Apparent Diffusion Coefficient Measurements Research Articles

Unsupervised clustering analysis-based characterization of spatial profiles of inaccuracy in apparent diffusion coefficient values with varying acquisition plan orientation and diffusion weighting gradient direction - A large multicenter phantom study.

This large multicenter study of 37 magnetic resonance imaging scanners aimed at characterizing, for the first time, spatial profiles of inaccuracy (namely, Δ-profiles) in apparent diffusion coefficient (ADC) values with varying acquisition plan orientation and diffusion weighting gradient direction, using a statistical approach exploiting unsupervised clustering analysis.&#xD;A diffusion-weighted imaging (DWI) protocol (b-value: 0-200-400-600-800-1000 s/mm2) with different combinations of acquisition plan orientation (axial/sagittal/coronal) and diffusion weighting gradient direction (anterior-posterior/left-right/feet-head) was acquired on a standard water phantom. For each acquisition setup, Δ-profiles along the 3 main orthogonal directions were characterized by fitting data with a second order polynomial function (ar2+br+c) . Moreover, for each Δ-profile, the maximum minus minimum of the fitting function (δmax) was calculated. &#xD;The parametersa,b,c, andδmaxshowed some significant variations between scanner systems by different manufacturers or with different static magnetic field strengths, as well as between different acquisition/estimation setups. Unsupervised clustering analysis showed two evident clusters with significantly different values of parameter a (p< 0.0001), which can be grouped by acquisition protocol/Δ-profile direction but not scanner system.&#xD;The results of ∆-profiles confirm an appreciable inter-scanner variability in ADC measurement and corroborate the importance of guarantying the reliability of ADC estimations in clinical or research studies, considering for each scanner system the specific acquisition sequence in terms of acquisition plan orientation and diffusion weighting gradient direction.

Deep learning based apparent diffusion coefficient map generation from multi-parametric MR images for patients with diffuse gliomas.

Apparent diffusion coefficient (ADC) maps derived from diffusion weighted magnetic resonance imaging (DWI MRI) provides functional measurements about the water molecules in tissues. However, DWI is time consuming and very susceptible to image artifacts, leading to inaccurate ADC measurements. This study aims to develop a deep learning framework to synthesize ADC maps from multi-parametric MR images. We proposed the multiparametric residual vision transformer model (MPR-ViT) that leverages the long-range context of vision transformer (ViT) layers along with the precision of convolutional operators. Residual blocks throughout the network significantly increasing the representational power of the model. The MPR-ViT model was applied to T1w and T2-fluid attenuated inversion recovery images of 501 glioma cases from a publicly available dataset including preprocessed ADC maps. Selected patients were divided into training (N=400), validation (N=50), and test (N=51) sets, respectively. Using the preprocessed ADC maps as ground truth, model performance was evaluated and compared against the Vision Convolutional Transformer (VCT) and residual vision transformer (ResViT) models with the peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and mean squared error (MSE). The results are as follows using T1w + T2-FLAIR MRI as inputs: MPR-ViT-PSNR: 31.0±2.1, MSE: 0.009±0.0005, SSIM: 0.950±0.015. In addition, ablation studies showed the relative impact on performance of each input sequence. Both qualitative and quantitative results indicate that the proposed MR-ViT model performs favorably against the ground truth data. We show that high-quality ADC maps can be synthesized from structural MRI using a MPR-ViT model. Our predicted images show better conformality to the ground truth volume than ResViT and VCT predictions. These high-quality synthetic ADC maps would be particularly useful for disease diagnosis and intervention, especially when ADC maps have artifacts or are unavailable.

Usefulness of apparent diffusion coefficient values for assessment of MRI abnormality at term equivalent age in low-birth-weight infants weighing less than 1500g.

To determine whether apparent diffusion coefficient (ADC) measurements at term equivalent age (TEA) are useful for assessment of major abnormalities revealed by MRI. Of 405 neonates who underwent MRI during the period 2016-2022, 101 low birth weight (LBW) infants (birth weight < 1500g) were imaged at TEA. ADC values were measured in the thalamus, basal ganglia, anterior and posterior centrum semiovale, pons, and cerebellar hemisphere. The ADC values in LBW infants with and without major abnormalities evident on MRI were compared at the above six sites. Abnormal findings included IVH-3 IVH-4, more than six punctate white matter lesion, white matter injury (cystic or non-cystic), and major cerebellar hemorrhage. LBW infants overall (N = 101) and an extreme LBW (ELBW) group (< 1000g) (N = 55) were compared and area under the curve was calculated using ROC analysis. There were no difference in ADC values between LBW infants with and without major abnormalities. In ELBW infants, ADC values in the cerebellum were higher when major abnormalities were present (p = 0.045). ROC analysis yielded AUC < 0.7 for both LBW cases overall and ELBW cases. For LBW infants overall, ADC measurements alone at TEA are not very useful for differentiation between individuals with and without major abnormalities, but ELBW infants with major abnormalitiesshowed higher ADC values in the cerebellum, suggesting that the normal reduction of ADC occurring with maturation between preterm birth and TEA may be impaired.

Concentric-object and equiangular-object methods to perform standardized regional analysis in renal mpMRI.

Renal multiparametric magnetic resonance imaging (mpMRI) sequences, including T1-T2 mapping, Blood oxygenation level-dependent (BOLD), Renal blood flow (RBF), and Apparent Diffusion Coefficient (ADC) from diffusion-weighted imaging (DWI), provide insights into kidney function. However, consensus on selecting regions of interest (ROIs) is lacking. This study aims to describe and compare the Concentric Objects (CO) and Equiangular Objects (EO) methods for standardized ROI selection and assess their efficacy in capturing regional variations in renal MRI parameters. Twelve healthy volunteers underwent mpMRI renal scans. ROIs were selected manually and by applying the CO and EO algorithms to each mpMRI sequence. The methods were tested across various subregion configurations. Regional differences in renal MRI parameters were evaluated. CO and EO methods demonstrated statistically significant differences in mpMRI parameters across renal regions. ASL-RBF, BOLD-MRI, and T2-map results indicated substantial variations from the lower to upper kidney areas. This study implemented CO and EO algorithms in renal mpMRI, showing their potential for evaluating cortico-medullary and cranio-caudal profiles. The findings validate the CO method for BOLD and ADC measurements and presented ASL-RBF and T1-T2 map profiles. The EO method's utility needs further validation with renal patients.

Measurement of apparent diffusion coefficient (ADC) in fetal organs and placenta using 3 Tesla magnetic resonance imaging (MRI) across gestational ages

Diffusion-weighted imaging (DWI) is a technique used to probe the random microscopic motion of water protons in living tissue, represented by a parameter measurement of apparent diffusion coefficient (ADC) values. This study aimed to measure the ADC values of various fetal organs and placenta using 3T at various gestational ages. This was a prospective observational study. A total of 103 singleton pregnancies from 20 to 38 weeks of gestational age were included. Diffusion-weighted imaging was performed in the axial plane from the fetal head to the trunk with the following parameters: TR: 2000–2500 ms; TE: 88 ms; FOV: 250 mm; 256 matrix; slice thickness: 4 mm with a 0 mm gap; acquisition time: 1 min, 18 s. Diffusion gradient values were b = 0 and b = 700 s/mm2. ADC was measured in fetal brain regions (frontal white matter, occipital white matter, centrum semiovale, pons, thalamus, cerebellum, and fetal organs (lungs, kidney, and placenta). ANOVA was used to calculate the mean ADC values. Karl Pearson’s coefficient of correlation was used to evaluate the correlation between ADC values and increasing gestational age. The mean ADC values of brain regions were: frontal white matter (1.64 ± 0.08 × 10− 3 mm2 /s, F-39.10,p-<0.001), occipital white matter (1.64 ± 0.06 × 10− 3 mm2/s, F-26.14, p-<0.001), centrum semiovale (1.62 ± 0.03 × 10− 3 mm2/s, F-49.88,p-<0.001, pons (1.23 ± 0.09 × 10− 3 mm2/s F-9.14,p-<0.001) ), Thalamus (1.21 ± 0.07 × 10− 3 mm2/s, F-13.54,p-<0.001) and cerebellum (1.36 ± 0.10 × 10− 3 mm2 /s, F-4.19,p-<0.001). The mean ADC values of fetal organs were lung (1.92 ± 0.15 × 10− 3 mm2 /s, F-28.24, p-<0.001), kidney (1.34 ± 0.11 × 10− 3 mm2 /s, F-1.05, p- 0.37) and placenta (1.94 ± 0.11 × 10− 3 mm2 /s, F-160.33, p-<0.001). White-matter regions showed a significant positive correlation with increasing gestational age. Statistically, a negative correlation was observed between increasing gestational age and ADC measurements obtained in the thalamus, cerebellum, pons, and kidney. This will be one of the first few studies to provide the ADC values of the fetal brain and fetal organs using 3T MRI. The current study shows that diffusion-weighted MRI can offer a promising technique to evaluate the structural development of fetal organs and can potentially lead to a biomarker for predicting the functionality of the fetal organs in abnormalities.

Comparison of Diffusion-weighted MRI using Singe-Shot Echo-planar Imaging (SS-EPI) and Split Acquisition of Fast Spin Echo Signal (SPLICE) Imaging, a non-EPI technique, in Tumors of the Head and Neck.

Diffusion-weighted imaging (DWI) using single-shot echo planar imaging (DW-EPI) is susceptible to distortions around air-filled cavities and dental fillings, typical for the head and neck area. Non-EPI, Split acquisition of fast spin echo signals for diffusion imaging (DWSPLICE) could reduce these distortions and enhance image quality, thereby potentially improving recurrence assessment in squamous cell carcinoma (SCC) of the head and neck region. This study evaluated whether DW-SPLICE is a viable alternative to DW-EPI through quantitative and qualitative analyses. The DW-SPLICE sequence was incorporated into the standard 3.0T head and neck MRI protocol with DW-EPI. Retrospective analysis was conducted on two subgroups: firstly benign or malignant lesions, and secondly post-treatment SCC recurrence. In both subgroups Image quality and distortion were scored by two independent radiologists, blinded for DW-technique, and evaluated using mixed-effect linear models. Lesion apparent diffusion coefficient (ADC) values were assessed with inter-class correlation (ICC) and Bland-Altman analyses. DWI's delineation geometric similarity to T1-weighted post-contrast (T1Wc) MRI was evaluated using the Dice Similarity Coefficient (DSC) before and after registration. Recurrence in post-treatment SCC scans was evaluated by the same two radiologists blinded for DW-technique. Recurrence detection rates were then compared between DW-SPLICE and DW-EPI using mixed logistic regression at six months and at one-year post-scan follow-up data. From August 2020 to January 2022, 55 benign or malignant lesion scans (55 patients) and 74 post-treatment SCC scans (66 patients) were analyzed. DW-SPLICE scored better on image quality and showed less overall distortion than DW-EPI (0.04<p<0.001). There was high ADC measurement reliability (ICC=0.93, p<0.001), though a proportional bias was also observed (β=0.11, p=0.03), indicating the bias increases as ADC values rise. DWSPLICE exhibited greater geometric similarity to T1Wc before registration (DSC 0.63 vs 0.47, p<0.001) and outperformed DW-EPI by more accurately identifying recurrences after one year (OR=0.96, p=0.05) but not after six months (OR=0.72, p=0.13). DW-SPLICE surpasses DW-EPI on image distortion and quality and improves diagnostic reliability for detecting recurrent or residual SCC on 3T MRI of the HN. Consistent use of one method for follow-up is advised, as ADC values are not completely interchangeable. Integrating DW-SPLICE can significantly improve tumor assessments in clinical practice. ANTs = Advanced Normalization Tools; DSC = Dice Similarity Coefficient; DW-EPI = Diffusion-weighted single-shot echo planar imaging; DW-MS-EPI = Diffusion-weighted multi-shot echo planar imaging; DW-SPLICE = Diffusion-weighted split acquisition of fast spin echo signals for diffusion imaging; DW-TSE = Diffusion-weighted Turbo Spin Echo; ICC = Intraclass Correlation Coefficient; ROC = Receiver Operating Characteristic; SCC = Squamous cell carcinoma; T1WIc = T1 weighted imaging with gadolinium contrast.

Time-Dependent Diffusion MRI Helps Predict Molecular Subtypes and Treatment Response to Neoadjuvant Chemotherapy in Breast Cancer.

Background Time-dependent diffusion MRI has the potential to help characterize tumor cell properties; however, to the knowledge of the authors, its usefulness for breast cancer diagnosis and prognostic evaluation is unknown. Purpose To investigate the clinical value of time-dependent diffusion MRI-based microstructural mapping for noninvasive prediction of molecular subtypes and pathologic complete response (pCR) in participants with breast cancer. Materials and Methods Participants with invasive breast cancer who underwent pretreatment with time-dependent diffusion MRI between February 2021 and May 2023 were prospectively enrolled. Four microstructural parameters were estimated using the IMPULSED method (a form of time-dependent diffusion MRI), along with three apparent diffusion coefficient (ADC) measurements and a relative ADC diffusion-weighted imaging parameter. Multivariable logistic regression analysis was used to identify parameters associated with each molecular subtype and pCR. A predictive model based on associated parameters was constructed, and its performance was assessed using the area under the receiver operating characteristic curve (AUC) and compared by using the DeLong test. The time-dependent diffusion MRI parameters were validated based on correlation with pathologic measurements. Results The analysis included 408 participants with breast cancer (mean age, 51.9 years ± 9.1 [SD]). Of these, 221 participants were administered neoadjuvant chemotherapy and 54 (24.4%) achieved pCR. The time-dependent diffusion MRI parameters showed reasonable performance in helping to identify luminal A (AUC, 0.70), luminal B (AUC, 0.78), and triple-negative breast cancer (AUC, 0.72) subtypes and high performance for human epidermal growth factor receptor 2 (HER2)-enriched breast cancer (AUC, 0.85), outperforming ADC measurements (all P < .05). Progesterone receptor status (odds ratio [OR], 0.08; P = .02), HER2 status (OR, 3.36; P = .009), and the cellularity index (OR, 0.01; P = .02) were independently associated with the odds of achieving pCR. The combined model showed high performance for predicting pCR (AUC, 0.88), outperforming ADC measurements and the clinical-pathologic model (AUC, 0.73 and 0.79, respectively; P < .001). The time-dependent diffusion MRI-estimated parameters correlated well with the pathologic measurements (n = 100; r = 0.67-0.81; P < .001). Conclusion Time-dependent diffusion MRI-based microstructural mapping was an effective method for helping to predict molecular subtypes and pCR to neoadjuvant chemotherapy in participants with breast cancer. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Partridge and Xu in this issue.

The QIBA Profile for Diffusion-Weighted MRI: Apparent Diffusion Coefficient as a Quantitative Imaging Biomarker.

The apparent diffusion coefficient (ADC) provides a quantitative measure of water mobility that can be used to probe alterations in tissue microstructure due to disease or treatment. Establishment of the accepted level of variance in ADC measurements for each clinical application is critical for its successful implementation. The Diffusion-Weighted Imaging Biomarker Committee of the Quantitative Imaging Biomarkers Alliance (QIBA) has recently advanced the ADC Profile from the consensus to clinically feasible stage for the brain, liver, prostate, and breast. This profile distills multiple studies on ADC repeatability and describes detailed procedures to achieve stated performance claims on an observed ADC change within acceptable confidence limits. In addition to reviewing the current ADC Profile claims, this report has used recent literature to develop proposed updates for establishing metrology benchmarks for mean lesion ADC change that account for measurement variance. Specifically, changes in mean ADC exceeding 8% for brain lesions, 27% for liver lesions, 27% for prostate lesions, and 15% for breast lesions are claimed to represent true changes with 95% confidence. This report also discusses the development of the ADC Profile, highlighting its various stages, and describes the workflow essential to achieving a standardized implementation of advanced quantitative diffusion-weighted MRI in the clinic. The presented QIBA ADC Profile guidelines should enable successful clinical application of ADC as a quantitative imaging biomarker and ensure reproducible ADC measurements that can be used to confidently evaluate longitudinal changes and treatment response for individual patients.

Different Sodium Concentrations of Noncancerous and Cancerous Prostate Tissue Seen on MRI Using an External Coil

Abstract Background Sodium (23Na) MRI of prostate cancer (PCa) is a novel but under-documented technique conventionally acquired using an endorectal coil. These endorectal coils are associated with challenges (e.g., a non-uniform sensitivity profile, limited prostate coverage, patient discomfort) that could be mitigated with an external 23Na MRI coil. Purpose To quantify tissue sodium concentration (TSC) differences within the prostate of participants with PCa and healthy volunteers using an external 23Na MRI radiofrequency coil at 3 Tesla. Materials and Methods A prospective study was conducted from January 2022 to June 2024 in healthy volunteers and participants with biopsy-proven PCa. Prostate 23Na MRI was acquired on a 3 Tesla PET/MRI scanner using a custom-built two-loop (diameter, 18 cm) butterfly surface coil tuned for the 23Na frequency (32.6 MHz). The percent difference in TSC (ΔTSC) between prostate cancer lesions and surrounding noncancerous prostate tissue of the peripheral zone (PZ) and transition zone (TZ) was evaluated using a one-sample t-test. TSC was compared to apparent diffusion coefficient (ADC) measurements as a clinical reference. Results 6 healthy volunteers (mean age, 54.5 years ± 12.7) and 20 participants with PCa (mean age, 70.7 years ± 8.3) were evaluated. A total of 31 lesions were detected (21 PZ, 10 TZ) across PCa participants. Compared to noncancerous prostate tissue, prostate cancer lesions had significantly lower TSC (ΔTSC, -14.1% ± 18.2, p = 0.0002) and ADC (ΔADC, -26.6% ± 18.7, p &amp;lt; 0.0001). Conclusion We used an external 23Na MRI coil for whole-gland comparison of TSC in PCa and noncancerous prostate tissue at 3 Tesla. PCa lesions presented with lower TSC compared to surrounding noncancerous PZ and TZ tissue. These findings demonstrate the feasibility of an external 23Na MRI coil to quantify TSC in the prostate and offer a promising, non-invasive approach to prostate cancer diagnosis and management.

Role of diffusion-weighted imaging in the diagnosis of pituitary region tumors.

This study aimed to assess the role of Diffusion-Weighted Imaging (DWI) in routine pituitary Magnetic Resonance Imaging (MRI) protocols for distinguishing sellar and parasellar tumors, addressing the lack of clear guidelines in contemporary literature. A retrospective analysis of 242 pituitary MRI scans with DWI sequences was conducted in a single-center study using a 1.5T scanner and standard DWI sequence parameters. Measurements of both absolute and relative mean apparent diffusion coefficient (ADC) values, along with minimal ADC values within tumors, were performed. The adopted region of interest (ROI) based method used for these measurements was validated. Invasive pituitary adenomas exhibited significantly lower min ADC and min rADC than meningiomas, with optimal cut-off points of 0.64 (sensitivity 73%, specificity 82%) and 0.78 (sensitivity 73%, specificity 89%), respectively. Post-hemorrhagic pituitary adenomas demonstrated lower ADC values than adamantinomatous craniopharyngiomas, with an AUC of 0.893 for min rADC = 1.07, and Rathke's Cleft Cysts with mucous content, AUC 0.8 for min rADC = 1.01. Specific differentiation with high sensitivity and specificity based on diffusion parameters was observed for these tumor groups. Cystic pituitary non-functional adenomas obtained significantly lower ADC values compared to the adamantinomatous type of craniopharyngiomas and serous Rathke's Cleft Cysts (AUC up to 0.942). The study concludes that integrating DWI into routine pituitary MRI protocols enhances diagnostic accuracy in distinguishing sellar and parasellar tumors. The short scan time of one minute makes DWI a valuable and precise tool, supporting its recommendation as a standard component of pituitary MRI examinations.

Transient elastography and diffusion-weighted magnetic resonance imaging for assessment of liver fibrosis in children with chronic hepatitis C.

Chronic hepatitis C (CHC) is a health burden with consequent morbidity and mortality. Liver biopsy is the gold standard for evaluating fibrosis and assessing disease severity and prognostic purposes post-treatment. Noninvasive alternatives for liver biopsy such as transient elastography (TE) and diffusion-weighted magnetic resonance imaging (DW-MRI) are critical needs. To evaluate TE and DW-MRI as noninvasive tools for predicting liver fibrosis in children with CHC. This prospective cross-sectional study initially recruited 100 children with CHC virus infection. Sixty-four children completed the full set of investigations including liver stiffness measurement (LSM) using TE and measurement of apparent diffusion coefficient (ADC) of the liver and spleen using DW-MRI. Liver biopsies were evaluated for fibrosis using Ishak scoring system. LSM and liver and spleen ADC were compared in different fibrosis stages and correlation analysis was performed with histopathological findings and other laboratory parameters. Most patients had moderate fibrosis (73.5%) while 26.5% had mild fibrosis. None had severe fibrosis or cirrhosis. The majority (68.8%) had mild activity, while only 7.8% had moderate activity. Ishak scores had a significant direct correlation with LSM (P = 0.008) and were negatively correlated with both liver and spleen ADC but with no statistical significance (P = 0.086 and P = 0.145, respectively). Similarly, histopathological activity correlated significantly with LSM (P = 0.002) but not with liver or spleen ADC (P = 0.84 and 0.98 respectively). LSM and liver ADC were able to significantly discriminate F3 from lower fibrosis stages (area under the curve = 0.700 and 0.747, respectively) with a better performance of liver ADC. TE and liver ADC were helpful in predicting significant fibrosis in children with chronic hepatitis C virus infection with a better performance of liver ADC.

Simultaneous multislice echo-planar diffusion-weighted imaging (DWI) in patients with focal liver lesions: a comparative study with conventional DWI.

Simultaneous multislice (SMS) technology improves acquisition efficiency of diffusion-weighted imaging (DWI). This study aimed to evaluate the performance of SMS-DWI in image quality and apparent diffusion coefficient (ADC) measurements for focal liver lesions (FLLs) as compared with that of conventional DWI (CON-DWI). The institutional ethics committee of West China Hospital, Sichuan University approved this single-center, prospective study conducted from February 2021 to March 2022. Free-breathing SMS-DWI and CON-DWI examinations were acquired on a 3-T scanner with b-values of 50, 400, and 800 s/mm2. Qualitative image quality and quantitative measurements of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and ADC were compared between SMS-DWI and CON-DWI. The ADC values for FLLs were further compared between SMS-DWI and CON-DWI in different patient subgroups. The intra- and interreader agreements were assessed. Significance was set at P<0.05. This study included 116 patients (96 males, 20 females; mean age 52.0±10.7 years) with 119 FLLs. No significant differences were observed between SMS-DWI and CON-DWI regarding overall image quality in any b-value DWIs, and there were also no differences observed between SMS-DWI and CON-DWI (b=800 s/mm2) for either SNR or CNR (both P values >0.05). ADC values obtained from CON-DWI were higher than those from SMS-DWI in all FLLs [(1.31±0.47)×10-3 vs. (1.26±0.46)×10-3 mm2/s; P=0.004], and similar findings were observed across the different patient subgroups. The consistency analysis showed intrareader intraclass correlation coefficient (ICC) values of 0.792-0.944 and interreader ICC values of 0.758-0.861 for quantitative measurements (SNR, CNR, and ADC) and kappa values of 0.609-0.878 for qualitative image quality. SMS-DWI achieved a 37% reduction in scan time compared to CON-DWI while maintaining comparable overall image quality. Notably, the ADC values for FLLs were observed to be quantitatively lower with SMS-DWI.

Assessment of prognostic indicators and KRAS mutations in rectal cancer using a fractional-order calculus MR diffusion model: whole tumor histogram analysis.

This study aims to explore the relationship between apparent diffusion coefficient (ADC) and fractional-order calculus (FROC)-specific parameters with prognostic indicators and Kirsten rat sarcoma viral oncogene homologue (KRAS) mutation status in rectal cancer. One hundred fifty-eight patients with rectal cancer were retrospectively enrolled. Histogram measurements of ADC, diffusion coefficient (D), intravoxel diffusion heterogeneity (β), and a microstructural quantity (μ) were estimated for the whole-tumor volume. The relationships between histogram measurements and prognostic indicators were evaluated. The efficacy of histogram measurements, both conducted singly and in conjunction, for evaluating different KRAS mutation statuses was also assessed. The performance of mean and median histogram measurements in evaluating various KRAS mutation statuses was assessed using Receiver Operating Characteristic (ROC) curve analysis. A p-value of less than 0.05 was considered statistically significant. The histogram measurements of ADC, D, β, and μ differed significantly between well-moderately differentiated groups and poorly differentiated groups, T1-2 and T3-4 subgroups, lymph node metastasis (LNM)-negative and LNM-positive subgroups, extranodal extension (ENE)-negative and ENE-positive subgroups, tumor deposit (TD)-negative and TD-positive subgroups, and lymphovascular invasion (LVI)-negative and LVI-positive subgroups. The combination of Dmean, βmean, and μmean achieved the highest performance [The area under the ROC curve (AUC) = 0.904] in evaluating the KRAS mutation status. When assessing parameters from the FROC model as potential biomarkers through histograms, they surpass traditional ADC values in distinguishing prognostic indicators and determining KRAS mutation status in rectal cancer.

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.

Primary sclerosing cholangitis: Is qualitative and quantitative 3 T MR imaging useful for the evaluation of disease severity?

PurposeTo analyze the role of qualitative and quantitative 3 T MR imaging assessment as a non-invasive method for the evaluation of disease severity in patients with primary sclerosing cholangitis (PSC). MethodsA series of 26 patients, with histological diagnosis of PSC undergoing 3 T MRI and hepatological evaluation, was retrospectively enrolled. All MR examinations included diffusion-weighted imaging (DWI), T2-weighted (T2w) and T1-weighted (T1w) sequences, before and after administration of Gd-EOB-DTPA with the acquisition of both dynamic and hepato-biliary phase (HBP). Qualitative analysis was performed by assessment of liver parenchyma and biliary tract changes, also including biliary excretion of gadoxetic acid on HBP. Quantitative evaluation was conducted on liver parenchyma by measurement of apparent diffusion coefficient (ADC) and relative enhancement (RE) on 3-minute delayed phase and on HBP. Results of blood tests (ALT, ALP, GGT, total and direct bilirubin, albumin, and platelets) and transient elastography-derived liver stiffness measurements (TE-LSM) were collected and correlated with qualitative and quantitative MRI findings. ResultsAmong qualitative and quantitative findings, fibrosis visual assessment and RE had the best performance in estimating disease severity, showing a statistically significant correlation with both biomarkers of cholestasis and TE-LSM. Statistical analysis also revealed a significant correlation of gadoxetic acid biliary excretion with ALT and direct bilirubin, as well as of ADC with total bilirubin. ConclusionQualitative and quantitative 3 T MR evaluation is a promising non-invasive method for the assessment of disease severity in patients with PSC.

Extraocular muscle Diffusion Weighted Imaging as a quantitative metric of posterior orbital involvement in thyroid associated orbitopathy

ObjectivesThe clinical activity score (CAS) and European severity scale (ESS) are established clinical tools to assess thyroid eye disease (TED) but are limited in terms of subjectivity and their reliability in non-Caucasian individuals, and can underestimate significant disease in the posterior orbit. Preliminary data from pilot studies have shown that diffusion-weighted imaging (DWI) using extraocular muscle (EOM) apparent diffusion coefficient (ADC) measurements may provide complementary information in TED. This study expands on previous research to assess for correlations between clinical scores and EOM-ADCs in stratifying disease activity and severity in a large patient cohort from an ethnically diverse population.MethodsA retrospective review of TED clinics between 2011 and 2021 identified 96 patients with a documented CAS and ESS and an orbital MRI that included DWI. From regions of interest manually placed on EOM bellies, the highest ADC was computed for each patient and analysed for correlations and associations with CAS and ESS using Spearman Rank correlation and Mann–Whitney U tests, and any potential discriminatory cut-offs using Receiver Operator Curve analyses. A p-value < 0.05 indicated statistical significance.ResultsEOM-ADCs showed a positive association with CAS (p ≤ 0.001). EOM-ADCs were higher in sight-threatening compared to mild disease (p ≤ 0.01). A cut-off of 995 mm2/s achieved AUC = 0.7744, equating to 77% sensitivity and 67% specificity for discrimination between mild-moderate and sight-threatening disease.ConclusionEOM-ADCs correlate with higher scores of disease severity and activity in TED. Besides providing quantitative data to support clinical tools, EOM-ADC cut-offs may identify patients at risk of developing sight-threatening diseases.Critical relevance statementThis study critically evaluates the limitations of conventional clinical assessment tools for TED and demonstrates the utility of DWI scans with ADC measurements in identifying active disease, offering valuable insights to advance clinical radiology practice.Key PointsConventional tools for TED assessment have subjective limitations.ADCs from non-echoplanar diffusion-weighted imaging correlate with clinical activity.Non-echoplanar diffusion-weighted imaging offers quantitative assessment to aid clinical practice reliability.Graphical

Influence of Gadolinium-based Contrast Media and Inter-reader Variation on the Estimation of Intravoxel Incoherent Motion (IVIM) Parameters in Breast MR Imaging.

Gadolinium-based contrast media (GBCM) may affect apparent diffusion coefficient measurements on diffusion-weighted imaging. We aimed at investigating the effect of GBCM and inter-reader variation on intravoxel incoherent motion (IVIM) parameters in breast lesions. A total of 89 patients referred to 3T breast MRI with at least one histologically verified lesion were included. IVIM data were acquired using a single-shot echo planar imaging sequence before and after GBCM administration. D (true diffusion coefficient), D* (pseudo-diffusion coefficient) and f (perfusion fraction) were calculated and measured by two readers (R1, R2). Inter-reader and intra-reader agreements were assessed by intraclass correlation coefficients (ICCs) and Bland-Altman plots. D was comparable before and after GBCM administration and between readers. D* and f decreased after GBCM administration and showed a lower agreement between readers. Intra-reader agreement before and after GBCM administration was almost perfect for D for both R1 and R2 (ICC 0.955 and 0.887). The intra-reader agreement was substantial to moderate for D* (ICC R1 0.708, R2 0.583) and moderate for f (ICC R1 0.529 and R2 0.425). Inter-reader agreement before GBCM administration was almost perfect for D (ICC 0.905), substantial for D* (ICC 0.733), and moderate for f (ICC 0.404); after contrast media administration, it was almost perfect for D (ICC 0.876) and substantial for D* (ICC 0.654) and f (ICC 0.606). Bland-Altman plots revealed no significant bias. Administration of GBCM seems to have a stronger effect on D* and f values than on D values. This should be considered when applying IVIM in clinical practice.

Treatment response assessment of acute pyelonephritis: A multi-reader DWI-based MRI approach

PurposeTo evaluate the diagnostic accuracy of a structured reporting score (SRS) in treatment response assessment for acute pyelonephritis (APN) using a diffusion-weighted imaging (DWI) -based MRI approach. Additionally, we explored the influence of reader experience on the interpretation of SRS and DWI, including lesion conspicuity and measurements of Apparent Diffusion Coefficient (ADC) maps. MethodsFollow-up DWI-based MRIs of 36 patients treated for APN between September 2021 and June 2023 were retrospectively reviewed by three readers. Follow-up blood inflammatory markers were used as reference standard. Treatment response was assessed using a structured reporting score (SRS). Each reader assigned a score from 1 to 3 to the "conspicuity" of the residual disease on DWI. Quantitative ADC measurements were compared with the Mann-Whitney U test. Descriptive statistics and Intraclass Correlation Coefficient (ICC) were calculated. ResultsThe diagnostic accuracy of SRS was 80.6 %, 76.9 %, and 72.2 % for the Reader 1, 2, and 3 respectively. ICC decreased from 0.82 (Reader 1 and 2), to 0.68 when considering all readers. The average conspicuity varied between 2.3 and 2.7. ADC values were significantly higher in complete responders for Reader 1 and 2 (153.5-154.5 vs 107.7-116.2, p < 0.001). The ICC was good (0.89) for Reader 1 and 2 and moderate (0.60) when considering all readers. ConclusionsTreatment response of pyelonephritis can be accurately assessed by a DWI-based MRI, potentially avoiding unnecessary contrast agent administration and radiation exposure. SRS and DWI analysis showed a good inter-observer agreement but a certain learning curve may be necessary for less expert readers.

Qualitative and quantitative MRI analysis of alveolar soft part sarcoma: correlation with histological grade and Ki-67 expression

ObjectiveTo investigate the correlation between MRI findings and histological features for preoperative prediction of histological grading and Ki-67 expression level in alveolar soft part sarcoma (ASPS).MethodsA retrospective analysis was conducted on 63 ASPS patients (Jan 2017–May 2023). All patients underwent 3.0-T MRI examinations, including conventional sequences, dynamic contrast-enhanced scans with time-intensity curve analysis, and diffusion-weighted imaging with apparent diffusion coefficient (ADC) measurements. Patients were divided into low-grade (histological Grade I) and high-grade (histological Grade II/III) groups based on pathology. Immunohistochemistry was used to assess Ki-67 expression levels in ASPS. Statistical analysis included chi-square tests, Wilcoxon rank-sum test, binary logistic regression analysis, Spearman correlation analysis, and receiver operating characteristic curve analysis of various observational data.ResultsThere were 29 low-grade and 34 high-grade patients (26 males and 37 females) and a wide age range (5–68 years). Distant metastasis, tumor enhancement characteristics, and ADC values were independent predictors of high-grade ASPS. High-grade ASPS had lower ADC values (p = 0.002), with an area under the curve (AUC), sensitivity, and specificity of 0.723, 79.4%, and 58.6%, respectively, for high-grade prediction. There was a negative correlation between ADC values and Ki-67 expression (r = −0.526; p < 0.001). When the cut-off value of ADC was 0.997 × 10−3 mm²/s, the AUC, sensitivity, and specificity for predicting high Ki-67 expression were 0.805, 65.6%, and 83.9%, respectively.ConclusionQualitative and quantitative MRI parameters are valuable for predicting histological grading and Ki-67 expression levels in ASPS.Critical relevance statementThis study will help provide a more nuanced understanding of ASPS and guide personalized treatment strategies.Key PointsThere is limited research on assessing ASPS prognosis through MRI.Metastasis, enhancement, and ADC correlated with histological grade; ADC related to Ki-67 expression.MRI provides clinicians with valuable information on ASPS grading and proliferation activity.Graphical

The performance of the node reporting and data system 1.0 (Node-RADS) and DWI–MRI in staging patients with cervical carcinoma according to the new FIGO classification (2018)

PurposeTo evaluate the diagnostic accuracy of the Node-RADS score and the utility of apparent diffusion coefficient (ADC) values in predicting metastatic lymph nodes (LNs) involvement in cervical cancer (CC) patients using magnetic resonance imaging (MRI). The applicability of the Node RADS score across three readers with different years of experience in pelvic imaging was also assessed.Material and methodsAmong 140 patients, 68 underwent staging MRI, neoadjuvant chemotherapy and radical surgery, forming the study cohort. Node-RADS scores of the main pelvic stations were retrospectively determined to assess LN metastatic likelihood and compared with the histological findings. Mean ADC, relative ADC (rADC), and correct ADC (cADC) values of LNs classified as Node-RADS ≥ 3 were measured and compared with histological reports, considered as gold standard.ResultsSensitivity, specificity, positive and negative predictive values (PPVs and NPVs), and accuracy were calculated for different Node-RADS thresholds. Node RADS ≥ 3 showed a sensitivity of 92.8% and specificity of 72.5%. Node RADS ≥ 4 yielded a sensitivity of 71.4% and specificity of 100%, while Node RADS 5 yielded 42.9% and 100%, respectively. The diagnostic performance of mean ADC, cADC and rADC values from 78 LNs with Node-RADS score ≥ 3 was assessed, with ADC demonstrating the highest area under the curve (AUC 0.820), compared to cADC and rADC values.ConclusionThe Node-RADS score provides a standardized LNs assessment, enhancing diagnostic accuracy in CC patients. Its ease of use and high inter-observer concordance support its clinical utility. ADC measurement of LNs shows promise as an additional tool for optimizing patient diagnostic evaluation.