Effect of Liver Segments and Hepatic Fibrosis Grade on Repeatability, Reliability, and Diagnostic Efficiency of Intravoxel Incoherent Motion

BACKGROUND

Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) is considered a potential marker of hepatic fibrosis (HF).

OBJECTIVE

To explore the influencing factors of repeatability and reliability in IVIM-DWI parameters of ROI-based liver segments in participants with HF and healthy volunteers (HV) and to assess the diagnostic efficiency of these parameters in HF.

METHODS

Participants with early HF (EHF, n=59) or advanced HF (AHF, n=38) and HV (n=48) were recruited. Two examiners measured IVIM data using mono-, bi-exponential and stretched exponential models. The results and influencing factors of repeatability and reliability of IVIM-DWI, and the diagnostic efficiency were analyzed.

RESULTS

The repeatability of D* (CV: 26.62-41.47%) and DDC (CV: 18.01-34.40%) was poor, the repeatability of ADC (CV: 4.95-9.76%), D (CV: 7.09-15.52%), f (CV: 9.35-17.15%), and α (CV: 7.48-13.81%) was better; ordered logistic regression showed statistically significant results of IVIM-derived parameters; the reliability showed no obvious trend, and ordered logistic regression showed statistically significant results of IVIMderived parameters, groups, and partial hepatic segments (all p<0.001). IVIM-derived parameters with relatively good repeatability (CV<20%) and reliability (ICC>0.4) were used to establish regression models for differential diagnosis. The AUC of regression models was 0.744-0.783 (EHF vs. AHF), but no statistically significant parameters were found in the HV vs EHF comparison.

CONCLUSION

IVIM-derived parameters were the most important factors affecting the repeatability and reliability, while staging of HF and hepatic segments may be the influencing factors of reliability. IVIM-derived parameters showed medium diagnostic efficiency in distinguishing between EHF and AHF.

Diagnostic test accuracy study of a commercially available deep learning algorithm for ischemic lesion detection on brain MRIs in suspected stroke patients from a non-comprehensive stroke center

PURPOSE

To estimate the ability of a commercially available artificial intelligence (AI) tool to detect acute brain ischemia on Magnetic Resonance Imaging (MRI), compared to an experienced neuroradiologist.

METHODS

We retrospectively included 1030 patients with brain MRI, suspected of stroke from January 6th, 2020 to 1st of April 2022, based on these criteria: Age ≥ 18 years, symptoms within four weeks before the scan. The neuroradiologist reinterpreted the MRI scans and subclassified ischemic lesions for reference. We excluded scans with interpretation difficulties due to artifacts or missing sequences. Four MRI scanner models from the same vendor were used. The first 800 patients were included consecutively, remaining enriched for less frequent lesions. The index test was a CE-approved AI tool (Apollo version 2.1.1 by Cerebriu).

RESULTS

The final analysis cohort comprised 995 patients (mean age 69 years, 53 % female). A case-based analysis for detecting acute ischemic lesions showed a sensitivity of 89 % (95 % CI: 85 %-91 %) and specificity of 90 % (95 % CI: 87 %-92 %). We found no significant difference in sensitivity or specificity based on sex, age, or comorbidities. Specificity was reduced in cases with DWI artifacts. Multivariate analysis showed that increasing ischemic lesion size and fragmented lesions were independently associated with higher sensitivity, while non-acute lesion ages lowered sensitivity.

CONCLUSIONS

The AI tool exhibits high sensitivity and specificity in detecting acute ischemic lesions on MRI compared to an experienced neuroradiologist. While sensitivity depends on the ischemic lesions' characteristics, specificity depends on the image quality.

Whole body MRI with Diffusion Weighted Imaging versus 18F-fluorodeoxyglucose-PET/CT in the staging of lymphomas

PURPOSE

To assess the diagnostic performance of Whole Body (WB)-MRI in comparison with 18F-Fluorodeoxyglucose-PET/CT (18F-FDG-PET/CT) in lymphoma staging and to assess whether quantitative metabolic parameters from 18F-FDG-PET/CT and Apparent Diffusion Coefficient (ADC) values are related.

MATERIALS AND METHODS

We prospectively enrolled patients with a histologically proven primary nodal lymphoma to  undergo 18F-FDG-PET/CT and WB-MRI, both performed within 15 days one from the other, either before starting treatment (baseline) or during treatment (interim). Positive and negative predictive values of WB-MRI for the identification of nodal and extra-nodal disease were measured. The agreement between WB-MRI and 18F-FDG-PET/CT for the identification of lesions and staging was assessed through Cohen's coefficient k and observed agreement. Quantitative parameters of nodal lesions derived from 18F-FDG-PET/CT and WB-MRI (ADC) were measured and the Pearson or Spearman correlation coefficient was used to assess the correlation between them. The specified level of significance was p ≤ 0.05.

RESULTS

Among the 91 identified patients, 8 refused to participate and 22 met exclusion criteria, thus images from 61 patients (37 men, mean age 30.7 years) were evaluated. The agreement between 18F-FDG-PET/CT and WB-MRI for the identification of nodal and extra-nodal lesions was 0.95 (95% CI 0.92 to 0.98) and 1.00 (95% CI NA), respectively; for staging it was 1.00 (95% CI NA). A strong negative correlation was found between ADCmean and SUVmean of nodal lesions in patients evaluated at baseline (Spearman coefficient r_s = - 0.61, p = 0.001).

CONCLUSION

WB-MRI has a good diagnostic performance for staging of patients with lymphoma in comparison with 18F-FDG-PET/CT and is a promising technique for the quantitative assessment of disease burden in these patients.

Test-retest repeatability of ADC in prostate using the multi b-Value VERDICT acquisition

PURPOSE

VERDICT (Vascular, Extracellular, Restricted Diffusion for Cytometry in Tumours) MRI is a multi b-value, variable diffusion time DWI sequence that allows generation of ADC maps from different b-value and diffusion time combinations. The aim was to assess precision of prostate ADC measurements from varying b-value combinations using VERDICT and determine which protocol provides the most repeatable ADC.

MATERIALS AND METHODS

Forty-one men (median age: 67.7 years) from a prior prospective VERDICT study (April 2016-October 2017) were analysed retrospectively. Men who were suspected of prostate cancer and scanned twice using VERDICT were included. ADC maps were formed using 5b-value combinations and the within-subject standard deviations (wSD) were calculated per ADC map. Three anatomical locations were analysed per subject: normal TZ (transition zone), normal PZ (peripheral zone), and index lesions. Repeated measures ANOVAs showed which b-value range had the lowest wSD, Spearman correlation and generalized linear model regression analysis determined whether wSD was related to ADC magnitude and ROI size.

RESULTS

The mean lesion ADC for b0b1500 had the lowest wSD in most zones (0.18-0.58x10-4 mm2/s). The wSD was unaffected by ADC magnitude (Lesion: p = 0.064, TZ: p = 0.368, PZ: p = 0.072) and lesion Likert score (p = 0.95). wSD showed a decrease with ROI size pooled over zones (p = 0.019, adjusted regression coefficient = -1.6x10-3, larger ROIs for TZ versus PZ versus lesions). ADC maps formed with a maximum b-value of 500 s/mm2 had the largest wSDs (1.90-10.24x10-4 mm2/s).

CONCLUSION

ADC maps generated from b0b1500 have better repeatability in normal TZ, normal PZ, and index lesions.

Diagnostic value of T2 and diffusion-weighted imaging (DWI) in local staging of endometrial cancer

BACKGROUND

Endometrial cancer (EC) is the eighth most prevalent cancer globally. T2-weighted magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) help anatomical localization and local staging of lesions. The present study was performed to assess the diagnostic value of the simultaneous use of T2 and DWI techniques in EC evaluation.

METHODS

Seventy-eight histopathological-proven EC cases were included in this study. Patients were assessed using a complete MRI exam, including T2 and DWI. The myometrial invasion, cervical, serosal or adnexal, vaginal or parametrial, and pelvic lymph node involvements and accuracy, sensitivity, specificity, and positive and negative predictive values were evaluated in each sequence distinctly and was compared with the pathology findings and full standard protocol using post-contrast multiphasic contrast-enhanced series.

RESULTS

Deep myometrial invasion in EC cases was detected in 38.5% by T2-DWI and 37.2% by pathology. The pathology diagnosed cervical, serosal, and vaginal involvements and pelvic lymph node metastases in 20.5%, 7.7%, 6.4% and 11.5% of cases respectively, while the numbers for T2-DWI were 26.9%, 7.7%, 7.7%, and 15.4%, respectively. The accuracy, sensitivity, specificity, PPV, and NPV of T2-DWI in the diagnosis of myometrial invasion were 93.5%, 93.1%, 93.8%, 90%, and 93.8%, respectively. A slightly higher Kappa coefficient of DWI (0.973) in the diagnosis of myometrial invasion was identified compared to T2 (0.946). The T2-DWI technique had a 52.6% intraclass correlation coefficient in the diagnosis of IA stage.

CONCLUSION

The simultaneous consideration of T2 and DWI technique may signify a noninvasive, rapid, safe, and accurate approach for precisely assessing myometrial invasion and EC staging. Elimination of intravenous contrast material result in prevention of contrast related side effects beside significant cost reduction for health care systems and patients with a comparable result to contrast enhanced MRI.

MRI markers of brain network integrity relate to neurological outcome in postanoxic coma

AIM

Current multimodal approaches leave approximately half of the comatose patients after cardiac arrest with an indeterminate prognosis. Here we investigated whether early MRI markers of brain network integrity can distinguish between comatose patients with a good versus poor neurological outcome six months later.

METHODS

We performed a prospective cohort study in 48 patients after cardiac arrest submitted in a comatose state to the Intensive Care Unit of two Dutch hospitals. MRI was performed at three days after cardiac arrest, including resting state functional MRI and diffusion-tensor imaging (DTI). Resting state fMRI was used to quantify functional connectivity within ten resting-state networks, and DTI to assess mean diffusivity (MD) in these same networks. We contrasted two groups of patients, those with good (n = 29, cerebral performance category 1-2) versus poor (n = 19, cerebral performance category 3-5) outcome at six months. Mutual associations between functional connectivity, MD, and clinical outcome were studied.

RESULTS

Patients with good outcome show higher within-network functional connectivity (fMRI) and higher MD (DTI) than patients with poor outcome across 8/10 networks, most prominent in the default mode network, salience network, and visual network. While the anatomical distribution of outcome-related changes was similar for functional connectivity and MD, the pattern of inter-individual differences was very different: functional connectivity showed larger inter-individual variability in good versus poor outcome, while the opposite was observed for MD. Exploratory analyses suggested that it is possible to define network-specific cut-off values that could help in outcome prediction: (1) high functional connectivity and high MD, associated with good outcome; (2) low functional connectivity and low MD, associated with poor outcome; (3) low functional connectivity and high MD, associated with uncertain outcome.

DISCUSSION

Resting-state functional connectivity and mean diffusivity-three days after cardiac arrest are strongly associated with neurological recovery-six months later in a complementary fashion. The combination of fMRI and MD holds potential to improve prediction of outcome.

Microstructural breast tissue characterization: A head-to-head comparison of Diffusion Weighted Imaging and Acoustic Radiation Force Impulse elastography with clinical implications

PURPOSE

Head-to-head comparison of Diffusion Weighted Imaging (DWI) and Acoustic Radiation Force Impulse (ARFI) elastography regarding the characterization of breast lesions in an assessment setting.

METHOD

Patients undergoing an ultrasound examination including ARFI and an MRI protocol including DWI for the characterization of a BI-RADS 3-5 breast lesion between 06/2013 and 10/2016 were eligible for inclusion in this retrospective, IRB-approved study. 60 patients (30-84 years, median 50) with a median lesion size of 16 mm (range 5-55 mm) were included. The maximum shear wave velocity (SWV_max) and mean apparent diffusion coefficient (ADC_mean) for each lesion were retrospectively evaluated by a radiologist experienced in the technique. Histology was the reference standard. Diagnostic performances of ARFI and DWI were assessed using ROC curve analysis. Spearman's rank correlation coefficient and multivariate logistic regression were used to investigate the independence of both tests regarding their diagnostic information to distinguish benign from malignant lesions.

RESULTS

Corresponding areas under the ROC curve for differentiation of benign (n = 16) and malignant (n = 49) lesions were 0.822 (ARFI) and 0.871 (DWI, p-value = 0.48). SWVmax and ADCmean values showed a significant negative correlation (ρ = -0.501, p-value < 0.001). In multivariate analysis, combination of ARFI and DWI did not improve the results of each single modality, thus no significant independent diagnostic information was present.

CONCLUSION

Significant correlation between quantitative findings of ARFI and DWI in breast lesions exists. Thus, ARFI provides similar diagnostic information as a DWI-including protocol of an additional "problem-solving" MRI for the characterization of a sonographically evident breast lesion, improving the immediate patient management in the assessment setting.

Staging, recurrence and follow-up of uterine cervical cancer using MRI: Updated Guidelines of the European Society of Urogenital Radiology after revised FIGO staging 2018

OBJECTIVES

The recommendations cover indications for MRI examination including acquisition planes, patient preparation, imaging protocol including multi-parametric approaches such as diffusion-weighted imaging (DWI-MR),  dynamic contrast-enhanced imaging (DCE-MR) and standardised reporting. The document also underscores the value of whole-body 18-Fluorodeoxyglucose Positron Emission Tomography/Computed Tomography (FDG-PET/CT) and highlights potential future methods.

METHODS

In 2019, the ESUR female pelvic imaging working group reviewed the revised 2018 FIGO staging system, the up-to-date clinical management guidelines, and the recent imaging literature. The RAND-UCLA Appropriateness Method (RAM) was followed to develop the current ESUR consensus guidelines following methodological steps: literature research, questionnaire developments, panel selection, survey, data extraction and analysis.

RESULTS

The updated ESUR guidelines are recommendations based on ≥ 80% consensus among experts. If ≥ 80% agreement was not reached, the action was indicated as optional.

CONCLUSIONS

The present ESUR guidelines focus on the main role of MRI in the initial staging, response monitoring and evaluation of disease recurrence. Whole-body FDG-PET plays an important role in the detection of lymph nodes (LNs) and distant metastases.

KEY POINTS

• T2WI and DWI-MR are now recommended for initial staging, monitoring of response and evaluation of recurrence. • DCE-MR is optional; its primary role remains in the research setting. • T2WI, DWI-MRI and whole-body FDG-PET/CT enable comprehensive assessment of treatment response and recurrence.

Statistical and spatial correlation between diffusion and perfusion MR imaging parameters: A study on soft tissue sarcomas

PURPOSE

The purpose of this study was to examine the correlation of diffusion and perfusion quantitative MR parameters, on patients with malignant soft tissue tumors. In addition, we investigated the spatial agreement of hallmarks of malignancy as indicated by diffusion and perfusion biomarkers respectively.

METHODS

Nonlinear least squares were used for the quantification of the DWI and DCE derived parameters for 25 patients of histologically proven soft tissue sarcoma scanned at a 1.5 T scanner. 4D data were analyzed by an in house built software implemented in Python 3.5 resulting in voxel based parametric maps based on the Intra-Voxel Incoherent Motion (IVIM), Extended Toft's (ETM) and Gamma Capillary Transit time (GCTT) models. The root mean squared error (RMSE) was also used for assessing the accuracy of the DCE fitting models.

RESULTS

A good Pearson's correlation (r > 0.5) was found between micro-perfusion fraction (f-IVIM) and plasma volume (vp-GCTT). There was no significant correlation between all other possible pairs of DCE and DWI derived parameters. Following thresholding the indicators of malignancy from both imaging methods, the percentage of volume overlap between regions of high cellularity and high vascular permeability ranged from 6% to 30%.

CONCLUSION

A free correlation study among all DCE and DWI derived pairs of parameters, showed a linear relationship between f-IVIM and vp-GCTT in patients with soft tissue sarcomas. DCE in conjunction with DWI MRI can provide useful information on sites of aggressive characteristics for guiding the pre-operative biopsy and for overall treatment planning.

Cerebral hunger maps in rodents and humans by diffusion weighted MRI

We design, implement and validate a novel image processing strategy to obtain in vivo maps of hunger stimulation in the brain of mice, rats and humans, combining Diffusion Weighted Magnetic Resonance Imaging (DWI) datasets from fed and fasted subjects. Hunger maps were obtained from axial/coronal (rodents/humans) brain sections containing the hypothalamus and coplanar cortico-limbic structures using Fisher's Discriminant Analysis of the combined voxel ensembles from both feeding situations. These maps were validated against those provided by the classical mono-exponential diffusion model as applied over the same subjects and conditions. Mono-exponential fittings revealed significant Apparent Diffusion Coefficient (ADC) decreases through the brain regions stimulated by hunger, but rigorous parameter estimations imposed the rejection of considerable number of pixels. The proposed approach avoided pixel rejections and provided a representation of the combined DWI dataset as a pixel map of the "Hunger Index" (HI), a parameter revealing the hunger score of every pixel. The new methodology proved to be robust both, by yielding consistent results with classical ADC maps and, by reproducing very similar HI maps when applied to newly acquired rodent datasets. ADC and HI maps demonstrated similar patterns of activation by hunger in hypothalamic and cortico-limbic structures of the brain of rodents and humans, albeit with different relative intensities, rodents showing more intense activations by hunger than humans, for similar fasting periods. The proposed methodology may be easily extended to other feeding paradigms or even to alternative imaging methods.

Magnetic Resonance Imaging in Huntington's Disease

Magnetic resonance imaging (MRI) is a noninvasive technique used routinely to image the body in both clinical and research settings. Through the manipulation of radio waves and static field gradients, MRI uses the principle of nuclear magnetic resonance to produce images with high spatial resolution, appropriate for the investigation of brain structure and function.

A systematic review on multiparametric MR imaging in prostate cancer detection

BACKGROUND

Literature data suggest that multi-parametric Magnetic Resonance Imaging (MRI), including morphologic T2-weigthed images (T2-MRI) and functional approaches such as Dynamic Contrast Enhanced-MRI (DCE-MRI), Diffusion Weighted Imaging (DWI) and Magnetic Resonance Spectroscopic Imaging (MRSI), give an added value in the prostate cancer localization and local staging.

METHODS

We performed a systematic review of literature about the role and the potentiality of morphological and functional MRI in prostate cancer, also in a multimodal / multiparametric approach, and we reported the diagnostic accuracy results for different imaging modalities and for different MR coil settings: endorectal coil (ERC) and phased array coil (PAC). Forest plots and receiver operating characteristic curves were performed. Risk of bias and the applicability at study level were calculated.

RESULTS

Thirty three papers were identified for the systematic review. Sensitivity and specificity values were, respectively, for T2-MRI of 75% and of 60%, for DCE-MRI of 80% and of 72%, for MRSI of 89% and of 69%, for combined T2-MRI and DCE-MRI of 87% and of 46%, for combined T2-MRI and MRSI of 79% and of 57%, for combined T2-MRI, DWI and DCE-MRI of 81% and of 84%, and for combined MRSI and DCE-MRI of 83% and of 83%. For MRI studies performed with ERC we obtained a pooled sensitivity and specificity of 81% and of 66% while the pooled values for MRI studies performed with PAC were of 78% and of 64%, respectively (p>0.05 at McNemar test). No studies were excluded from the analysis based on the quality assessment.

CONCLUSIONS

ERC use yielded no additional benefit in terms of prostate cancer detection accuracy compared to multi-channel PAC use (71% versus 68%) while the use of additional functional imaging techniques (DCE-MRI, DWI and MRSI) in a multiparametric MRI protocol improves the accuracy of prostate cancer detection allowing both the early cure and the guidance of biopsy.

Comparison of the Prostate Imaging Reporting and Data System (PI-RADS) Version 1 and 2 in a Cohort of 245 Patients with Histopathological Reference and Long-Term Follow-Up

Objective:

To compare the performance of PI-RADSv2 with PI-RADSv1 in patients with elevated PSA before biopsy.

Methods:

245 patients with elevated PSA underwent mpMRI before biopsy between May 2011 and December 2014 at 3.0 Tesla without endorectal coil. Patients underwent transrectal ultrasound-guided systematic 12-core biopsy followed by radical prostatectomy (N = 68), radiation therapy (N = 91) or clinical follow-up for at least two years (N = 86). All exams were scored on a per-patient basis according to PI-RADSv1 and PI-RADSv2. ClinsigPC was defined as Gleason score ≥7 (including 3+4 with prominent but not predominant Gleason 4 component), and/or tumour volume of ≥0.5cc, and/or tumour stage ≥T3a.

Results:

In 144 patients (58.8%) a ClinsigPC was found within two years after mpMRI. The PI-RADSv1 and PI-RADSv2 overall assessment scores were significantly higher (P < 0.001) in patients with ClinsigPC as compared to patients without ClinsigPC. ROC analysis showed an area under the curve of 0.82 (CI 0.76–0.87) for PI-RADSv1 and 0.79 (CI 0.73–0.85) for PI-RADSv2 (P: NS). A threshold score of 3 exhibited sensitivities of 88.2% and 79.2% (P = 0.001) and specificities of 64.4% and 67.3% (P: NS) with PI-RADSv1 and PI-RADSv2, respectively.

Conclusions:

The mpMRI scoring systems PI-RADSv1 and PI-RADSv2 yield similar accuracy to detect ClinsigPC in patients with elevated PSA, although clinicians should be aware that when an overall assessment score of 3 is used as a threshold for a positive mpMRI, PI-RADSv2 has lower sensitivity than PI-RADSv1. Nevertheless, PI-RADSv2 is preferable over PI-RADSv1 because it has the advantage of providing well-defined instructions on how to determine the overall assessment category.

Optimising TNM Staging of Patients with Prostate Cancer Using WB-MRI

Multiparametric Magnetic Resonance Imaging (mp-MRI) is the current standard of reference for the local staging of prostate cancer (PCa). On the other hand, despite the low sensitivity and specificity of Technetium Bone Scanning (BS) for the detection of bone metastases (BM) and of Body Computed Tomography CT for the detection of lymph node metastases (LNM), these techniques are routinely used, in the current clinical practice. Nevertheless, whole Body MRI (WB-MRI) and Positron Emission Tomography Computed Tomography (PET-CT) are emerging as robust tools for the staging of oncologic patients, including those with (PCa).

The available techniques (BS, WB-MRI, PET, CT) for the detection of BM in oncologic patients were compared and showed striking center differences in terms of anatomic sequences and planes used. This heterogeneity and the long acquisition time of WB-MRI protocols – due to the addition of multiple anatomic sequences in different planes – questioned whether a single three dimensional (3D) sequence could replace the multiple anatomic sequences used for node and bone staging of PCa. We demonstrated that WB-MRI is a credible tool for the detection of bone and node metastasis.

The second question addressed the possibility to obtain a complete TNM staging of PCa in a single MRI session. A WB-MRI protocol was developed to enable complete, T (local), N (regional) and M (distant) staging of PCa in a single session, in less than an hour. This ‘all-in-one’ protocol proved to be as efficient as the sum of exams currently in use for the staging of PCa (ie: mp-MRI of the prostate for ‘T’ staging, Thoraco-abdominal CT for ‘N’ staging and bone scintigraphy for ‘M’ staging).

Investigating the prediction value of multiparametric magnetic resonance imaging at 3 T in response to neoadjuvant chemotherapy in breast cancer

Objective

To explore the predictive value of parameters derived from diffusion-weighted imaging (DWI) and contrast-enhanced (CE)-MRI at different time-points during neoadjuvant chemotherapy (NACT) in breast cancer.

Methods

Institutional review board approval and written, informed consent from 42 breast cancer patients were obtained. The patients were investigated before and at three different time-points during neoadjuvant chemotherapy (NACT) using tumour diameter and volume from CE-MRI and ADC values obtained from drawn 2D and segmented 3D regions of interest. Prediction of pathologic complete response (pCR) was evaluated using the area under the curve (AUC) of receiver operating characteristic analysis.

Results

There was no significant difference between pathologic complete response and non-pCR in baseline size measures (p > 0.39). Diameter change was significantly different in pCR (p < 0.02) before the mid-therapy point. The best predictor was lesion diameter change observed before mid-therapy (AUC = 0.93). Segmented volume was not able to differentiate between pCR and non-pCR at any time-point. The ADC values from 3D-ROI were not significantly different from 2D data (p = 0.06). The best AUC (0.79) for pCR prediction using DWI was median ADC measured before mid-therapy of NACT.

Conclusions

The results of this study should be considered in NACT monitoring planning, especially in MRI protocol designing and time point selection.

Key Points

• Mid-therapy diameter changes are the best predictors of pCR in neoadjuvant chemotherapy.

• Volumetric measures are not strictly superior in therapy monitoring to lesion diameter.

• Size measures perform as a better predictor than ADC values.

Apparent Diffusion Coefficient Quantification in Determining the Histological Diagnosis of Malignant Liver Lesions

Purpose: Diffusion Weighted Imaging is an established diagnostic tool for accurate differential diagnosis between benign and malignant liver lesions. The aim of our study was to evaluate the role of Histogram Analysis of ADC quantification in determining the histological diagnosis as well as the grade of malignant liver tumours. To our knowledge, there is no study evaluating the role of Histogram Analysis of ADC quantification in determining the histological diagnosis as well as the grade of malignant liver tumours.

Methods: During five years, 115 patients with known liver lesions underwent Diffusion Weighted Imaging in 3Tesla MR scanner prior to core needle biopsy. Histogram analyses of ADC in regions of interest were drawn and were correlated with biopsy histological diagnosis and grading.

Results: Histogram analysis of ADC values shows that 5th and 30th percentile parameters have statistically significant potency of discrimination between primary and secondary lesions groups (p values 0.0036 and 0.0125 respectively). Skewness of the histogram can help discriminate between good and poor differentiated (p value 0.17). Discrimination between primary malignancy site in metastases failed for the present number of patients in each subgroup.

Conclusion: Statistical parameters reflecting the shape of the left side of the ADC histogram can be useful for discriminating between primary and secondary lesions and also between well differentiated versus moderate or poor. For the secondary malignancies, they failed to predict the original site of tumour.

Diffusion Weighted Imaging, Diffusion Tensor Imaging, and T2* Mapping of Lumbar Intervertebral Disc in Young Healthy Adults

Background:

Although conventional magnetic resonance imaging (MRI) could provide excellent detection of morphological changes in the diagnosis of lumbar disc degeneration (LDD), it has some difficulties in discriminating minimal changes associated with early LDD before morphological or clinical alterations. Therefore, newer MRI techniques have emerged for investigation of early LDD.

Objectives:

The aim of this study was to use diffusion weighted imaging (DWI), diffusion Tensor Imaging (DTI) and T2* mapping to detect lumbar discs in healthy young adults, to evaluate if they could depict the microstructural changes of early LDD.

Patients and Methods:

Apparent diffusion coefficient (ADC), fractional anisotropy (FA), and T2* images of the lumbar discs were obtained for 40 asymptomatic young subjects (19 males and 21 females; mean age of 24.3 years), using DWI, DTI and T2* mapping with a 1.5-T MRI scanner. ADC, FA, and T2* values were measured to compare five regions of interest (ROI) selected in each nucleus pulposus (NP) of the images.

Results:

The ADC, FA, and T2* values were different (P < 0.05) among different ROIs within the same disc or among corresponding ROIs in different level discs. While the average values of ADC increased regularly with the lowering of the anatomical location (P < 0.05), the average FA and T2* values also associated with the anatomic locations, showed an increase in L4-L5 and L5-S1 discs (P < 0.05).

Conclusion:

ADC, FA, and T2* values may quantitatively reflect the microstructural characteristics of NP, therefore they could be used to detect the minimal changes of early LDD.

Recent Developments in Diffusion Tensor Imaging of Brain

Magnetic resonance imaging (MRI) has come to be known as a unique radiological imaging modality because of its ability to perform tomographic imaging of body without the use of any harmful ionizing radiation. The radiologists use MRI to gain insight into the anatomy of organs, including the brain, while biomedical researchers explore the modality to gain better understanding of the brain structure and function. However, due to limited resolution and contrast, the conventional MRI fails to show the brain microstructure. Diffusion tensor imaging (DTI) harnesses the power of conventional MRI to deduce the diffusion dynamics of water molecules within the tissue and indirectly create a three-dimensional sketch of the brain anatomy. DTI enables visualization of brain tissue microstructure, which is extremely helpful in understanding various neuropathologies and neurodegenerative disorders. In this review, we briefly discuss the background and operating principles of DTI, followed by current trends in DTI applications for biomedical and clinical investigation of various brain diseases and disorders.

Hepatic metastasis complicated by abscess formation

Hepatic abscesses and hepatic metastasis are common diseases. However, hepatic abscesses seldom occur in patients with hepatic metastases. We describe a case of a 67-year-old female patient with abdominal pain in the right upper quadrant. Magnetic resonance imaging revealed several lesions, with the largest lesion displaying features of both hepatic pyogenic abscess and liver metastasis. These features included iso- or hypointense signaling on T1WI and T2WI, hyperintense signaling on diffusion weighted imaging of the thick wall, and mixed hyperintense signal in the center on DWI, as well as dramatic and irregular peripheral enhancement was detected on LAVA dynamic contrast scanning. Aspiration and culture of the largest lesions revealed Klebsiella pneumoniae and a pathologic diagnosis of adenocarcinoma. At this point, the patient admitted a history of colon adenocarcinoma 9 years ago treated with hemicolectomy. Therefore, this patient was considered to have a hepatic pyogenic abscesses complicated by hepatic metastasis. The patient began treatment for the responsible pathogens and underwent chemoembolization of the liver lesions. In special cases, we could attempt to pursue a more detailed search for coexistence of microorganism infection and tumor.

Combined reading of Contrast Enhanced and Diffusion Weighted Magnetic Resonance Imaging by using a simple sum score

OBJECTIVE

To improve specificity of breast MRI by integrating Apparent Diffusion Coefficient (ADC) values with contrast enhanced MRI (CE-MRI) using a simple sum score.

METHODS

Retrospective analysis of a consecutive series of patients referred to breast MRI at 1.5 T for further workup of breast lesions. Reading results of CE-MRI were dichotomized into score 1 (suspicious) or 0 (benign). Lesion's ADC-values (in *10-3 mm2/s) were assigned two different scores: ADC2: likely malignant (score +1, ADC ≤ 1), indeterminate (score 0, ADC >1- ≤ 1.4) and likely benign (score -1, ADC > 1.4) and ADC1: indeterminate (score 0, ADC ≤ 1.4) and likely benign (score -1, ADC > 1.4). Final added CE-MRI and ADC scores >0 were considered suspicious. Reference standard was histology and imaging follow-up of >24 months. Diagnostic parameters were compared using McNemar tests.

RESULTS

A total of 150 lesions (73 malignant) were investigated. Reading of CE-MRI showed a sensitivity of 100 % (73/73) and a specificity of 81.8 % (63/77). Additional integration of ADC scores increased specificity (ADC2/ADC1, P = 0.008/0.001) without causing false negative results.

CONCLUSION

Using a simple sum score, ADC-values can be integrated with CE-MRI of the breast, improving specificity. The best approach is using one threshold to exclude cancer.

KEY POINTS

ADC is used to assign levels of suspicion to breast lesions. ADC values >1.4 *10 (-3)   mm (2) /s are likely benign and effectively rule out malignancy. ADC values below ≤1*10 (-3)   mm (2) /s) are likely malignant but may be false positive. CE-MRI (+1: suspicious, 0: benign) and ADC (0: indeterminate, -1: benign) scores are added. Sum scores >0 should be biopsied.

Diffusion weighted MR imaging and proton MR spectroscopy findings of central neurocytoma with pathological correlation

PURPOSE

Three cases of histopathologically confirmed central neurocytoma (CN) are presented, emphasizing diagnostic imaging issues: conventional magnetic resonance imaging with Proton magnetic resonance spectroscopy (MRS) and diffusion-weighted imaging (DWI) findings of CN.

MATERIALS AND METHODS

Patients age ranged from 17 to 32 years, Imaging include a CT scan and MR examination with DWI and proton MRS on a 1.5-T system. DWI and subsequent apparent diffusion coefficient (ADC) were obtained in all. Single voxel MRS was performed prior to surgery using a point resolved spectroscopy sequence (PRESS) with short 35 ms and long echotime (TE) 144 ms, associated with a two-dimensional chemical Shift Imaging (2D-CSI) with 144 ms TE (one case). Histopathological examination included immunostaining with synaptophysin.

RESULTS

With the long TE, a variable amount of glycine with markedly increased choline, very small to almost complete loss of N-acetylaspartate and creatine, and inverted triplet of alanine-lactate were observed in all three patients. Increased glutamate and glutamine complex (Glx) was also observed in all with short TE. DWI demonstrated variable low ADC which appeared well correlated with the tumor signal intensity and cell density: the most homogeneous and highly dense cellular tumor with increased nucleus to cytoplasm ratio demonstrated the lower ADC. Histological pattern was typical in two cases and demonstrated an oligodendroglioma-like pattern in one case. Positivity for synaptophysin confirmed the neuronal origin in all.

CONCLUSION

The demonstration within an intraventricular tumor of both glycine and alanine on MRS along with high choline, bulky Glx and restricted diffusion appear diagnostic of CN.

Background and Mathematical Analysis of Diffusion MRI Methods

The addition of a pair of magnetic field gradient pulses had initially provided the measurement of spin motion with nuclear magnetic resonance (NMR) techniques. In the adaptation of DW-NMR techniques to magnetic resonance imaging (MRI), the taxonomy of mathematical models is divided in two categories: model matching and spectral methods. In this review, the methods are summarized starting from early diffusion weighted (DW) NMR models followed up with their adaptation to DW MRI. Finally, a newly introduced Fourier analysis based unifying theory, so-called Complete Fourier Direct MRI, is included to explain the mechanisms of existing methods.

Quality Control of Diffusion Weighted Images

Diffusion Tensor Imaging (DTI) has become an important MRI procedure to investigate the integrity of white matter in brain in vivo. DTI is estimated from a series of acquired Diffusion Weighted Imaging (DWI) volumes. DWI data suffers from inherent low SNR, overall long scanning time of multiple directional encoding with correspondingly large risk to encounter several kinds of artifacts. These artifacts can be too severe for a correct and stable estimation of the diffusion tensor. Thus, a quality control (QC) procedure is absolutely necessary for DTI studies. Currently, routine DTI QC procedures are conducted manually by visually checking the DWI data set in a gradient by gradient and slice by slice way. The results often suffer from low consistence across different data sets, lack of agreement of different experts, and difficulty to judge motion artifacts by qualitative inspection. Additionally considerable manpower is needed for this step due to the large number of images to QC, which is common for group comparison and longitudinal studies, especially with increasing number of diffusion gradient directions. We present a framework for automatic DWI QC. We developed a tool called DTIPrep which pipelines the QC steps with a detailed protocoling and reporting facility. And it is fully open source. This framework/tool has been successfully applied to several DTI studies with several hundred DWIs in our lab as well as collaborating labs in Utah and Iowa. In our studies, the tool provides a crucial piece for robust DTI analysis in brain white matter study.