma and chromophobe renal cell carcinoma: Preliminary findings

ObjectiveDifferentiation between renal oncocytoma (RON) and chromophobe renal cell carcinoma (chRCC) remains challenging. We aimed to assess the accurate apparent diffusion coefficient (ADC) radiomics features in differentiating these tumors. Materials and methodsThis single-center retrospective study included 14 patients with histopathologically proven RON (n = 6) and chRCC (n = 8) who underwent magnetic resonance imaging. Features were extracted from ADC maps. Features with an intraclass correlation coefficient >0.90, an intergroup p < 0.01 and interrater differences with normal distribution underwent agreement and receiver operating characteristic curve analyses. ResultsOverall, 6 features qualified for further analysis and Bland–Altman plots revealed acceptable agreement for all. Only 1 first order feature and 5 high order texture features successfully predicted RON with more than 90% sensitivities and specificities more than 80%. ConclusionSquared mean ADC and certain gray level run length matrix features extracted by radiomics of ADC mapping provide quite high diagnostic precision in terms of distinguishing between RON and chRCC.

La radiómica mejora la utilidad del ADC en la diferenciación entre el oncocitoma renal y el carcinoma cromófobo de células renales: resultados preliminares

ObjectiveDifferentiation between renal oncocytoma (RON) and chromophobe renal cell carcinoma (chRCC) remains challenging. We aimed to assess the accurate apparent diffusion coefficient (ADC) radiomics features in differentiating these tumors. Materials and methodsThis single-center retrospective study included 14 patients with histopathologically proven RON (n=6) and chRCC (n=8) who underwent magnetic resonance imaging. Features were extracted from ADC maps. Features with an intraclass correlation coefficient >0.90, an intergroup p<0.01 and interrater differences with normal distribution underwent agreement and receiver operating characteristic curve analyses. ResultsOverall, 6 features qualified for further analysis and Bland-Altman plots revealed acceptable agreement for all. Only 1 first order feature and 5 high order texture features successfully predicted RON with more than 90% sensitivities and specificities more than 80%. ConclusionSquared mean ADC and certain gray level run length matrix features extracted by radiomics of ADC mapping provide quite high diagnostic precision in terms of distinguishing between RON and chRCC.

Role of DWI in evaluation of HCC after radiofrequency ablation compared to dynamic MRI using MRI (3\xa0T)

BackgroundThe purpose of this study was to investigate the diagnostic performance of diffusion weight imaging (DWI), apparent diffusion coefficient (ADC) map, normalized ADC liver, and normalized ADC spleen compared to the dynamic contrast-enhanced MRI (DCE-MRI) in the evaluation of residual hepatocellular carcinoma (HCC) after radiofrequency ablation (RFA) using 3 T (T) magnetic resonance imaging (MRI).ResultsA prospective study was performed on 40 patients with radiofrequency-ablated HCC, and 15 (37.5%) patients had viable lesion post-RFA, while 25 (62.5%) had non-viable lesions. DCE-MRI had a sensitivity, specificity, and accuracy of 100%, 100%, and 100%, respectively, compared to DWI which had a sensitivity, specificity, and accuracy of 80%, 88%, and 85%, respectively, for identifying post-RFA viable HCC. The sensitivity, specificity, and accuracy of ADC at a cutoff value of 1.01 × 10−3 mm2/s were 80%, 100%, and 97.1%, respectively. The optimal cutoff value of normalized ADC liver was 0.81 with a sensitivity of 73.3%, specificity of 96%, and accuracy of 92.8%. The sensitivity, specificity, and accuracy of normalized ADC spleen at a cutoff value of 1.22 were 80%, 92%, and 91.1%, respectively.ConclusionsDWI-MRI is a reliable technique for assessing HCC after radiofrequency ablation. DWI-MRI with ADC may be used as an alternate sequence for assessing radiofrequency-ablated lesions in individuals who have a contraindication to the contrast media, and the normalized ADC value may be of additional benefit.

Noninferiority of Monoparametric MRI Versus Multiparametric MRI for the Detection of Prostate Cancer: Diagnostic Accuracy of ADC Ratios Based on Advanced "Zoomed" Diffusion-Weighted Imaging.

The aim of this study was to compare the diagnostic accuracy of apparent diffusion coefficient (ADC) ratios as a monoparametric magnetic resonance imaging (MRI) protocol for the detection of prostate cancer (PCa) with the established multiparametric (mp) MRI at 3.0 T. According to power analysis, 52 male patients were included in this monocenter study with prospective data collection and retrospective, blinded multireader image analysis. The study was approved by the local ethics committee. Patients were recruited from January to December 2020. Based on mpMRI findings, patients underwent in-bore MR biopsy or prostatectomy for histopathologic correlation of suspicious lesions. Three readers, blinded to the histopathologic results and images of mpMRI, independently evaluated ADC maps for the detection of PCa. The ADC ratio was defined as the lowest signal intensity (SI) of lesions divided by the SI of normal tissue in the zone of origin. Predictive accuracy of multiparametric and monoparametric MRI were compared using logistic regression analysis. Moreover, both protocols were compared applying goodness-of-fit analysis with the Hosmer-Lemeshow test for continuous ADC ratios and Pearson χ2 test for binary decision calls, correlation analysis with Spearman ρ and intraclass correlation coefficients, as well as noninferiority assessment with a TOST ("two one-sided test"). Eighty-one histopathologically proven, unique PCa lesions (Gleason score [GS] ≥ 3 + 3) in 52 patients could be unequivocally correlated, with 57 clinically significant (cs) PCa lesions (GS ≥ 3 + 4). Multiparametric MRI detected 95%, and monoparametric ADC detected ratios 91% to 93% of csPCa. Noninferiority of monoparametric MRI was confirmed by TOST (P < 0.05 for all comparisons). Logistic regression analysis revealed comparable predictive diagnostic accuracy of ADC ratios (73.7%-87.8%) versus mpMRI (72.2%-84.7%). Spearman rank correlation coefficient for PCa aggressiveness revealed satisfactory correlation of ADC ratios (P < 0.013 for all correlations). The Hosmer-Lemeshow test for the logistic regression analysis for continuous ADC ratios indicated adequate predictive accuracy (P = 0.55-0.87), and the Pearson χ2 test showed satisfactory goodness of fit (P = 0.35-0.69, χ2 = 0.16-0.87). Normalized ADC ratios based on advanced DWI are noninferior to mpMRI at 3.0 T for the detection of csPCa in a preselected patient cohort and proved a fast and accurate assessment tool, thus showing a potential prospect of easing the development of future screening methods for PCa.

MP05-06 DIAGNOSTIC ACCURACY OF ADC VALUE ON BIPARAMETRIC MRI FOR DETECTING CLINICALLY SIGNIFICANT PROSTATE CANCER

You have accessJournal of UrologyProstate Cancer: Detection & Screening I (MP05)1 Sep 2021MP05-06 DIAGNOSTIC ACCURACY OF ADC VALUE ON BIPARAMETRIC MRI FOR DETECTING CLINICALLY SIGNIFICANT PROSTATE CANCER Jih Hoon Park, Ja Yoon Ku, and Hong Koo Ha Jih Hoon ParkJih Hoon Park More articles by this author , Ja Yoon KuJa Yoon Ku More articles by this author , and Hong Koo HaHong Koo Ha More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000001972.06AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: PI-RADS v2 is helpful for the detection of clinically significant prostate cancer (CS-PCa), but does not provide quantitative information. We conducted this study to evaluate the diagnostic accuracy of apparent diffusion coefficient (ADC) value for detecting CS-PCa with TRUS-MR fusion biopsy using 3T biparametric MRI (bpMRI). METHODS: We enrolled 310 patients with elevated PSA level over 4 ng/mL who underwent bpMRI followed by TRUS-MR fusion biopsy of prostate between June 2016 and June 2019. Patients underwent MRI examination on Achieva 3.0T TX MRI Scanner from Philips. The suspicious lesions were indicated by experienced radiologists according to PI-RADS v2, marked as a region-of-interest (ROI) and targeted by TRUS-MR fusion biopsy. ADC values were calculated for a pair of b values: 50 and 1400 s/mm2. ADC values of ROIs were recorded by averaging the values measured at least three times each by two urologists. The size of ROIs was chosen to be as large as possible and with minimal contamination from normal tissue. CS-PCa was defined as ISUP grade of 2 or greater. Lower grade (LG) PCa was defined as ISUP grade 1 or 2, and higher grade (HG) as ISUP grade over 2. RESULTS: Of the 502 lesions indicated and biopsied, 348 (69.3%) were on peripheral zone (PZ) and 154 (30.7%) on transitional zone (TZ). In PZ, 101 (29.0%) lesions were diagnosed with PCa, including 73 (21.0%) with CS-PCa, and in TZ, 39 (25.3%) and 21 (13.6%) were detected with PCa and CS-PCa, respectively. Receiver operating characteristic (ROC) curve analyses showed larger area under curve (AUC) for ADC value compared to PI-RADS (0.902 vs 0.827) for detecting CS-PCa in PZ, but not in TZ (0.797 vs 0.786). According to DeLong test there was a statistically significant better AUC for ADC value on ROC curve analysis compared to PI-RADS in PZ (p=0.0095), but not in TZ (p=0.8496). Mean ADC value (x10-3 mm2/s) of the lesions diagnosed with benign prostatic tissues was 0.929 (95% CI 0.906-0.953), and was different statistically significant with that of LG PCa tissues (mean=0.643, 95% CI 0.591-0.695, p<0.001) and that of HG PCa tissue (mean=0.576, 95% CI 0.540-0.610, p<0.001). The difference between LG and HG PCa tissues was statistically significant (p=0.034). CONCLUSIONS: Predictive role of ADC value on biparametric MRI before TRUS-MR fusion biopsy is better than PI-RADS v2 in detection of CS-PCa. Source of Funding: No source of funding © 2021 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 206Issue Supplement 3September 2021Page: e79-e80 Advertisement Copyright & Permissions© 2021 by American Urological Association Education and Research, Inc.MetricsAuthor Information Jih Hoon Park More articles by this author Ja Yoon Ku More articles by this author Hong Koo Ha More articles by this author Expand All Advertisement Loading ...