Diffusion-weighted imaging of the liver in patients with chronic liver disease: comparison of monopolar and bipolar diffusion gradients for image quality and lesion detection. AJR Am J Roentgenol. 2015;204:59-68. [PMID: 25539238 DOI: 10.2214/ajr.13.11695]

Noncontrast MRI for Hepatocellular Carcinoma Detection: A Systematic Review and Meta-analysis - A Potential Surveillance Tool?

BACKGROUND AND AIMS

This meta-analysis investigates the diagnostic performance of non-contrast magnetic resonance imaging (MRI) for the detection of hepatocellular carcinoma (HCC).

METHODS

A systematic review was performed to May 2020 for studies which examined the diagnostic performance of non-contrast MRI (multi-sequence or diffusion-weighted imaging (DWI)- alone) for HCC detection in high risk patients. The primary outcome was accuracy for the detection of HCC. Random effects models were used to pool outcomes for sensitivity, specificity, positive likelihood ratio (LR) and negative LR. Subgroup analyses for cirrhosis and size of the lesion were performed.

RESULTS

Twenty-two studies were included involving 1685 patients for per-patient analysis and 2128 lesions for per-lesion analysis. Multi-sequence non-contrast MRI (NC-MRI) using T2+DWI±T1 sequences had a pooled per-patient sensitivity of 86.8% (95%CI:83.9-89.4%), specificity of 90.3% (95%CI:87.3-92.7%), and negative LR of 0.17 (95%CI:0.14-0.20). DWI-only MRI (DW-MRI) had a pooled sensitivity of 79.2% (95%CI:71.8-85.4%), specificity of 96.5% (95%CI:94.3-98.1%) and negative LR of 0.24 (95%CI:1.62-0.34). In patients with cirrhosis, NC-MRI had a pooled per-patient sensitivity of 87.3% (95%CI:82.7-91.0%) and specificity of 81.6% (95%CI:75.3-86.8%), whilst DWI-MRI had a pooled sensitivity of 71.4% (95%CI:60.5-80.8%) and specificity of 97.1% (95%CI:91.9-99.4%). For lesions <2 cm, the pooled per-lesion sensitivity was 77.1% (95%CI:73.8-80.2%). For lesions >2 cm, pooled per-lesion sensitivity was 88.5% (95%CI:85.0-91.5%).

CONCLUSION

Non-contrast MRI has a moderate negative LR and high specificity with acceptable sensitivity for the detection of HCC, even in patients with cirrhosis and with lesions <2 cm. Prospective trials to validate if non-contrast MRI can be used for HCC surveillance is warranted.

HCC screening: assessment of an abbreviated non-contrast MRI protocol

BACKGROUND

Hepatocellular carcinoma (HCC) guidelines recommend ultrasound screening in high-risk patients. However, in some patients, ultrasound image quality is suboptimal due to factors such as hepatic steatosis, cirrhosis, and confounding lesions. Our aim was to investigate an abbreviated non-contrast magnetic resonance imaging (aNC-MRI) protocol as a potential alternative screening method.

METHODS

A retrospective study was performed using consecutive liver MRI studies performed over 3 years, with set exclusion criteria. The unenhanced T2-weighted, T1-weighted Dixon, and diffusion-weighted sequences were extracted from MRI studies with a known diagnosis. Each anonymised aNC-MRI study was read by three radiologists who stratified each study into either return to 6 monthly screening or investigate with a full contrast-enhanced MRI study.

RESULTS

A total of 188 patients were assessed; 28 of them had 42 malignant lesions, classified as Liver Imaging Reporting and Data System 4, 5, or M. On a per-patient basis, aNC-MRI had a negative predictive value (NPV) of 97% (95% confidence interval [CI] 95-98%), not significantly different in patients with steatosis (99%, 95% CI 93-100%) and no steatosis (97%, 95% CI 94-98%). Per-patient sensitivity and specificity were 85% (95% CI 75-91%) and 93% (95% CI 90-95%).

CONCLUSION

Our aNC-MRI HCC screening protocol demonstrated high specificity (93%) and NPV (97%), with a sensitivity (85%) comparable to that of ultrasound and gadoxetic acid contrast-enhanced MRI. This screening method was robust to hepatic steatosis and may be considered an alternative in the case of suboptimal ultrasound image quality.

Prostate diffusion MRI with minimal echo time using eddy current nulled convex optimized diffusion encoding

BACKGROUND

Prostate diffusion-weighted imaging (DWI) using monopolar encoding is sensitive to eddy-current-induced distortion artifacts. Twice-refocused bipolar encoding suppresses eddy current artifacts, but increases echo time (TE), leading to lower signal-to-noise ratio (SNR). Optimization of the diffusion encoding might improve prostate DWI.

PURPOSE

To evaluate eddy current nulled convex optimized diffusion encoding (ENCODE) for prostate DWI with minimal TE.

STUDY TYPE

Prospective cohort study.

POPULATION

A diffusion phantom, an ex vivo prostate specimen, 10 healthy male subjects (27 ± 3 years old), and five prostate cancer patients (62 ± 7 years old).

FIELD STRENGTH/SEQUENCE

3T; single-shot spin-echo echoplanar DWI.

ASSESSMENT

Eddy-current artifacts, TE, SNR, apparent diffusion coefficient (ADC), and image quality scores from three independent readers were compared between monopolar, bipolar, and ENCODE prostate DWI for standard-resolution (1.6 × 1.6 mm² , partial Fourier factor [pF] = 6/8) and higher-resolution protocols (1.6 × 1.6 mm² , pF = off; 1.0 × 1.0 mm² , pF = 6/8).

STATISTICAL TESTING

SNR and ADC differences between techniques were tested with Kruskal-Wallis and Wilcoxon signed-rank tests (P < 0.05 considered significant).

RESULTS

Eddy current suppression with ENCODE was comparable to bipolar encoding (mean coefficient of variation across three diffusion directions of 9.4% and 9%). For a standard-resolution protocol, ENCODE achieved similar TE as monopolar and reduced TE by 14 msec compared to bipolar, resulting in 27% and 29% higher mean SNR in prostate transition zone (TZ) and peripheral zone (PZ) (P < 0.05) compared to bipolar, respectively. For higher-resolution protocols, ENCODE achieved the shortest TE (67 msec), with 17-21% and 58-70% higher mean SNR compared to monopolar (TE = 77 msec) and bipolar (TE = 102 msec) in PZ and TZ (P < 0.05). No significant differences were found in mean TZ (P = 0.91) and PZ ADC (P = 0.94) between the three techniques. ENCODE achieved similar or higher image quality scores than bipolar DWI in patients, with mean intraclass correlation coefficient of 0.77 for overall quality between three independent readers.

DATA CONCLUSION

ENCODE minimizes TE (improves SNR) and reduces eddy-current distortion for prostate DWI compared to monopolar and bipolar encoding.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1526-1539.

Image quality and diagnostic performance of free-breathing diffusion-weighted imaging for hepatocellular carcinoma

AIM

To retrospectively evaluate the diagnostic performance of free-breathing diffusion-weighted imaging (FB-DWI) with modified imaging parameter settings for detecting hepatocellular carcinomas (HCCs).

METHODS

Fifty-one patients at risk for HCC were scanned with both FB-DWI and respiratory-triggered DWI with the navigator echo respiratory-triggering technique (RT-DWI). Qualitatively, the sharpness of the liver contour, the image noise and the chemical shift artifacts on each DWI with b-values of 1000 s/mm² were independently evaluated by three radiologists using 4-point scoring. We compared the image quality scores of each observer between the two DWI methods, using the Wilcoxon signed-rank test. Quantitatively, we compared the signal-to-noise ratios (SNRs) of the liver parenchyma and lesion-to-nonlesion contrast-to-noise ratios (CNRs) after measuring the signal intensity on each DWI with a b-factor of 1000 s/mm². The average SNRs and CNRs between the two DWI methods were compared by the paired t-test. The detectability of HCC on each DWI was also analyzed by three radiologists. The detectability provided by the two DWI methods was compared using McNemar’s test.

RESULTS

For all observers, the averaged image quality scores of FB-DWI were: Sharpness of the liver contour [observer (Obs)-1, 3.08 ± 0.81; Obs-2, 2.98 ± 0.73; Obs-3, 3.54 ± 0.75], those of the distortion (Obs-1, 2.94 ± 0.50; Obs-2, 2.71 ± 0.70; Obs-3, 3.27 ± 0.53), and the chemical shift artifacts (Obs-1, 3.38 ± 0.60; Obs-2, 3.15 ± 1.07; Obs-3, 3.21 ± 0.85). The averaged image quality scores of RT-DWI were: Sharpness of the liver contour (Obs-1, 2.33 ± 0.65; Obs-2, 2.37 ± 0.74; Obs-3, 2.75 ± 0.81), distortion (Obs-1, 2.81 ± 0.56; Obs-2, 2.25 ± 0.74; Obs-3, 2.96 ± 0.71), and the chemical shift artifacts (Obs-1, 2.92 ± 0.59; Obs-2, 2.21 ± 0.85; Obs-3, 2.77 ± 1.08). All image quality scores of FB-DWI were significantly higher than those of RT-DWI (P < 0.05). The average SNR of the normal liver parenchyma by FB-DWI (11.0 ± 4.8) was not significantly different from that shown by RT-DWI (11.0 ± 5.0); nor were the lesion-to-nonlesion CNRs significantly different (FB-DWI, 21.4 ± 17.7; RT-DWI, 20.1 ± 15.1). For all three observers, the detectability of FB-DWI (Obs-1, 43.6%; Obs-2, 53.6%; and Obs-3, 45.0%) was significantly higher than that of RT-DWI (Obs-1, 29.1%; Obs-2, 43.6%; and Obs-3, 34.5%) (P < 0.05).

CONCLUSION

FB-DWI showed better image quality and higher detectability of HCC compared to RT-DWI, without significantly reducing the SNRs of the liver parenchyma and lesion-to-nonlesion CNRs.

Diffusion-Weighted Imaging with Two Different b-Values in Detection of Solid Focal Liver Lesions

One hundred and eighty-two consecutive patients with suspected liver disease were recruited to receive diffusion-weighted imaging (DWI) with two different b-values, in comparison with T2-weighted imaging (T2WI). The detection rate of three MR sequences in solid focal liver lesions (FLLs) and subgroup analyses were performed. Our prospective study found that DWI600 was equivalent to DWI100 and T2WI for the detection of solid FLLs overall but was significantly more accurate in the detection of malignant solid FLLs and lesions larger than 10 mm.

Evaluation of Hepatic Tumors Using Intravoxel Incoherent Motion Diffusion-Weighted MRI

Background

This study aimed to evaluate the diagnostic value of the D value, D* value, and f magnitude for identifying benign and malignant hepatic tumors using intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI).

Material/Methods

Data of 89 cases (123 lesions) with hepatic tumor confirmed by surgical pathology and postoperative follow-up were retrospectively collected. Among these cases, 40 cases were benign hepatic tumors (57 lesions) and 49 cases were malignant hepatic tumors (66 lesions). All subjects underwent conventional MRI with T₁WI, T₂WI, multi-b-value DWI, and dynamic enhanced LAVA scan. Diffusion-weighted images with 11 b values (0, 10, 20, 30, 50, 80, 100, 200, 400, 800, and 1000 s/mm²) were obtained to calculate true molecular diffusion (D), perfusion-related diffusion coefficient (D*), and perfusion fraction (f). The diagnostic performance in differentiating between malignant and benign hepatic lesions was analyzed.

Results

Malignant lesions had a significantly lower D value ([1.04±0.34]×10⁻³ mm²/s) and D* value ([16.5±7.7]×10⁻³ mm²/s) compared to benign lesions (D value: [1.70±0.55]×10⁻³ mm²/s, P<0.01; D* value: [21.7±9.9]×10⁻³ mm²/s, P<0.01). There was no statistically significant difference in f values between malignant (23.3±9.5) and benign lesions (33.5±14.9, P=0.13). In addition, D exhibited a better diagnostic performance than D* in terms of the area under the curve, sensitivity, and specificity when identifying malignancies from benign lesions.

Conclusions

D and D* are significant parameters for diagnosing hepatic tumors. Moreover, the D value is a more reliable parameter in distinguishing benign and malignant hepatic tumors.

Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice

Technologic advances enable performance of diffusion-weighted imaging (DWI) at ultrahigh b-values, where standard monoexponential model analysis may not apply. Rather, non-Gaussian water diffusion properties emerge, which in cellular tissues are, in part, influenced by the intracellular environment that is not well evaluated by conventional DWI. The novel technique, diffusion kurtosis imaging (DKI), enables characterization of non-Gaussian water diffusion behavior. More advanced mathematical curve fitting of the signal intensity decay curve using the DKI model provides an additional parameter Kapp that presumably reflects heterogeneity and irregularity of cellular microstructure, as well as the amount of interfaces within cellular tissues. Although largely applied for neural applications over the past decade, a small number of studies have recently explored DKI outside the brain. The most investigated organ is the prostate, with preliminary studies suggesting improved tumor detection and grading using DKI. Although still largely in the research phase, DKI is being explored in wider clinical settings. When assessing extracranial applications of DKI, careful attention to details with which body radiologists may currently be unfamiliar is important to ensure reliable results. Accordingly, a robust understanding of DKI is necessary for radiologists to better understand the meaning of DKI-derived metrics in the context of different tumors and how these metrics vary between tumor types and in response to treatment. In this review, we outline DKI principles, propose biostructural basis for observations, provide a comparison with standard monoexponential fitting and the apparent diffusion coefficient, report on extracranial clinical investigations to date, and recommend technical considerations for implementation in body imaging.