Biexponential apparent diffusion coefficients in prostate cancer

Purpose

The purpose of this study was to investigate the need for biexponential signal decay modeling for prostate cancer diffusion signal decays with b-factor over an extended b-factor range.

Materials and Methods

Ten healthy volunteers and 12 patients with a bulky prostate cancer underwent line scan diffusion-weighted MR imaging in which b-factors from 0 to 3000 s/mm² in 16 steps were sampled. The acquired signal decay curves were fit with both monoexponential and biexponential signal decay functions and a statistical comparison between the two fits was performed.

Results

The biexponential model provided a statistically better fit over the monoexponential model on the peripheral zone (PZ), transitional zone (TZ) and prostate cancer. The fast and slow apparent diffusion coefficients (ADCs) in the PZ, TZ and cancer were 2.9±0.2, 0.7±0.2×10⁻³ mm²/ms (PZ); 2.9±0.4, 0.7±0.2×10⁻³ mm²/ms (TZ); and 1.7±0.4, 0.3±0.1×10⁻³ mm²/ms (cancer), respectively. The apparent fractions of the fast diffusion component in the PZ, TZ and cancer were 70±10%, 60±10% and 50±10%, respectively. The fast and slow ADCs of cancer were significantly lower than those of TZ and PZ, and the apparent fraction of the fast diffusion component was significantly smaller in cancer than in PZ.

Conclusions

Biexponential diffusion decay functions are required for prostate cancer diffusion signal decay curves when sampled over an extended b-factor range, providing additional, unique tissue characterization parameters for prostate cancer.     

Comparison of different mathematical models of diffusion-weighted prostate MR imaging

Purpose

To evaluate which mathematical model (monoexponential, biexponential, statistical, kurtosis) fits best to the diffusion-weighted signal in prostate magnetic resonance imaging (MRI).

Materials and Methods

24 prostate 3-T MRI examinations of young volunteers (YV, n= 8), patients with biopsy proven prostate cancer (PC, n= 8) and an aged matched control group (AC, n= 8) were included. Diffusion-weighted imaging was performed using 11 b-values ranging from 0 to 800 s/mm².

Results

Monoexponential apparent diffusion coefficient (ADC) values were significantly (P<.001) lower in the peripheral (PZ) zone (1.18±0.16 mm²/s) and the central (CZ) zone (0.73±0.13 mm²/s) of YV compared to AC (PZ 1.92±0.17 mm²/s; CZ 1.35±0.21 mm²/s). In PC ADC_mono values (0.61±0.06 mm²/s) were significantly (P<.001) lower than in the peripheral of central zone of AC. Using the statistical analysis (Akaike information criteria) in YV most pixels were best described by the biexponential model (82%), the statistical model, respectively kurtosis (93%) each compared to the monoexponential model. In PC the majority of pixels was best described by the monoexponential model (57%) compared to the biexponential model.

Conclusion

Although a more complex model might provide a better fitting when multiple b-values are used, the monoexponential analyses for ADC calculation in prostate MRI is sufficient to discriminate prostate cancer from normal tissue using b-values ranging from 0 to 800 s/mm².     

Differential detection of metastatic and inflammatory lymph nodes using intravoxel incoherent motion diffusion-weighted imaging

PurposeThis study sought to monitor the dynamic process of lymph node (LN) metastasis with intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI), and to investigate the impact of disease course on the detection of metastatic LNs by IVIM-DWI.MethodsTwenty female New Zealand rabbits with 2.5–3.0 kg body weight were studied. VX2 cells and egg yolk emulsion were randomly inoculated into one thigh to induce metastatic and inflammatory popliteal LNs, respectively. Eight rabbits underwent IVIM-DWI (14 b values, 0–2000 s/mm²) 2 h prior to, and 14, 21, and 28 days after inoculation (D0, D14, D21, D28). The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were measured and compared between the metastatic and the inflammatory groups at each time point. Three rabbits randomly chosen from the remaining twelve rabbits were sacrificed at each time point to perform hematoxylin and eosin staining and histologic evaluation.ResultsThe patterns of dynamic change of D*, ADC, and D were different between the metastatic and the inflammatory LNs. The metastatic group had a lower D* value at D14 (p = .003), and greater ADC and D values at both D21 (p = .001, p = .001) and D28 (p = .021, p = .001), compared to the inflammatory group. The f value of the metastatic group was greater than that of the inflammatory only at D28 (p = .001).ConclusionsIVIM-DWI can reflect the dynamic process of LN metastasis, and disease course has a significant influence on the ability of IVIM-DWI to detect metastatic nodes.     

Using intravoxel incoherent motion (IVIM) MR imaging to predict lipiodol uptake in patients with hepatocellular carcinoma following transcatheter arterial chemoembolization: A preliminary result

Purpose

To assess the usefulness of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) for predicting lipiodol uptake in patients with hepatocellular carcinoma (HCC) after transcatheter arterial chemoembolization (TACE).

Materials and methods

The institutional review board approved this study. 44 HCC patients underwent IVIM-DWI and Gd-EOB-DTPA-enhanced MRI prior to TACE. Using post-TACE CT as a reference standard, each HCC was classified into either lipiodol good uptake (LGU) or poor uptake (LPU) group. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), perfusion coefficient (D*), and perfusion fraction (f) in HCC were calculated. Arterial enhancement ratio (AER) and IVIM parameters were compared between those two groups using the Mann-Whitney U test.

Results

Of the 51 HCCs, 37 (72.5%) were LGU group and 14 (27.5%) were LPU group. AER of HCC was significantly higher in LGU than LPU (0.99 ± 0.54 and 0.67 ± 0.45; P = .034). ADC, D, and f values were not significantly different (P = .073, .059, and .196, respectively) between these two groups. D* was significantly elevated in LGU than LPU (48.10 ± 15.33 and 26.75 ± 9.55; P = .001).

Conclusion

Both AER derived from contrast enhanced MRI and D* values derived from IVIM-DWI for HCC were significantly higher in LGU than in LPU. These parameters would be helpful for predicting the lipiodol uptake.     

Diffusion-weighted MRI in prostate cancer -- comparison between single-shot fast spin echo and echo planar imaging sequences

Diffusion-weighted (DW) MRI at 1.5 T was carried out in two groups of patients. MRI data were correlated with the biopsy and histopathology (where available). The performance of two sequences -- a single-shot FSE (14 patients) and a single-shot EPI (15 patients) -- was compared. Average ADC values from the normal peripheral zone (PZ), central gland (CG) and the tumour [prostate carcinoma (PCa)] were calculated from b values of 0 and 600. Tukey-Kramer test was used for statistical analysis. EPI produced higher values of ADC (10(-3) mm(2)/s) than FSE sequence: 1.992+/-0.208 vs. 1.573+/-0.270 in PZ (P<.001), 1.518+/-0.126 vs. 1.373+/-0.179 in CG and 1.214+/-0.254 vs. 0.993+/-0.158 in PCa (P<.01). In conclusion, both EPI and FSE sequences showed differences in ADC between normal PZ, CG and PCa; however, EPI produced significantly higher ADC values than FSE.     

MRI quantification of diffusion and perfusion in bone marrow by intravoxel incoherent motion (IVIM) and non-negative least square (NNLS) analysis

Object

To assess the feasibility of measuring diffusion and perfusion fraction in vertebral bone marrow using the intravoxel incoherent motion (IVIM) approach and to compare two fitting methods, i.e., the non-negative least squares (NNLS) algorithm and the more commonly used Levenberg–Marquardt (LM) non-linear least squares algorithm, for the analysis of IVIM data.

Materials and Methods

MRI experiments were performed on fifteen healthy volunteers, with a diffusion-weighted echo-planar imaging (EPI) sequence at five different b-values (0, 50, 100, 200, 600 s/mm²), in combination with an STIR module to suppress the lipid signal. Diffusion signal decays in the first lumbar vertebra (L1) were fitted to a bi-exponential function using the LM algorithm and further analyzed with the NNLS algorithm to calculate the values of the apparent diffusion coefficient (ADC), pseudo-diffusion coefficient (D*) and perfusion fraction.

Results

The NNLS analysis revealed two diffusion components only in seven out of fifteen volunteers, with ADC = 0.60 ± 0.09 (10^− 3 mm²/s), D* = 28 ± 9 (10^− 3 mm²/s) and perfusion fraction = 14% ± 6%. The values obtained by the LM bi-exponential fit were: ADC = 0.45 ± 0.27 (10^− 3 mm²/s), D* = 63 ± 145 (10^− 3 mm²/s) and perfusion fraction = 27% ± 17%. Furthermore, the LM algorithm yielded values of perfusion fraction in cases where the decay was not bi-exponential, as assessed by NNLS analysis.

Conclusion

The IVIM approach allows for measuring diffusion and perfusion fraction in vertebral bone marrow; its reliability can be improved by using the NNLS, which identifies the diffusion decays that display a bi-exponential behavior.     

Non-Gaussian water diffusion kurtosis imaging of prostate cancer

Purpose

To evaluate the non-Gaussian water diffusion properties of prostate cancer (PCa) and determine the diagnostic performance of diffusion kurtosis (DK) imaging for distinguishing PCa from benign tissues within the peripheral zone (PZ), and assessing tumor lesions with different Gleason scores.

Materials and Methods

Nineteen patients who underwent diffusion weighted (DW) magnetic resonance imaging using multiple b-values and were pathologically confirmed with PCa were enrolled in this study. Apparent diffusion coefficient (ADC) was derived using a monoexponential model, while diffusion coefficient (D) and kurtosis (K) were determined using a DK model. Differences between the ADC, D and K values of benign PZ and PCa, as well as those of tumor lesions with Gleason scores of 6, 7 and ≥ 8 were assessed. Correlations between parameters D and K in PCa were analyzed using Pearson’s correlation coefficient. ADC, D and K values were correlated with Gleason scores of 6, 7 and ≥ 8, respectively.

Results

ADC and D values were significantly (p < 0.001) lower in PCa (0.79 ± 0.14 μm²/ms and 1.56 ± 0.23 μm²/ms, respectively) compared to benign PZ (1.23 ± 0.19 μm²/ms and 2.54 ± 0.24 μm²/ms, respectively). K values were significantly (p < 0.001) greater in PCa (0.96 ± 0.20) compared to benign PZ (0.59 ± 0.08). D and K showed fewer overlapping values between benign PZ and PCa compared to ADC. There was a strong negative correlation between D and K values in PCa (Pearson correlation coefficient r = − 0.729; p < 0.001). ADC and K values differed significantly in tumor lesions with Gleason scores of 6, 7 and ≥ 8 (p < 0.001 and p = 0.001, respectively), although no significant difference was detected for D values (p = 0.325). Significant correlations were found between the ADC value and Gleason score (r = − 0.828; p < 0.001), as well as the K value and Gleason score (r = 0.729; p < 0.001).

Conclusion

DK model may add value in PCa detection and diagnosis. K potentially offers a new metric for assessment of PCa.     

Comparison of accuracy of intravoxel incoherent motion and apparent diffusion coefficient techniques for predicting malignancy of head and neck tumors using half-Fourier single-shot turbo spin-echo diffusion-weighted imaging

Purpose

To evaluate the use of the intravoxel incoherent motion (IVIM) technique in half-Fourier single-shot turbo spin-echo (HASTE) diffusion-weighted imaging (DWI), and to compare its accuracy to that of apparent diffusion coefficient (ADC) to predict malignancy in head and neck tumors.

Patients and methods

HASTE DW images of 33 patients with head and neck tumors (10 benign and 23 malignant) were evaluated. Using the IVIM technique, parameters (D, true diffusion coefficient; f, perfusion fraction; D*, pseudodiffusion coefficient) were calculated for each tumor. ADC values were measured over a range of b values from 0 to 1000 s/mm². IVIM parameters and ADC values in benign and malignant tumors were compared using Student's t test, receiver operating characteristics (ROC) analysis, and multivariate logistic regression modeling.

Results

Mean ADC and D values of malignant tumors were significantly lower than those of benign tumors (P < 0.05). Mean D* values of malignant tumors were significantly higher than those of benign tumors (P < 0.05). There was no significant difference in mean f values between malignant and benign tumors (P > 0.05). The technique of combining D and D* was the best for predicting malignancy; accuracy for this model was higher than that for ADC.

Conclusions

The IVIM technique may be applied in HASTE DWI as a diagnostic tool to predict malignancy in head and neck masses. The use of D and D* in combination increases the diagnostic accuracy in comparison with ADC.     

Toward an optimal distribution of b values for intravoxel incoherent motion imaging

The intravoxel incoherent motion (IVIM) theory provides a framework for the separation of perfusion and diffusion effects in diffusion-weighted imaging (DWI). To measure the three free IVIM parameters, DWIs with several diffusion weightings b must be acquired. To date, the used b value distributions are chosen heuristically and vary greatly among researchers. In this work, optimal b value distributions for the three parameter fit are determined using Monte-Carlo simulations for the measurement of a low, medium and high IVIM perfusion regime. The first 16 b values of a b value distribution, which was optimized to be appropriate for all three regimes, are {0, 40, 1000, 240, 10, 750, 90, 390, 170, 10, 620, 210, 100, 0, 530 and 970} in units of seconds per square meter. This distribution performed well for all organs and outperformed a distribution frequently used in the literature. In case of limited acquisition time, the b values should be chosen in the given order, but at least 10 b values should be used for current clinical settings. The overall parameter estimation quality depends strongly and nonlinearly on the signal-to-noise ratio (SNR): it is essential that the SNR is considerably higher than a critical SNR. This critical SNR is about 8 for medium and high IVIM perfusion and 50 for the low IVIM perfusion regime. Initial in vivo IVIM measurements were performed in the abdomen and were in keeping with the numerically simulated results.     

Intravoxel incoherent motion imaging of the kidney: alterations in diffusion and perfusion in patients with renal dysfunction

Purpose

To investigate the relationship between estimated glomerular filtration rate (eGFR) and parameters calculated using intravoxel incoherent motion (IVIM) imaging of the kidneys.

Materials and Methods

We studied 365 patients, divided into 4 groups based on eGFR levels (mL/min/1.73 m²): group 1, eGFR ≥ 80(n = 80); group 2, eGFR 60–80 (n = 156); group 3, eGFR 30–60 (n = 114); and group 4 ,eGFR < 30 (n = 15). IVIM imaging was used to acquire diffusion-weighted images at 12 b values. The diffusion coefficient of pure molecular diffusion (D), the diffusion coefficient of microcirculation or perfusion (D*), and perfusion fraction (f) were compared among the groups using group 1 as control.

Results

In the renal cortex, D* values were significantly lower in groups 2, 3, and 4 than in group 1. The D value of renal cortex was significantly low in only group 3. In the renal medulla, the D* and D values were significantly lower only in groups 2 and 3, respectively.

Conclusion

As renal dysfunction progresses, renal perfusion might be reduced earlier and affected more than molecular diffusion in the renal cortex. These changes are effectively detected by IVIM MR imaging.     

Intra-voxel incoherent motion MRI in rodent model of diethylnitrosamine-induced liver fibrosis

Rationale and Objectives

To compare the apparent diffusion coefficient (ADC) and the perfusion fraction measured by intra-voxel incoherent motion (IVIM) Magnetic Resonance Imaging (MRI) with liver fibrosis degrees in a rodent model.

Materials and Methods

All experiments received approval from our institutional animal care and use committee. Liver fibrosis was induced in 13 rats by oral gavage with diethylnitrosamine; 4 untreated rats with normal livers were used as controls. Diffusion Weighted MRI was performed and 8 gradient factors (0, 50, 100, 150, 200, 300, 400 and 500 s/mm²) were acquired. The values of ADC, true diffusion coefficient D and perfusion fraction f were measured based on Li Bihan’s method. The percentage of liver fibrosis was assessed via quantitative analysis of Masson trichrome staining using an average of 30 fields per section. The MRI measurements were compared to the histological fibrotic grade to evaluate the correlation between them.

Results

ADC contained the contribution of diffusion and perfusion. The ADC and f values decreased significantly with the increasing fibrosis level (correlation coefficient: ADC: ρ = − 0.781, p < 0.001; f: ρ = − 0.720, p = 0.001); but D was poorly correlated with fibrosis level (ρ = − 0.502, p = 0.040).

Conclusion

The hepatic ADC and the perfusion fraction f were significantly correlated with the liver fibrosis level; however, D was not. This might suggest that hepatic perfusion is altered during the progression of hepatic fibrosis.     

Feasibility of diffusional kurtosis tensor imaging in prostate MRI for the assessment of prostate cancer: Preliminary results

Purpose

To assess the feasibility of full diffusional kurtosis tensor imaging (DKI) in prostate MRI in clinical routine. Histopathological correlation was achieved by targeted biopsy.

Materials and Methods

Thirty-one men were prospectively included in the study. Twenty-one were referred to our hospital with increased prostate specific antigen (PSA) values (> 4 ng/ml) and suspicion of prostate cancer. The other 10 men were volunteers without any history of prostate disease. DKI applying diffusion gradients in 20 different spatial directions with four b-values (0, 300, 600, 1000 s/mm²) was performed additionally to standard functional prostate MRI. Region of interest (ROI)-based measurements were performed in all histopathologically verified lesions of every patient, as well as in the peripheral zone, and the central gland of each volunteer.

Results

DKI showed a substantially better fit to the diffusion-weighted signal than the monoexponential apparent diffusion coefficient (ADC). Altogether, 29 lesions were biopsied in 14 different patients with the following results: Gleason score 3 + 3 = 6 (n = 1), 3 + 4 = 7 (n = 7), 4 + 3 = 7 (n = 6), 4 + 4 = 8 (n = 1), and 4 + 5 = 9 (n = 2), and prostatitis (n = 12). Values of axial (K_ax) and mean kurtosis (K_mean) were significantly different in the tumor (K_ax 1.78 ± 0.39, K_mean 1.84 ± 0.43) compared with the normal peripheral zone (K_ax 1.09 ± 0.12, K_mean 1.16 ± 0.13; p < 0.001) or the central gland (K_ax 1.40 ± 0.12, K_mean 1.44 ± 0.17; p = 0.01 respectively). There was a minor correlation between axial kurtosis (r = 0.19) and the Gleason score.

Conclusion

Full DKI is feasible to utilize in a routine clinical setting. Although there is some overlap some DKI parameters can significantly distinguish prostate cancer from the central gland or the normal peripheral zone. Nevertheless, the additional value of DKI compared with conventional monoexponential ADC calculation remains questionable and requires further research.     

Quantifying hepatic fibrosis using a biexponential model of diffusion weighted imaging in ex vivo liver specimens

The purpose of this study was to evaluate the non-Gaussian behavior of diffusion related signal decay of the ex vivo murine liver tissues from a dietary model of hepatic fibrosis. To this end, a biexponential formalism was used to model high b-value diffusion imaging (up to 3500 s/mm²), the findings of which were correlated with liver histopathology and compared to a simple monoexponential model. The presence of a major, fast diffusing component and a minor, slow diffusing component was demonstrated. With increasing hepatic fibrosis, the fractional contribution of the fast diffusing component decreased, as did the diffusion coefficient of the fast diffusing component. Strong correlation between the degrees of liver fibrosis and a two-predictor regression model incorporating parameters of the biexponential model was found. Using Akaike's Information Criterion analyses, the biexponential model resulted in an improved fit of the high b-value diffusion data when compared to the monoexponential model.     

Combined prostate diffusion tensor imaging and dynamic contrast enhanced MRI at 3T — quantitative correlation with biopsy

The purpose of this work was to compare diagnostic accuracy of Diffusion Tensor Imaging (DTI), dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) and their combination in diagnosing prostate cancer. Twenty-five patients with clinical suspicion of prostate cancer underwent MRI, prior to transrectal ultrasound-guided biopsies. MRI data were correlated to biopsy results. Logistic regression models were constructed for the DTI parameters, DCE MRI parameters, and their combination. The areas under the receiver operator characteristic curves (AUC) were compared between the models. The nonparametric Wilcoxon signed rank test was used for statistical analysis. The sensitivity and specificity values were respectively 81% (74–87%) and 85% (79–90%) for DTI and 63% (55–70%) and 90% (85–94%) for DCE. The combination “DTI or DCE MRI” had 100% (97–100%) sensitivity and 77% (69–83%) specificity, while “DTI and DCE MRI” had 44% (37–52%) sensitivity and 98% (94–100%) specificity. The AUC for DTI+DCE parameters was significantly higher than that for either DTI (0.96 vs. 0.92, P=.0143) or DCE MRI parameters (0.96 vs. 0.87, P=.00187) alone. In conclusion, the combination of DTI and DCE MRI has significantly better accuracy in prostate cancer diagnosis than either technique alone.     

Effect of gadolinium injection on diffusion-weighted imaging with background body signal suppression (DWIBS) imaging of breast lesions

Objectives

Diffusion-weighted imaging with background body signal suppression (DWIBS) provides both qualitative and quantitative imaging of breast lesions and are usually performed before contrast material injection (CMI). This study aims to assess whether the administration of gadolinium significantly affects DWIBS imaging.

Methods

200 patients were prospectively evaluated by MRI with STIR, TSE-T2, pre-CMI DWIBS, contrast enhanced THRIVE-T1 and post-CMI DWIBS sequences. Pre and post-CMI DWIBS were analyzed searching for the presence of breast lesions and calculating the ADC value. ADC values of ≤ 1.44 × 10^- 3 mm²/s were considered suspicious for malignancy. This analysis was then compared with the histological findings. Sensitivity, specificity, diagnostic accuracy (DA), positive predictive value (PPV) and negative (NPV) were calculated for both sequences and represented by ROC analysis. Pre and post-CMI ADC values were compared by using the paired t test.

Results

In 150/200 (59%) patients, pre and post-CMI DWIBS indicated the presence of breast lesions, 53 (35%) with ADC values of > 1.44 × 10^- 3 mm²/s and 97 (65%) with ADC ≤ 1.44 × 10^- 3 mm²/s. Pre-CMI and post-DWIBS sequences obtained the same sensitivity, specificity, DA, PPV and NPV values of 97%, 83%, 89%, 79% and 98%. The mean ADC value of benign lesions was 1.831 ± 0.18 × 10^- 3 mm²/s before and 1.828 ± 0.18 × 10^- 3 mm²/s after CMI. The mean ADC value of the malignant lesions was 1.146 ± 0.16 × 10^- 3 mm²/s before and 1.144 ± 0.16 × 10^- 3 mm²/s after CMI. No significant difference was found between pre and post CMI ADC values (p > 0.05).

Conclusion

DWIBS imaging is not influenced by CMI. Breast MR protocol could be modified by placing DWIBS after dynamic contrast enhanced sequences in order to maximize patient cooperation.     

Intravoxel incoherent motion diffusion-weighted imaging in head and neck squamous cell carcinoma: Assessment of perfusion-related parameters compared to dynamic contrast-enhanced MRI

Purpose

To investigate the correlation between perfusion-related parameters obtained with intravoxel incoherent motion (IVIM) and classical perfusion parameters obtained with dynamic contrast-enhanced (DCE) magnetic resonance imaging in patients with head and neck squamous cell carcinoma (HNSCC), and to compare direct and asymptotic fitting, the pixel-by-pixel approach, and a region of interest (ROI)-based approach respectively for IVIM parameter calculation.

Materials and methods

Seventeen patients with HNSCC were included in this retrospective study. All magnetic resonance (MR) scanning was performed using a 3 T MR unit. Acquisition of IVIM was performed using single-shot spin-echo echo-planar imaging with three orthogonal gradients with 12 b-values (0, 10, 20, 30, 50, 80, 100, 200, 400, 800, 1000, and 2000). Perfusion-related parameters of perfusion fraction ‘f’ and the pseudo-diffusion coefficient ‘D*’ were calculated from IVIM data by using least square fitting with the two fitting methods of direct and asymptotic fitting, respectively. DCE perfusion was performed in a total of 64 dynamic phases with a 3.2-s phase interval. The two-compartment exchange model was used for the quantification of tumor blood volume (TBV) and tumor blood flow (TBF). Each tumor was delineated with a polygonal ROI for the calculation of f, f ? D* performed using both the pixel-by-pixel approach and the ROI-based approach. In the pixel-by-pixel approach, after fitting each pixel to obtain f, f ? D* maps, the mean value in the delineated ROI on these maps was calculated. In the ROI-based approach, the mean value of signal intensity was calculated within the ROI for each b-value in IVIM images, and then fitting was performed using these values. Correlations between f in a total of four combinations (direct or asymptotic fitting and pixel-by-pixel or ROI-based approach) and TBV were respectively analyzed using Pearson's correlation coefficients. Correlations between f ? D* and TBF were also similarly analyzed.

Results

In all combinations of f and TBV, f ? D* and TBF, there was a significant correlation. In the comparison of f and TBV, a moderate correlation was observed only between f obtained by direct fitting with the pixel-by-pixel approach, whereas a good correlation was observed in the comparisons using the other three combinations. In the comparison of f ? D* and TBF, a good correlation was observed only with f ? D* obtained by asymptotic fitting with the ROI-based approach. In contrast, moderate correlations were observed in the comparisons using the other three combinations.

Conclusion

IVIM was found to be feasible for the analysis of perfusion-related parameters in patients with HNSCC. Especially, the combination of asymptotic fitting with the ROI-based approach was better correlated with DCE perfusion.     

Assessment of early response to concurrent chemoradiotherapy in cervical cancer: value of diffusion-weighted and dynamic contrast-enhanced MR imaging

Purpose

To investigate diffusion-weighted (DWI) and dynamic contrast-enhanced MR imaging (DCE-MRI) as early response predictors in cervical cancer patients who received concurrent chemoradiotherapy (CCRT).

Materials and methods

Sixteen patients with cervical cancer underwent DWI and DCE-MRI before CCRT (preTx), at 1 week (postT1) and 4 weeks (postT2) after initiating treatment, and 1 month after the end of treatment (postT3). At each point, apparent diffusion coefficient (ADC) and DCE-MRI parameters were measured in tumors and gluteus muscles (GM). Tumor response was correlated with imaging parameters or changes in imaging parameters at each point.

Results

At each point, ADC, K^trans and V_e in tumors showed significant changes (P < 0.05), as compared with those of GM (P > 0.05). PostT1 tumor ADCs showed a significant correlation with tumor size response at postT2 (P = 0.041), and changes in tumor ADCs at postT1 had a significant correlation with tumor size (P = 0.04) and volume response (P = 0.003) at postT2. In tumors, preTx K^trans and V_e showed significant correlations with tumor size at postT3 (P = 0.011) and tumor size response at postT2 (P = 0.019), respectively.

Conclusion

DWI and DCE-MRI, as early biomarkers, have the potential to evaluate therapeutic responses to CCRT in cervical cancers.     

Evaluation of the role of magnetization transfer imaging in prostate: a preliminary study

Results of the preliminary study on the evaluation of the role of magnetization transfer imaging (MTI) of prostate in men who had raised prostate-specific antigen (PSA) (>4 ng/ml) or abnormal digital rectal examination (DRE) are reported. MT ratio (MTR) was calculated for 20 patients from the hyper- (normal) and hypo-intense regions (area suspicious of malignancy as seen on T2-weighted MRI) of the peripheral zone (PZ) and the central gland (CG) at 1.5 T. In addition, MTR was calculated for three healthy controls. Mean MTR was also calculated for the whole of the PZ (including hyper- and hypo-intense area) in all patients. Out of 20 patients, biopsy revealed malignancy in 12 patients. Mean MTR value (8.29+/-3.49) for the whole of the PZ of patients who were positive for malignancy on biopsy was statically higher than that observed for patients who were negative for malignancy (6.18+/-3.15). The mean MTR for the whole of the PZ of controls was 6.18+/-1.63 and is similar to that of patients who were negative for malignancy. Furthermore, for patients who showed hyper- (normal portion) and hypo-intense (region suspicious of malignancy) regions of the PZ, the MTR was statistically significantly different. These preliminary results reveal the potential role of MT imaging in the evaluation of prostate cancer.     

Emerging spectroscopic techniques for prostate cancer diagnosis

ABSTRACT

Over the past several decades, large efforts have been made to diagnose and overcome prostate cancer. Among all screening methods, the measurement of prostate-specific antigen (PSA) threshold has been stood out and contributed to diagnose prostate cancer (PCa) in a large number of men. Nevertheless, the early detection of prostate carcinoma and its focal imaging is remaining crucial to diminish the elevated number of PCa-related deaths. Because of the multifocal behavior of PCa development, a whole gland ablation has been practiced during previous years. Furthermore, there is an evidence of the likelihood of high-risk PCa that proves once again the importance of early diagnosis and accurate staging of the disease. So far, numerous advanced spectroscopic methods with different approaches have been reported as the alternative tools to conventional techniques of PCa diagnosis and imaging. In this review, we introduce innovative emerging techniques utilizing spectroscopic methods such as photoluminescence, surface-enhanced Raman spectroscopy, and surface plasmon resonance to measure the ultralow level of PSA. In addition, we review novel and alternative approaches of diagnosis such as imaging methods through photoluminescence, magnetic resonance imaging, and positron emission tomography.     

Correction strategy for diffusion-weighted images corrupted with motion: application to the DTI evaluation of infants' white matter

Objective

Diffusion imaging techniques such as DTI and HARDI are difficult to implement in infants because of their sensitivity to subject motion. A short acquisition time is generally preferred, at the expense of spatial resolution and signal-to-noise ratio. Before estimating the local diffusion model, most pre-processing techniques only register diffusion-weighted volumes, without correcting for intra-slice artifacts due to motion or technical problems. Here, we propose a fully automated strategy, which takes advantage of a high orientation number and is based on spherical-harmonics decomposition of the diffusion signal.

Material and methods

The correction strategy is based on two successive steps: 1) automated detection and resampling of corrupted slices; 2) correction for eddy current distortions and realignment of misregistered volumes. It was tested on DTI data from adults and non-sedated healthy infants.

Results

The methodology was validated through simulated motions applied to an uncorrupted dataset and through comparisons with an unmoved reference. Second, we showed that the correction applied to an infant group enabled to improve DTI maps and to increase the reliability of DTI quantification in the immature cortico-spinal tract.

Conclusion

This automated strategy performed reliably on DTI datasets and can be applied to spherical single- and multiple-shell diffusion imaging.