Pharmacokinetic Approach for Dynamic Breast MRI to Indicate Signal Intensity Time Curves of Benign and Malignant Lesions by Using the Tumor Flow Residence Time:

Numerical evaluation of high-energy, laser-Compton x-ray sources for contrast enhancement and dose reduction in clinical imaging via gadolinium-based K-edge subtraction

Conventional x-ray sources for medical imaging utilize bremsstrahlung radiation. These sources generate large bandwidth (BW) x-ray spectra with large fractions of photons that impart a dose, but do not contribute to image production. X-ray sources based on laser-Compton scattering can have inherently small energy BWs and can be tuned to low dose-imparting energies, allowing them to take advantage of atomic K-edge contrast enhancement. This paper investigates the use of gadolinium-based K-edge subtraction imaging in the context of mammography using a laser-Compton source through simulations quantifying contrast and dose in such imaging systems as a function of laser-Compton source parameters. Our simulations indicate that a K-edge subtraction image generated with a 0.5% BW (FWHM) laser-Compton x-ray source can obtain an equal contrast to a bremsstrahlung image with only 3% of the dose.

Classification of breast mass lesions on dynamic contrast-enhanced magnetic resonance imaging by a computer-assisted diagnosis system based on quantitative analysis

The aim of the current study was to develop a semi-automatic and quantitative method for the analysis of a time-intensity curve (TIC) from breast dynamic contrast-enhanced magnetic resonance imaging. The performance of the proposed method, based on the level set segmentation algorithm, was evaluated by comparison with the traditional method. In the traditional method, the lesion area is delineated manually and the corresponding mean TIC is classified subjectively as one of three washout patterns. In addition, only one quantitative parameter, the maximum slope of increase (MSI), is calculated. In the proposed method, the lesion region was determined semi-automatically and the corresponding mean TIC was categorized quantitatively. In addition to MSI, a number of quantitative parameters were derived from the mean TIC and lesion area, including signal intensity slope (SI_slope), initial percentage of enhancement (E_initial), percentage of peak enhancement (E_peak), early signal enhancement ratio (ESER) and second enhancement percentage (SEP). Wilcoxon signed-rank test and receiver operating characteristic analyses were performed for statistical analysis. For TIC categorization the accuracy was 61.54% for the traditional method and 82.05% for the proposed method. Using the proposed method, mean curve accuracies were 84.0% for SI_slope, 66.7% for MSI, 66.0% for E_initial, 66.0% for E_peak, 68.0% for ESER and 44.9% for SEP. In the lesion region, the accuracies for the aforementioned parameters were 80.8, 65.4, 66.7, 62.2, 69.2 and 57.1%, respectively. Accuracy of the MSI value derived from the traditional method was 63.4%. Compared with the traditional method, the proposed semi-automatic method in the current study may provide results with a higher accuracy to differentiate benign and malignant lesions. Therefore, the proposed method should be considered as a supplementary tool for the diagnosis of breast lesions.

Whole-tumour histogram analysis of pharmacokinetic parameters from dynamic contrast-enhanced MRI in resectable oesophageal squamous cell carcinoma can predict T-stage and regional lymph node metastasis

OBJECTIVE

To identify whether whole-tumour histogram analysis of pharmacokinetic parameters from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) could predict T-stage and regional lymph node metastasis (LNM) of resectable oesophageal squamous cell carcinoma (SCC).

MATERIALS AND METHODS

Forty-two consecutive patients with confirmed oesophageal SCC underwent thoracic DCE-MRI. Histogram metrics (median, mean, standard deviation [SD], skewness, kurtosis and entropy) of whole-tumour pharmacokinetic parameters including endothelial transfer constant (Ktrans), reflux rate (Kep) and fractional extravascular extracellular space volume (Ve) were generated by the Omni-Kinetics software. Histogram datasets were interpreted using the Mann-Whitney U test and receiver operating characteristic (ROC) statistical analyses.

RESULTS

The Mann-Whitney U tests revealed that the median, mean and SD of Ktrans, the SD and entropy of Kep, and the median, mean and entropy of Ve of T1-2 stage oesophageal SCC were lower when compared with T3 stage (all Ps < 0.05); and the ROC analysis showed that the entropy of Ve could reliably distinguish T1-2 stage from T3 stage with an area under ROC (AUC) of 0.773. The Mann-Whitney U tests illustrated that the entropy of Ktrans, and the median, mean, SD and entropy of Kep were higher while the skewness of Kep was lower in tumours with LNM than without LNM (all Ps < 0.05); and the ROC analysis demonstrated that the SD of Kep could best identify tumours with LNM with an AUC of 0.702.

CONCLUSION

Whole-tumour histogram analysis of pharmacokinetic parameters of oesophageal SCC on DCE-MRI could be used to predict T-stage and regional LNM.

[Comparison of Time-intensity Curve with Gadobenatedimeglumine and Gadobutrol on Multiphase Contrast-enhanced Breast MRI]

The purpose of this study was to compare the time-intensity curve (TIC) on multiphase contrast-enhanced breast magnetic resonance imaging (MRI) between Gadobenatedimeglumine (Gd-DTPA) and Gadobutrol. We assessed the images of 53 cases obtained from MRI that had malignant findings by pathology from October 2015 to October 2016 in our institute. Gd-DTPA and Gadobutrol were administrated in 16 and 37 cases, respectively. The TIC of the lesion was classified according to the Kuhl's method (type I: persistent pattern, type II: plateau pattern and type III: washout pattern). Type III was the most common TIC pattern in both the groups (Gd-DTPA, 12 cases; Gadobutrol, 18 cases). Type II was the second common TIC pattern in Gadobutrol group (12 cases). As a result, there was no significant difference in TIC analysis between Gd-DTPA and gadobutrol. In conclusion, the contrast between Gd-DTPA and Gadobutrol contrast media did not differ in TIC pattern of multiphasic contrast-enhanced breast MRI.

Discrimination between malignant and benign mass-like lesions from breast dynamic contrast enhanced MRI: semi-automatic vs. manual analysis of the signal time-intensity curves

Purpose: To investigate the performance of a new semi-automatic method for analyzing the signal time-intensity curve (TIC) obtained by breast dynamic contrast enhancement (DCE)-MRI.

Methods: In the conventional method, a circular region of interest was drawn manually onto the map reflecting the maximum slope of increase (MSI) to delineate the suspicious lesions. The mean TIC was determined subjectively as one of three different wash-out patterns. In the new method, the lesion area was identified semi-automatically. The mean TIC was categorized quantitatively. In addition to the MSI, other quantitative parameters were calculated, including the signal intensity slope (SI_slope), initial percentage of enhancement (E_initial), percentage of peak enhancement (E_peak), early signal enhancement ratio (ESER), and second enhancement percentage (SEP). The performances were compared with receiver operating characteristic (ROC) analysis and Wilcoxon's test.

Results: For TIC categorization results, the diagnostic accuracy rates were 61.54% with the traditional manual method and 76.92% with the new method. For the mean MSI values from the manual method, the accuracy was 63.41%. For the mean TIC derived using the semi-automatic method, the diagnostic accuracy were 82.05% for SI_slope, 67.31% for MSI, 61.53% for E_initial, 64.75% for E_peak, 64.74% for ESER, and 52.56% for SEP, respectively. For the lesion regions identified by the semi-automatic method, the diagnostic accuracy for above mentioned parameters were 80.13%, 69.87%, 61.54%, 63.47%, 64.74% and 55.13%, respectively.

Conclusion: With respect to the analysis of TIC from breast DCE-MRI, the results demonstrated that the new method increased the diagnostic accuracy, and should be considered as a supplementary tool for distinguishing benign and malignant lesions.

Value of DCE-MRI for staging and response evaluation in rectal cancer: A systematic review

PURPOSE

Aim was to perform a systematic review to evaluate the clinical value of dynamic contrast-enhanced (DCE) MRI in rectal cancer.

METHODS AND MATERIALS

A systematic search was performed on Pubmed, Embase and the Cochrane library. Studies that evaluated DCE-MRI for tumour aggressiveness, primary staging and restaging after chemoradiation (CRT) were included. Information on population, DCE technique, DCE parameters and outcome (angiogenesis, staging and response) were extracted.

RESULTS

19 studies were identified; 10 evaluated quantitative analyses, 6 semiquantitative analyses and 3 evaluated both. 8 studies evaluated correlation between DCE-parameters and angiogenesis or tumour aggressiveness, 11 studies evaluated response prediction pre- and post-CRT. Semiquantitative washin parameters showed a significantly positive correlation with angiogenesis, while for quantitative analyses conflicting results were found. Conflicting results were also reported for the correlation between DCE parameters and tumour aggressiveness: both higher and lower vascularity in more aggressive tumours are reported, while some studies report no correlation. Six studies showed a predictive value of Ktrans for response. A high Ktrans pre-CRT was significantly correlated with a complete/good response, but the reported pre-CRT Ktrans varied substantially (0.36-1.93). After CRT a reduction in Ktrans of 32%-36% was significantly associated with response. For semiquantitative analyses pre-CRT late slope was reported to be significantly lower in good responders, however only few studies exist on semiquantitative analyses of post-CRT DCE-MRI.

CONCLUSION

DCE-MRI in rectal cancer is promising mainly for prediction and assessment of response to CRT, where a high pre-CRT Ktrans and a decrease in Ktrans are significantly predictive for response.

Correlation between quantitative and semiquantitative parameters in DCE-MRI with a blood pool agent in rectal cancer: can semiquantitative parameters be used as a surrogate for quantitative parameters?

PURPOSE

The aim of this study was to assess correlation between quantitative and semiquantitative parameters in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in rectal cancer patients, both in a primary staging and restaging setting.

MATERIALS AND METHODS

Nineteen patients were included with DCE-MRI before and/or after neoadjuvant therapy. DCE-MRI was performed with gadofosveset trisodium (Ablavar^®, Lantheus Medical Imaging, North Billerica, Massachusetts, USA). Regions of interest were placed in the tumor and quantitative parameters were extracted with Olea Sphere 2.2 software permeability module using the extended Tofts model. Semiquantitative parameters were calculated on a pixel-by-pixel basis. Spearman rank correlation tests were used for assessment of correlation between parameters. A p value ≤0.05 was considered statistically significant.

RESULTS

Strong positive correlations were found between mean peak enhancement and mean K _trans: 0.79 (all patients, p<0.0001), 0.83 (primary staging, p = 0.003), and 0.81 (restaging, p = 0.054). Mean wash-in correlated significantly with mean V _p and K _ep (0.79 and 0.58, respectively, p<0.0001 and p = 0.009) in all patients. Mean wash-in showed a significant correlation with mean K _ep (0.67, p = 0.033) in the primary staging group. On the restaging MRI, mean wash-in only strongly correlated with mean V _p (0.81, p = 0.054).

CONCLUSION

This study shows a strong correlation between quantitative and semiquantitative parameters in DCE-MRI for rectal cancer. Peak enhancement correlates strongly with K _trans and wash-in showed strong correlation with V _p and K _ep. These parameters have been reported to predict tumor aggressiveness and response in rectal cancer. Therefore, semiquantitative analyses might be a surrogate for quantitative analyses.

Accuracy of combined dynamic contrast-enhanced magnetic resonance imaging and diffusion-weighted imaging for breast cancer detection: a meta-analysis

BACKGROUND

Magnetic resonance imaging (MRI) is increasingly being used to examine patients with suspected breast cancer.

PURPOSE

To determine the diagnostic performance of combined dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) for breast cancer detection.

MATERIAL AND METHODS

A comprehensive search of the PUBMED, EMBASE, Web of Science, and Cochrane Library databases was performed up to September 2014. Statistical analysis included pooling of sensitivity and specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and diagnostic accuracy using the summary receiver operating characteristic (SROC). All analyses were conducted using STATA (version 12.0), RevMan (version 5.2), and Meta-Disc 1.4 software programs.

RESULTS

Fourteen studies were analyzed, which included a total of 1140 patients with 1276 breast lesions. The pooled sensitivity and specificity of combined DCE-MRI and DWI were 91.6% and 85.5%, respectively. The pooled sensitivity and specificity of DWI-MRI were 86.0% and 75.6%, respectively. The pooled sensitivity and specificity of DCE-MRI were 93.2% and 71.1%. The area under the SROC curve (AUC-SROC) of combined DCE-MRI and DWI was 0.94, the DCE-MRI of 0.85. Deeks testing confirmed no significant publication bias in all studies.

CONCLUSION

Combined DCE-MRI and DWI had superior diagnostic accuracy than either DCE-MRI or DWI alone for the diagnosis of breast cancer.

Quantitative discrimination between invasive ductal carcinomas and benign lesions based on semi-automatic analysis of time intensity curves from breast dynamic contrast enhanced MRI

Background

Traditional subjective method for the analysis of time-intensity curves (TICs) from breast dynamic contrast enhanced MRI (DCE-MRI) presented a low specificity. Hence, a semi-automatic quantitative method was proposed and evaluated for distinguishing invasive ductal carcinomas from benign lesions.

Materials and methods

In the traditional method, the lesion was extracted by placing a region of interest (ROI) manually. The mean curve of the TICs from the ROI was subjectively classified as one of three patterns. Only one quantitative parameter, the mean value of maximum slope of increase (MSI), was provided. In the new method, the lesion was identified semi-automatically, and the mean curve was classified quantitatively. Some additional parameters, the signal intensity slope (SI_slope), initial percentage of enhancement (E_initial), percentage of peak enhancement (E_peak), early signal enhancement ratio (ESER), and second enhancement percentage (SEP) were derived from the mean curves as well as the lesion areas. Wilcoxon’s test and receiver operating characteristic (ROC) analyses were performed, and P < 0.05 was considered significant.

Results

According to the TIC classification results, the accuracies were 59.16% for the traditional manual method and 76.05% for the new method (P < 0.05). For the mean MSI values from the manual method, the accuracy was 63.35%. For the mean TICs derived from the semi-automatic method, the accuracies were 77.47% for SI_slope, 65.24% for MSI, 58.45% for E_initial, 66.20% for E_peak, 71.83% for ESER, and 54.93% for SEP, respectively. For the lesion regions identified by the semi-automatic method, the accuracies were 73.24%, 72.54%, 58.45%, 62.68%, 64.09%, and 55.64%, respectively.

Conclusion

Compared with traditional subjective method, the semi-automatic quantitative method proposed in this study showed a higher performance, and should be used as a supplementary tool to aid radiologist's subjective interpretation.

Assessing response in breast cancer with dynamic contrast-enhanced magnetic resonance imaging: are signal intensity-time curves adequate?

Quantitative DCE-MRI parameters including K(trans) (transfer constant min(-1)) can predict both response and outcome in breast cancer patients treated with neoadjuvant chemotherapy (NAC). Quantitative methods are time-consuming to calculate, requiring expensive software and interpretive expertise. For diagnostic purposes, signal intensity-time curves (SITCs) are used for tissue characterisation. In this study, we compare the ability of NAC-related changes in SITCs with K(trans) to predict response and outcomes. 73 women with primary breast cancer underwent DCE-MRI studies before and after two cycles of NAC. Patients received anthracycline and/or docetaxel-based chemotherapy. At completion of NAC, patients had local treatment with surgery & radiotherapy and further systemic treatments. SITCs for paired DCE-MRI studies were visually scored using a five-curve type classification schema encompassing wash-in and wash-out phases and correlated with K(trans) values and to the endpoints of pathological response, OS and DFS. 58 paired patients studies were evaluable. The median size by MRI measurement for 52 tumours was 38 mm (range 17-86 mm) at baseline and 26 mm (range 10-85 mm) after two cycles of NAC. Median baseline K(trans) (min(-1)) was 0.214 (range 0.085-0.469), and post-two cycles of NAC was 0.128 (range 0.013-0.603). SITC shapes were significantly related to K(trans) values both before (χ (2) = 43.3, P = 0.000) and after two cycles of NAC (χ (2) = 60.5, P = 0.000). Changes in curve shapes were significantly related to changes in K(trans) (χ (2) = 53.5, P = 0.000). Changes in curve shape were significantly correlated with clinical (P = 0.005) and pathological response (P = 0.005). Reductions in curve shape of ≥1 point were significant for overall improved survival using Kaplan-Meier analysis with a 5-year OS of 80.9 versus 68.6 % (P = 0.048). SITCs require no special software to generate and provide a useful method of assessing the effectiveness of NAC for primary breast cancer.

Response to neoadjuvant treatment of invasive ductal breast carcinomas including outcome evaluation: MRI analysis by an automatic CAD system in comparison to visual evaluation

BACKGROUND

The aim of this study was to evaluate imaging-based response to standardized neoadjuvant chemotherapy (NACT) regimen by dynamic contrast-enhanced magnetic resonance mammography (DCE-MRM), whereas MR images were analyzed by an automatic computer-assisted diagnosis (CAD) system in comparison to visual evaluation. MRI findings were correlated with histopathologic response to NACT and also with the occurrence of metastases in a follow-up analysis.

PATIENTS AND METHODS

Fifty-four patients with invasive ductal breast carcinomas received two identical MRI examinations (before and after NACT; 1.5T, contrast medium gadoteric acid). Pre-therapeutic images were compared with post-therapeutic examinations by CAD and two blinded human observers, considering morphologic and dynamic MRI parameters as well as tumor size measurements. Imaging-assessed response to NACT was compared with histopathologically verified response. All clinical, histopathologic, and DCE-MRM parameters were correlated with the occurrence of distant metastases.

RESULTS

Initial and post-initial dynamic parameters significantly changed between pre- and post-therapeutic DCE-MRM. Visually evaluated DCE-MRM revealed sensitivity of 85.7%, specificity of 91.7%, and diagnostic accuracy of 87.0% in evaluating the response to NACT compared to histopathology. CAD analysis led to more false-negative findings (37.0%) compared to visual evaluation (11.1%), resulting in sensitivity of 52.4%, specificity of 100.0%, and diagnostic accuracy of 63.0%. The following dynamic MRI parameters showed significant associations to occurring metastases: Post-initial curve type before NACT (entire lesions, calculated by CAD) and post-initial curve type of the most enhancing tumor parts after NACT (calculated by CAD and manually).

CONCLUSIONS

In the accurate evaluation of response to neoadjuvant treatment, CAD systems can provide useful additional information due to the high specificity; however, they cannot replace visual imaging evaluation. Besides traditional prognostic factors, contrast medium-induced dynamic MRI parameters reveal significant associations to patient outcome, i.e. occurrence of distant metastases.