Intravoxel Incoherent Motion Magnetic Resonance Imaging for Assessing Parotid Gland Tumors: Correlation and Comparison with Arterial Spin Labeling Imaging

Discriminating atypical parotid carcinoma and pleomorphic adenoma utilizing extracellular volume fraction and arterial enhancement fraction derived from contrast-enhanced CT imaging: A multicenter study

OBJECTIVES

To investigate the added value of extracellular volume fraction (ECV) and arterial enhancement fraction (AEF) derived from enhanced CT to conventional image and clinical features for differentiating between pleomorphic adenoma (PA) and atypical parotid adenocarcinoma (PCA) pre-operation.

METHODS

From January 2010 to October 2023, a total of 187 cases of parotid tumors were recruited, and divided into training cohort (102 PAs and 51 PCAs) and testing cohort (24 PAs and 10 atypical PCAs). Clinical and CT image features of tumor were assessed. Both enhanced CT-derived ECV and AEF were calculated. Univariate analysis identified variables with statistically significant differences between the two subgroups in the training cohort. Multivariate logistic regression analysis with the forward variable selection method was used to build four models (clinical model, clinical model+ECV, clinical model+AEF, and combined model). Diagnostic performances were evaluated using receiver operating characteristic (ROC) curve analyses. Delong's test compared model differences, and calibration curve and decision curve analysis (DCA) assessed calibration and clinical application.

RESULTS

Age and boundary were chosen to build clinical model, and to construct its ROC curve. Amalgamating the clinical model, ECV, and AEF to establish a combined model demonstrated superior diagnostic effectiveness compared to the clinical model in both the training and test cohorts (AUC = 0.888, 0.867). There was a significant statistical difference between the combined model and the clinical model in the training cohort (p = 0.0145).

CONCLUSIONS

ECV and AEF are helpful in differentiating PA and atypical PCA, and integrating clinical and CT image features can further improve the diagnostic performance.

Characterization of parotid gland tumors: Whole-tumor histogram analysis of diffusion weighted imaging, diffusion kurtosis imaging, and intravoxel incoherent motion - A pilot study

PURPOSE

To investigate the diagnostic performance of histogram features of diffusion parameters in characterizating parotid gland tumors.

METHOD

From December 2018 to January 2023, patients who underwent diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI), and intravoxel incoherent motion (IVIM) were consecutively enrolled in this retrospective study. The histogram features of diffusion parameters, including apparent diffusion coefficient (ADC), diffusion coefficient (Dk), diffusion kurtosis (K), pure diffusion coefficient (D), pseudo-diffusion coefficient (DP), and perfusion fraction (FP) were analyzed. The Mann-Whitney U test was used for comparison between benign parotid gland tumors (BPGTs) and malignant parotid gland tumors (MPGTs). Receiver operating characteristic curve and logistic regression analysis were used to identify the differential diagnostic performance. The Spearman's correlation coefficient was used to analyze the correlation between diffusion parameters and Ki-67 labeling index.

RESULTS

For diffusion MRI, twenty-three histogram features of diffusion parameters showed significant differences between BPGTs and MPGTs (all P < 0.05). Compared with the DWI model, the IVIM model and combined model had better diagnostic specificity (58 %, 94 %, and 88 %, respectively; both corrected P < 0.001) and accuracy (64 %, 89 %, and 86 %, respectively; both corrected P = 0.006). The combined model was superior to the single DWI model with improved IDI (IDI improvement 0.25). Significant correlations were found between Ki-67 and ADCmean, Dkmean, Kmean, and Dmean (r = -0.57 to 0.53; all P < 0.05).

CONCLUSIONS

Whole-tumor histogram analysis of IVIM and combined diffusion model could further improve the diagnostic performance for differentiating BPGTs from MPGTs.

Deep learning-assisted diagnosis of benign and malignant parotid tumors based on contrast-enhanced CT: a multicenter study

OBJECTIVES

To develop deep learning-assisted diagnosis models based on CT images to facilitate radiologists in differentiating benign and malignant parotid tumors.

METHODS

Data from 573 patients with histopathologically confirmed parotid tumors from center 1 (training set: n = 269; internal-testing set: n = 116) and center 2 (external-testing set: n = 188) were retrospectively collected. Six deep learning models (MobileNet V3, ShuffleNet V2, Inception V3, DenseNet 121, ResNet 50, and VGG 19) based on arterial-phase CT images, and a baseline support vector machine (SVM) model integrating clinical-radiological features with handcrafted radiomics signatures were constructed. The performance of senior and junior radiologists with and without optimal model assistance was compared. The net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to evaluate the clinical benefit of using the optimal model.

RESULTS

MobileNet V3 had the best predictive performance, with sensitivity increases of 0.111 and 0.207 (p < 0.05) in the internal- and external-testing sets, respectively, relative to the SVM model. Clinical benefit and overall efficiency of junior radiologist were significantly improved with model assistance; for the internal- and external-testing sets, respectively, the AUCs improved by 0.128 and 0.102 (p < 0.05), the sensitivity improved by 0.194 and 0.120 (p < 0.05), the NRIs were 0.257 and 0.205 (p < 0.001), and the IDIs were 0.316 and 0.252 (p < 0.001).

CONCLUSIONS

The developed deep learning models can assist radiologists in achieving higher diagnostic performance and hopefully provide more valuable information for clinical decision-making in patients with parotid tumors.

KEY POINTS

• The developed deep learning models outperformed the traditional SVM model in predicting benign and malignant parotid tumors. • Junior radiologist can obtain greater clinical benefits with assistance from the optimal deep learning model. • The clinical decision-making process can be accelerated in patients with parotid tumors using the established deep learning model.

Current status of diffusion-weighted imaging in differentiating parotid tumors

Recently, diffusion-weighted imaging (DWI) is an essential magnetic resonance imaging (MRI) protocol for head and neck imaging in clinical practice as it plays an important role in lesion detection, tumor extension evaluation, differential diagnosis, therapeutic effect prediction, therapy evaluation, and recurrence diagnosis. Especially in the parotid gland, several studies have already attempted to achieve accurate differentiation between benign and malignant tumors using DWI. A conventional single-shot echo-planar-based DWI is widely used for head and neck imaging, whereas advanced DWI sequences, such as intravoxel incoherent motion, diffusion kurtosis imaging, periodically rotated overlapping parallel lines with enhanced reconstruction, and readout-segmented echo-planar imaging (readout segmentation of long variable echo-trains), have been used to characterize parotid tumors. The mean apparent diffusion coefficient values are easily measured and useful for assessing cellularity and histological characteristics, whereas advanced image analyses, such as histogram analysis, texture analysis, and machine and deep learning, have been rapidly developed. Furthermore, a combination of DWI and other MRI protocols has reportedly improved the diagnostic accuracy of parotid tumors. This review article summarizes the current state of DWI in differentiating parotid tumors.

Discriminating between benign and malignant salivary gland tumors using diffusion-weighted imaging and intravoxel incoherent motion at 3 Tesla

PURPOSE

The purpose of this study was to retrospectively evaluate the diagnostic performances of diffusion-weighted imaging (DWI) and intravoxel incoherent motion (IVIM) for discriminating between benign and malignant salivary gland tumors (SGTs).

MATERIALS AND METHODS

Sixty-seven patients with 71 SGTs who underwent MRI examination at 3 Tesla were included. There were 34 men and 37 women with a mean age of 57 ± 17 (SD) years (age range: 20-90 years). SGTs included 21 malignant tumors (MTs) and 50 benign SGTs (33 pleomorphic adenomas [PAs] and 17 Warthin's tumors [WTs]). For each SGT, DWI and IVIM parameters, mean, skewness, and kurtosis of apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*) and perfusion volume fraction (f) were calculated and further compared between SGTs using univariable analysis. Areas under the curves (AUC) of receiver operating characteristic of significant parameters were compared using the Delong test.

RESULTS

Significant differences in ADC_mean, D_mean and D*_mean were found between SGTs (P < 0.001). The highest AUC values were obtained for ADC_mean (0.949) for identifying PAs and D*_mean (0.985) for identifying WTs and skewness and kurtosis did not outperform mean. To discriminate benign from malignant SGTs with thresholds set to maximize Youden index, IVIM and DWI produced accuracies of 85.9% (61/71; 95% CI: 75.6-93.0) and 77.5% (55/71; 95% CI: 66.0-86.5) but misdiagnosed MTs as benign in 28.6% (6/21) and 61.9% (13/21) of SGTs, respectively. After maximizing specificity to 100% for benign SGTs, the accuracies of IVIM and DWI decreased to 76.1% (54/71; 95% CI: 64.5-85.4) and 64.8% (46/71; 95% CI: 52.5-75.8) but no MTs were misdiagnosed as benign. IVIM and DWI correctly diagnosed 66.0% (33/50) and 50.0% (25/50) of benign SGTs and 46.5% (33/71) and 35.2% (25/71) of all SGTs, respectively.

CONCLUSION

IVIM is more accurate than DWI for discriminating between benign and malignant SGTs because of its advantage in detecting WTs. Thresholds set by maximizing specificity for benign SGTs may be advantageous in a clinical setting.

Feasibility of Intravoxel Incoherent Motion (IVIM) and Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) in Differentiation of Benign Parotid Gland Tumors

Aim: The aim of this prospective study is to identify quantitative intravoxel incoherent motion and dynamic contrast-enhanced magnetic resonance imaging parameters of the most frequent benign parotid tumors, compare their utility and diagnostic accuracy. Methods: The study group consisted of 52 patients with 64 histopathologically confirmed parotid focal lesions. Parametric maps representing apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (FP) and transfer constant (Ktrans), reflux constant (Kep), extra-vascular extra-cellular volume fraction (Ve), and initial area under curve in 60 s (iAUC) have been obtained from multiparametric MRI. Results: Statistically significant (p < 0.001) inter-group differences were found between pleomorphic adenomas (PA) and Warthin tumors (WT) in all tested parameters but iAUC. Receiver operating characteristic curves were constructed to determine the optimal cut-off levels of the most significant parameters allowing differentiation between WT and PA. The Area Under the Curve (AUC) values and thresholds were for ADC: 0.931 and 1.05, D: 0.896 and 0.9, Kep: 0.964 and 1.1 and Ve: 0.939 and 0.299, respectively. Lesions presenting with a combination of ADC, D, and Ve values superior to the cut-off and Kep values inferior to the cut-off are classified as pleomorphic adenomas. Lesions presenting with combination of ADC, D, and Ve values inferior to the cut-off and Kep values superior to the cut-off are classified as Warthin tumors. Conclusions: DWI, IVIM and quantitative analysis of DCE-MRI derived parameters demonstrated distinctive features of PAs and WT and as such they seem feasible in differentiation of benign parotid gland tumors.

Amide Proton Transfer Weighted and Intravoxel Incoherent Motion Imaging in Evaluation of Prognostic Factors for Rectal Adenocarcinoma

Objectives

To analyze the value of amide proton transfer (APT) weighted and intravoxel incoherent motion (IVIM) imaging in evaluation of prognostic factors for rectal adenocarcinoma, compared with diffusion weighted imaging (DWI).

Materials and Methods

Preoperative pelvic MRI data of 110 patients with surgical pathologically confirmed diagnosis of rectal adenocarcinoma were retrospectively evaluated. All patients underwent high-resolution T₂-weighted imaging (T₂WI), APT, IVIM, and DWI. Parameters including APT signal intensity (APT SI), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), and apparent diffusion coefficient (ADC) were measured in different histopathologic types, grades, stages, and structure invasion statuses. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic efficacy, and the corresponding area under the curves (AUCs) were calculated.

Results

APT SI, D and ADC values of rectal mucinous adenocarcinoma (MC) were significantly higher than those of rectal common adenocarcinoma (AC) ([3.192 ± 0.661%] vs. [2.333 ± 0.471%], [1.153 ± 0.238×10^-3 mm²/s] vs. [0.792 ± 0.173×10^-3 mm²/s], and [1.535 ± 0.203×10^-3 mm²/s] vs. [0.986 ± 0.124×10^-3 mm²/s], respectively; all P<0.001). In AC group, the APT SI and D values showed significant differences between low- and high-grade tumors ([2.226 ± 0.347%] vs. [2.668 ± 0.638%], and [0.842 ± 0.148×10^-3 mm²/s] vs. [0.777 ± 0.178×10^-3 mm²/s], respectively, both P<0.05). The D value had significant difference between positive and negative extramural vascular invasion (EMVI) tumors ([0.771 ± 0.175×10^-3 mm²/s] vs. [0.858 ± 0.151×10^-3 mm²/s], P<0.05). No significant difference of APT SI, D, D*, f or ADC was observed in different T stages, N stages, perineural and lymphovascular invasions (all P>0.05). The ROC curves showed that the AUCs of APT SI, D and ADC values for distinguishing MC from AC were 0.921, 0.893 and 0.995, respectively. The AUCs of APT SI and D values in distinguishing low- from high-grade AC were 0.737 and 0.663, respectively. The AUC of the D value for evaluating EMVI involvement was 0.646.

Conclusion

APT and IVIM were helpful to assess the prognostic factors related to rectal adenocarcinoma, including histopathological type, tumor grade and the EMVI status.

Comparative Study between ZOOMit and Conventional Intravoxel Incoherent Motion MRI for Assessing Parotid Gland Abnormalities in Patients with Early- or Mid-Stage Sjögren’s Syndrome

Objective

To compare the reproducibility and performance of quantitative metrics between ZOOMit and conventional intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) in the diagnosis of early- and mid-stage Sjögren’s syndrome (SS).

Materials and Methods

Twenty-two patients (mean age ± standard deviation, 52.0 ± 10.8 years; male:female, 2:20) with early- or mid-stage SS and 20 healthy controls (46.9 ± 14.6 years; male:female, 7:13) were prospectively enrolled in our study. ZOOMit IVIM and conventional IVIM MRI were performed simultaneously in all individuals using a 3T scanner. Quantitative IVIM parameters - including tissue diffusivity (D), pseudodiffusion coefficient (D^*), and perfusion fraction (f) - inter- and intra-observer reproducibility in measuring these parameters, and their ability to distinguish patients with SS from healthy individuals were assessed and compared between ZOOMit IVIM and conventional IVIM methods, appropriately. MR gland nodular grade (MRG) was also examined.

Results

Inter- and intra-observer reproducibility was better with ZOOMit imaging than with conventional IVIM imaging (ZOOMit vs. conventional, intraclass correlation coefficient of 0.897–0.941 vs. 0.667–0.782 for inter-observer reproducibility and 0.891–0.968 vs. 0.814–0.853 for intra-observer reproducibility). Significant differences in ZOOMit f, ZOOMit D^*, conventional D^*, and MRG between patients with SS and healthy individuals (all p < 0.05) were observed. ZOOMit D^* outperformed conventional D^* in diagnosing early- and mid-stage SS (area under receiver operating curve, 0.867 and 0.658, respectively; p = 0.002). The combination of ZOOMit D^*, MRG, and ZOOMit f as a new diagnostic index for SS, increased diagnostic area under the curve to 0.961, which was higher than that of any single parameter (all p < 0.01).

Conclusion

Considering its better reproducibility and performance, ZOOMit IVIM may be preferred over conventional IVIM MRI, and may subsequently improve the ability to diagnose early- and mid-stage SS.

Noncontrast Pediatric Brain Perfusion: Arterial Spin Labeling and Intravoxel Incoherent Motion

Noncontrast magnetic resonance imaging techniques for measuring brain perfusion include arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM). These techniques provide noninvasive and repeatable assessment of cerebral blood flow or cerebral blood volume without the need for intravenous contrast. This article discusses the technical aspects of ASL and IVIM with a focus on normal physiologic variations, technical parameters, and artifacts. Multiple pediatric clinical applications are presented, including tumors, stroke, vasculopathy, vascular malformations, epilepsy, migraine, trauma, and inflammation.

Arterial spin labeling for head and neck lesion assessment: technical adjustments and clinical applications

PURPOSE

Despite, currently, "state-of-the-art" magnetic resonance imaging (MRI) protocols for head and neck (H&N) lesion assessment incorporate perfusion sequences, these acquisitions require the intravenous injection of exogenous gadolinium-based contrast agents (GBCAs), which may have potential risks. Alternative techniques such as arterial spin labeling (ASL) can provide quantitative microvascular information similar to conventional perfusion sequences for H&N lesions evaluation, as a potential alternative without GBCA administration.

METHODS

We review the existing literature and analyze the latest evidence regarding ASL in H&N area highlighting the technical adjustments needed for a proper ASL acquisition in this challenging region for lesion characterization, treatment monitoring, and tumor recurrence detection.

RESULTS

ASL techniques, widely used for central nervous system lesions evaluation, can be also applied to the H&N region. Technical adjustments, especially regarding post-labeling delay, are mandatory to obtain robust and reproducible results. Several studies have demonstrated the feasibility of ASL in the H&N area including the orbits, skull base, paranasal sinuses, upper airway, salivary glands, and thyroid.

CONCLUSION

ASL is a feasible technique for the assessment of H&N lesions without the need of GBCAs. This manuscript reviews ASL's physical basis, emphasizing the technical adjustments necessary for proper ASL acquisition in this unique and challenging anatomical region, and the main applications in evaluating H&N lesions.

Influence of post-label delay time on the performance of 3D pseudo-continuous arterial spin labeling magnetic resonance imaging in the characterization of parotid gland tumors

OBJECTIVE

To evaluate the influence of post-label delay times (PLDs) on the performance of 3D pseudo-continuous arterial spin labeling (pCASL) magnetic resonance imaging for characterizing parotid gland tumors and to explore the optimal PLDs for the differential diagnosis.

MATERIALS AND METHOD

Fifty-eight consecutive patients with parotid gland tumors were enrolled, including 33 patients with pleomorphic adenomas (PAs), 16 patients with Warthin's tumors (WTs), and 9 patients with malignant tumors (MTs). 3D pCASL was scanned for each patient five times, with PLDs of 1025 ms, 1525 ms, 2025 ms, 2525 ms, and 3025 ms. Tumor blood flow (TBF) was calculated, and compared among different PLDs and tumor groups. Performance of TBF at different PLDs was evaluated using receiver operating characteristic analysis.

RESULTS

With an increasing PLD, TBF tended to gradually increase in PAs (p < 0.001), while TBF tended to slightly increase and then gradually decrease in WTs (p = 0.001), and PAs showed significantly lower TBF than WTs at all 5 PLDs (p < 0.05). PAs showed significantly lower TBF than MTs at 4 PLDs (p < 0.05), except at 3025 ms (p = 0.062). WTs showed higher TBF than MTs at all 5 PLDs; however, differences did not reach significance (p > 0.05). Setting a TBF of 64.350 mL/100g/min at a PLD of 1525 ms, or a TBF of 23.700 mL/100g/min at a PLD of 1025 ms as the cutoff values, optimal performance could be obtained for differentiating PAs from WTs (AUC = 0.905) or from MTs (AUC = 0.872).

CONCLUSIONS

Short PLDs (1025 ms or 1525 ms) are suggested to be used in 3D pCASL for characterizing parotid gland tumors in clinical practice.

KEY POINTS

• With 5 different PLDs, 3D pCASL can reflect the variation of blood flow in parotid gland tumors. • 3D pCASL is useful for characterizing PAs from WTs or MTs. • Short PLDs (1025 ms or 1525 ms) are suggested to be used in 3D pCASL for characterizing parotid gland tumors in clinical practice.