Standard diffusion-weighted, diffusion kurtosis and intravoxel incoherent motion MR imaging of sinonasal malignancies: correlations with Ki-67 proliferation status

Dynamic contrast-enhanced and diffusion-weighted MRI of cervical carcinoma: Correlations with Ki-67 proliferation status

OBJECTIVES

To investigate the association of quantitative parameter (apparent diffusion coefficient [ADC]) from diffusion-weighted imaging (DWI) and various quantitative and semiquantitative parameters from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) with Ki-67 proliferation index (PI) in cervical carcinoma (CC).

METHODS

A total of 102 individuals with CC who received 3.0 T MRI examination (DWI and DCE MRI) between October 2016 and December 2022 were enrolled in our investigation. Two radiologists separately assessed the ADC parameter and various quantitative and semiquantitative parameters including (volume transfer constant [Ktrans], rate constant [kep], extravascular extracellular space volume fraction [ve], volume fraction of plasma [vp], time to peak [TTP], maximum concentration [MaxCon], maximal slope [MaxSlope] and area under curve [AUC]) for each tumor. Their association with Ki-67 PI was analyzed by Spearman association analysis. The discrepancy between low-proliferation and high-proliferation groups was subsequently analyzed. The receiver operating characteristic (ROC) curve analysis utilized to identify optimal cut-off points for significant parameters.

RESULTS

Both ADC (ρ = -0.457, p < 0.001) and Ktrans (ρ = -0.467, p < 0.001) indicated a strong negative association with Ki-67 PI. Ki-67 PI showed positive correlations with TTP, MaxCon, MaxSlope and AUC (ρ = 0.202, 0.231, 0.309, 0.235, respectively; all p values<0.05). Compared with the low-proliferation group, high-Ki-67 group presented a significantly lower ADC (0.869 ± 0.125 × 10-3 mm2/s vs. 1.149 ± 0.318 × 10-3 mm2/s; p < 0.001) and Ktrans (1.314 ± 1.162 min-1vs. 0.391 ± 0.390 min-1; p < 0.001), also significantly higher MaxCon values (0.756 ± 0.959 vs. 0.422 ± 0.341; p < 0.05) and AUC values (2.373 ± 3.012 vs. 1.273 ± 1.000; p < 0.05). The cut-offs of ADC, Ktrans, MaxCon and AUC for discrimating low- and high-Ki-67 groups were 0.920 × 10-3 mm2/s, 0.304 min-1, 0.209 and 1.918, respectively.

CONCLUSIONS

ADC, Ktrans, TTP, MaxCon, MaxSlope and AUC are associated with Ki-67 PI. ADC and Ktrans exhibited high performance to discriminate low and high Ki-67 status of CC.

Detecting Muscle Invasion of Bladder Cancer: An Application of Diffusion Kurtosis Imaging Ratio and Vesical Imaging-Reporting and Data System

BACKGROUND

Independent factors are needed to supplement vesical imaging-reporting and data system (VI-RADS) to improve its ability to identify muscle invasive bladder cancer (MIBC).

PURPOSE

To assess the correlation between MIBC and diffusion kurtosis imaging (DKI) ratio, VI-RADS, and other factors (such as tumor location).

STUDY TYPE

Retrospective.

POPULATION

Sixty-eight patients (50 males and 18 females; age: 70.1 ± 9.5 years) with bladder urothelial carcinoma.

FIELD STRENGTH/SEQUENCE

1.5 T, conventional diffusion-weighted imaging (DWI), and DKI (single shot echo-planar sequence).

ASSESSMENT

Three radiologists independently measured the diffusion parameters of each bladder cancer (BCa) and obturator internus, including the mean apparent diffusion coefficient (ADCmean), mean kurtosis (MK), and mean diffusion (MD). And the ratio of diffusion parameters between BCa and obturator internus was calculated (diffusion parameter ratio = bladder cancer:obturator internus). Based on the VI-RADS, the target lesions were independently scored. Furthermore, the actual tumor-wall contact length (ACTCL) and absolute tumor-wall contact length (ABTCL) were measured.

STATISTICAL TESTS

Multicollinearity among independent variables was evaluated using the variance inflation factor (VIF). Multivariable logistic regression analysis was used to determine the independent risk factors of MIBC. The receiver operating characteristic curve was used to evaluate the efficacy of each variable in detecting MIBC. The DeLong test was used to compare the area under the curve (AUC). A P < 0.05 was considered statistically significant.

RESULTS

MKratio (median: 0.62) and VI-RADS were independent risk factors for MIBC. AUCs for MKratio, VI-RADS, and MKratio combined with VI-RADS in assessing MIBC were 0.895, 0.871, and 0.973, respectively. MKratio combined with VI-RADS was more effective in diagnosing MIBC than VI-RADS alone.

DATA CONCLUSIONS

MKratio has potential to assist the assessment of MIBC. MKratio can be used as a supplement to VI-RADS for detecting MIBC.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY: Stage 2.

Multiparametric MRI-based radiomics approach with deep transfer learning for preoperative prediction of Ki-67 status in sinonasal squamous cell carcinoma

Purpose

Based on comparison of different machine learning (ML) models, we developed the model that integrates traditional hand-crafted (HC) features and ResNet50 network-based deep transfer learning (DTL) features from multiparametric MRI to predict Ki-67 status in sinonasal squamous cell carcinoma (SNSCC).

Methods

Two hundred thirty-one SNSCC patients were retrospectively reviewed [training cohort (n = 185), test cohort (n = 46)]. Pathological grade, clinical, and MRI characteristics were analyzed to choose the independent predictor. HC and DTL radiomics features were extracted from fat-saturated T2-weighted imaging, contrast-enhanced T1-weighted imaging, and apparent diffusion coefficient map. Then, HC and DTL features were fused to formulate the deep learning-based radiomics (DLR) features. After feature selection and radiomics signature (RS) building, we compared the predictive ability of RS-HC, RS-DTL, and RS-DLR.

Results

No independent predictors were found based on pathological, clinical, and MRI characteristics. After feature selection, 42 HC and 10 DTL radiomics features were retained. The support vector machine (SVM), LightGBM, and ExtraTrees (ET) were the best classifier for RS-HC, RS-DTL, and RS-DLR. In the training cohort, the predictive ability of RS-DLR was significantly better than those of RS-DTL and RS-HC (p< 0.050); in the test set, the area under curve (AUC) of RS-DLR (AUC = 0.817) was also the highest, but there was no significant difference of the performance between DLR-RS and HC-RS.

Conclusions

Both the HC and DLR model showed favorable predictive efficacy for Ki-67 expression in patients with SNSCC. Especially, the RS-DLR model represented an opportunity to advance the prediction ability.

Synthetic MRI and amide proton transfer-weighted MRI for differentiating between benign and malignant sinonasal lesions

OBJECTIVES

To explore the value of the synthetic MRI (SyMRI), combined with amide proton transfer-weighted (APTw) MRI for quantitative and morphologic assessment of sinonasal lesions, which could provide relative scale for the quantitative assessment of tissue properties.

METHODS

A total of 80 patients (31 malignant and 49 benign) with sinonasal lesions, who underwent the SyMRI and APTw examination, were retrospectively analyzed. Quantitative parameters (T1, T2, proton density (PD)) and APT % were obtained through outlining the region of interest (ROI) and comparing the two groups utilizing independent Student t test or a Wilcoxon test. Receiver operating characteristic curve (ROC), Delong test, and logistic regression analysis were performed to assess the diagnostic efficiency of one-parameter and multiparametric models.

RESULTS

SyMRI-derived mean T1, T2, and PD were significantly higher and APT % was relatively lower in benign compared to malignant sinonasal lesions (p < 0.05). The ROC analysis showed that the AUCs of the SyMRI-derived quantitative (T1, T2, PD) values and APT % ranged from 0.677 to 0.781 for differential diagnosis between benign and malignant sinonasal lesions. The T2 values showed the best diagnostic performance among all single parameters for differentiating these two masses. The AUCs of combined SyMRI-derived multiple parameters with APT % (AUC = 0.866) were the highest than that of any single parameter, which was significantly improved (p < 0.05).

CONCLUSION

The combination of SyMRI and APTw imaging has the potential to reflect intrinsic tissue characteristics useful for differentiating benign from malignant sinonasal lesions.

CLINICAL RELEVANCE STATEMENT

Combining synthetic MRI with amide proton transfer-weighted imaging could function as a quantitative and contrast-free approach, significantly enhancing the differentiation of benign and malignant sinonasal lesions and overcoming the limitations associated with the superficial nature of endoscopic nasal sampling.

KEY POINTS

• Synthetic MRI and amide proton transfer-weighted MRI could differentiate benign from malignant sinonasal lesions based on quantitative parameters. • The diagnostic efficiency could be significantly improved through synthetic MRI + amide proton transfer-weighted imaging. • The combination of synthetic MRI and amide proton transfer-weighted MRI is a noninvasive method to evaluate sinonasal lesions.

Standard diffusion-weighted, diffusion kurtosis and intravoxel incoherent motion in differentiating invasive placentas

PURPOSE

To investigate the diagnostic value of monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in distinguishing invasive placentas.

METHODS

A total of 53 patients with invasive placentas and 47 patients with noninvasive placentas undergoing conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) were retrospectively enrolled. The mean, minimum, and maximum parameters including the apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard DWI, diffusion kurtosis (MK), and diffusion coefficient (MD) from DKI and pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from IVIM were measured and compared from the volumetric analysis. Receiver operating characteristics (ROC) curve and logistic regression analyses were conducted to evaluate the diagnostic efficiency of different diffusion parameters for distinguishing invasive placentas.

RESULTS

Comparisons between accreta lesions in patients with invasive placentas (AL) and lower 1/3 part of the placenta in patients with noninvasive placentas (LP) demonstrated that MD mean, D mean, and D* mean were significantly lower while ADC max and D max were significantly higher in invasive placentas (all p < 0.05). Multivariate analysis demonstrated that D mean, D max and D* mean differed significantly among all the studied parameters for invasive placentas. A combined use of these three parameters yielded an AUC of 0.86 with sensitivity, specificity, and accuracy of 84.91%, 76.60%, and 80%, respectively.

CONCLUSION

The combined use of different IVIM parameters is helpful in distinguishing invasive placentas.

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.

Non-Gaussian model-based diffusion-weighted imaging of oral squamous cell carcinoma: associations with Ki-67 proliferation status

OBJECTIVES

To investigate possible associations between diffusion-weighted imaging (DWI) parameters derived from a non-Gaussian model fitting and Ki-67 status in patients with oral squamous cell carcinoma (OSCC).

METHODS

Twenty-four patients with newly diagnosed OSCC were prospectively recruited. DWI was performed using six b-values (0-2500). The diffusion-related parameters of kurtosis value (K), kurtosis-corrected diffusion coefficient (DK), diffusion heterogeneity (α), distributed diffusion coefficient (DDC), slow diffusion coefficient (Dslow), and apparent diffusion coefficient (ADC) were calculated from four diffusion fitting models. Ki-67 status was categorized as low (Ki-67 percentage score < 20%), middle (20-50%), or high (> 50%). Kruskal-Wallis tests were performed between each non-Gaussian diffusion model parameters and Ki-67 grade.

RESULTS

The Kruskal-Wallis tests revealed that multiple parameters (K, ADC, Dk, DDC and Dslow) showed statistically significant differences between the three levels of Ki-67 status (K: p = 0.020, ADC: p = 0.012, Dk: p = 0.027, DDC: p = 0.007 and Dslow: p = 0.026).

CONCLUSIONS

Several non-Gaussian diffusion model parameters and ADC values were significantly associated with Ki-67 status and have potential as promising prognostic biomarkers in patients with OSCC.

T1 mapping and multimodel diffusion-weighted imaging in the assessment of cervical cancer: a preliminary study

OBJECTIVE

To evaluate the clinical feasibility of T1 mapping and multimodel diffusion-weighted imaging (DWI) for assessing the histological type, grade, and lymphovascular space invasion (LVSI) of cervical cancer.

METHODS

Eighty patients with cervical cancer and 43 patients with a normal cervix underwent T1 mapping and DWI with 11 b-values (0-2000 s/mm2). Monoexponential, biexponential, and kurtosis models were fitted to calculate the apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion (D*), perfusion fraction (f), mean diffusivity (MD), and mean kurtosis (MK). Native T1 and DWI-derived parameters (ADCmean, ADCmin, Dmean, Dmin, D*, f, MDmean, MDmin, MKmean, and MKmax) were compared based on histological type, grade, and LVSI status.

RESULTS

Native T1 and DWI-derived parameters differed significantly between cervical cancer and normal cervix (all p < 0.05), except D* (p = 0.637). Native T1 and MKmean varied significantly between squamous cell carcinoma (SCC) and adenocarcinoma (both p < 0.05). ADCmin, Dmin, and MDmin were significantly lower while MKmax was significantly higher in the high-grade SCC group than in the low-grade SCC group (all p < 0.05). LVSI-positive SCC had a significantly higher MKmean than LVSI-negative SCC (p < 0.05).

CONCLUSION

Both T1 mapping and multimodel DWI can effectively differentiate cervical cancer from a normal cervix and cervical adenocarcinoma from SCC. Furthermore, multimodel DWI may provide quantitative metrics for non-invasively predicting histological grade and LVSI status in SCC patients.

ADVANCES IN KNOWLEDGE

Combined use of T1 mapping and multimodel DWI may provide more comprehensive information for non-invasive pre-operative evaluation of cervical cancer.

An MRI-Based Radiomics Nomogram to Assess Recurrence Risk in Sinonasal Malignant Tumors

BACKGROUND

Sinonasal malignant tumors (SNMTs) have a high recurrence risk, which is responsible for the poor prognosis of patients. Assessing recurrence risk in SNMT patients is a current problem.

PURPOSE

To establish an MRI-based radiomics nomogram for assessing relapse risk in patients with SNMT.

STUDY TYPE

Retrospective.

POPULATION

A total of 143 patients with 68.5% females (development/validation set, 98/45 patients).

FIELD STRENGTH/SEQUENCE

A 1.5-T and 3-T, fat-suppressed fast spin echo (FSE) T2-weighted imaging (FS-T2WI), FSE T1-weighted imaging (T1WI), and FSE contrast-enhanced T1WI (T1WI + C).

ASSESSMENT

Three MRI sequences were used to manually delineate the region of interest. Three radiomics signatures (T1WI and FS-T2WI sequences, T1WI + C sequence, and three sequences combined) were built through dimensional reduction of high-dimensional features. The clinical model was built based on clinical and MRI features. The Ki-67-based and tumor-node-metastasis (TNM) model were established for comparison. The radiomics nomogram was built by combining the clinical model and best radiomics signature. The relapse-free survival analysis was used among 143 patients.

STATISTICAL TESTS

The intraclass/interclass correlation coefficients, univariate/multivariate Cox regression analysis, least absolute shrinkage and selection operator Cox regression algorithm, concordance index (C index), area under the curve (AUC), integrated Brier score (IBS), DeLong test, Kaplan-Meier curve, log-rank test, optimal cutoff values. A P value < 0.05 was considered statistically significant.

RESULTS

The T1 + C-based radiomics signature had best prognostic ability than the other two signatures (T1WI and FS-T2WI sequences, and three sequences combined). The radiomics nomogram had better prognostic ability and less error than the clinical model, Ki-67-based model, and TNM model (C index, 0.732; AUC, 0.765; IBS, 0.185 in the validation set). The cutoff values were 0.2 and 0.7 and then the cumulative risk rates were calculated.

DATA CONCLUSION

A radiomics nomogram for assessing relapse risk in patients with SNMT may provide better prognostic ability than the clinical model, Ki-67-based model, and TNM model.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 5.

Differentiation of placenta percreta through MRI features and diffusion-weighted magnetic resonance imaging

OBJECTIVES

To identify whether parameters measured from diffusion kurtosis and intravoxel incoherent motion help diagnose placenta percreta.

METHODS

We retrospectively enrolled 75 patients with PAS disorders including 13 patients with placenta percreta and 40 patients without PAS disorders. Each patients underwent diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI). The apparent diffusion coefficient (ADC), perfusion fraction (f), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), mean diffusion kurtosis (MK) and mean diffusion coefficient (MD) were measured by the volumetric analysis and compared. MRI features were also analyzed and compared. The receiver operating characteristic (ROC) curve and logistic regression analysis were used to evaluate the diagnostic efficiency of different diffusion parameters and MRI features for distinguishing placental percreta.

RESULTS

D* was an independent risk factor from DWI for predicting placenta percreta with sensitivity of 73% and specificity of 76%. Focal exophytic mass remained as independent risk factor from MRI features for predicting placenta percreta with sensitivity of 72.7% and specificity of 88.1%. When the two risk factors were combined together, the AUC was the highest, 0.880 (95% CI 0.8-0.96).

CONCLUSION

D* and focal exophytic mass were associated with placenta percreta. A combination of the 2 risk factors can be used to predict placenta percreta.

CRITICAL RELEVANCE STATEMENT

A combination of D* and focal exophytic mass can be used to differentiate placenta percreta.

Correlations between DKI and DWI with Ki-67 in gastric adenocarcinoma

BACKGROUND

Diffusion kurtosis imaging (DKI) has been applied for gastric adenocarcinoma. Correlations between its parameters and Ki-67 are unclear.

PURPOSE

To investigate the correlation between DKI and diffusion-weighted imaging (DWI) parameters with the Ki-67 index in gastric adenocarcinoma.

MATERIAL AND METHODS

A total of 54 patients with gastric adenocarcinoma were enrolled in the study and underwent DWI and DKI at 3.0-T MRI before surgery. Based on the settings of the regions of interest, the DWI and DKI parameters (including apparent diffusion coefficient [ADC], diffusion kurtosis [K], and diffusion coefficient [DK]) of each patient's gastric adenocarcinoma were measured and calculated. The participants were divided into two groups (low Ki-67 group and high Ki-67 groups). The intraclass correlation coefficient (ICC) and independent-sample t-test were used to compare differences in each parameter between two groups. Spearman's correlation coefficient was calculated to determine the correlation between Ki-67 and the parameters. Each parameter was compared using the area under the receiver operating characteristic curve. All parameters were included in the multivariate logistic regression analysis to explore the relationship between each parameter and high Ki-67 index.

RESULTS

ADC and DK were negatively relevant with Ki-67 and K was positively relevant with Ki-67 in gastric adenocarcinoma. ADC, DK, and K had diagnostic efficiency in differentiating the low Ki-67 group from the high Ki-67 group. A higher K value independently predicted a high Ki-67 status.

CONCLUSION

DWI and DKI reflected the proliferative characteristics of gastric adenocarcinoma. K was the strongest independent factor for predicting high Ki-67 status.

Advances in The Application and Research of Magnetic Resonance Diffusion Kurtosis Imaging in The Musculoskeletal System

Magnetic resonance diffusion kurtosis imaging (DKI) is an emerging magnetic resonance imaging (MRI) technique that can reflect microstructural changes in tissue through non-Gaussian diffusion of water molecules. Compared to traditional diffusion weighted imaging (DWI), the DKI model has shown greater sensitivity for diagnosis of musculoskeletal diseases and can help formulate more reasonable treatment plans. Moreover, DKI is an important auxiliary examination for evaluation of the motor function of the musculoskeletal system. This article briefly introduces the basic principles of DKI and reviews the application and research of DKI in the evaluation of disorders of the musculoskeletal system (including bone tumors, soft tissue tumors, spinal lesions, chronic musculoskeletal diseases, musculoskeletal trauma, and developmental disorders) as well as the normal musculoskeletal tissues. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: 1.

A diagnostic scoring model of ENKTCL in the nose-Waldeyer's ring based on logistic regression: Differential diagnosis from DLBCL

Objective

To establish a logistic regression model based on CT and MRI imaging features and Epstein-Barr (EB) virus nucleic acid to develop a diagnostic score model to differentiate extranodal NK/T nasal type (ENKTCL) from diffuse large B cell lymphoma (DLBCL).

Methods

This study population was obtained from two independent hospitals. A total of 89 patients with ENKTCL (n = 36) or DLBCL (n = 53) from January 2013 to May 2021 were analyzed retrospectively as the training cohort, and 61 patients (ENKTCL=27; DLBCL=34) from Jun 2021 to Dec 2022 were enrolled as the validation cohort. All patients underwent CT/MR enhanced examination and EB virus nucleic acid test within 2 weeks before surgery. Clinical features, imaging features and EB virus nucleic acid results were analyzed. Univariate analyses and multivariate logistic regression analyses were performed to identify independent predictors of ENKTCL and establish a predictive model. Independent predictors were weighted with scores based on regression coefficients. A receiver operating characteristic (ROC) curve was created to determine the diagnostic ability of the predictive model and score model.

Results

We searched for significant clinical characteristics, imaging characteristics and EB virus nucleic acid and constructed the scoring system via multivariate logistic regression and converted regression coefficients to weighted scores. The independent predictors for ENKTCL diagnosis in multivariate logistic regression analysis, including site of disease (nose), edge of lesion (blurred), T2WI (high signal), gyrus like changes, EB virus nucleic acid (positive), and the weighted score of regression coefficient was 2, 3, 4, 3, 4 points. The ROC curves, AUCs and calibration tests were carried out to evaluate the scoring models in both the training cohort and the validation cohort. The AUC of the scoring model in the training cohort were 0.925 (95% CI, 0.906-0.990) and the cutoff point was 5 points. In the validation cohort, the AUC was 0.959 (95% CI, 0.915-1.000) and the cutoff value was 6 points. Four score ranges were as follows: 0-6 points for very low probability of ENKTCL, 7-9 points for low probability; 10-11 points for middle probability; 12-16 points for very high probability.

Conclusion

The diagnostic score model of ENKTCL based on Logistic regression model which combined with imaging features and EB virus nucleic acid. The scoring system was convenient, practical and could significantly improve the diagnostic accuracy of ENKTCL and the differential diagnosis of ENKTCL from DLBCL.

Diffusion and perfusion MRI parameters in the evaluation of placenta accreta spectrum disorders in patients with placenta previa

OBJECTIVES

To evaluate the placental function by monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in patients with placenta previa.

METHODS

A total of 62 patients with placenta accreta spectrum (PAS) disorders and 11 patients with normal placentas were retrospectively enrolled, who underwent conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI). The apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard DWI, mean kurtosis (MK), and diffusion coefficient (MD) from DKI, and pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from IVIM were measured and compared from the volumetric analysis.

RESULTS

Comparisons between patients with PAS disorders and patients with normal placentas demonstrated that MD mean, D mean, and D* mean values in patients with PAS disorders were significantly higher than those in patients with normal placentas (p < 0.05). Comparisons between patients with accreta, increta, and percreta, and patients with normal placentas showed that the D mean was significantly higher in patients with placenta increta and percreta than in patients with normal placentas (p < 0.05).

CONCLUSION

The accreta lesions in PAS disorders had deceased cellularity and increased blood movement. The alteration of placental cellularity was more prominent in placenta increta and percreta.

State of the Art: Lung Cancer Staging Using Updated Imaging Modalities

Lung cancer is among the most common mortality causes worldwide. This scientific article is a comprehensive review of current knowledge regarding screening, subtyping, imaging, staging, and management of treatment response for lung cancer. The traditional imaging modality for screening and initial lung cancer diagnosis is computed tomography (CT). Recently, a dual-energy CT was proven to enhance the categorization of variable pulmonary lesions. The National Comprehensive Cancer Network (NCCN) recommends usage of fluorodeoxyglucose positron emission tomography (FDG PET) in concert with CT to properly stage lung cancer and to prevent fruitless thoracotomies. Diffusion MR is an alternative to FDG PET/CT that is radiation-free and has a comparable diagnostic performance. For response evaluation after treatment, FDG PET/CT is a potent modality which predicts survival better than CT. Updated knowledge of lung cancer genomic abnormalities and treatment regimens helps to improve the radiologists’ skills. Incorporating the radiologic experience is crucial for precise diagnosis, therapy planning, and surveillance of lung cancer.

The prognostic value of S-100 protein and Ki-67 index in olfactory neuroblastoma

OBJECTIVE

To evaluate the prognostic value of S-100 protein and Ki-67 labeling index in olfactory neuroblastomas.

METHODS

A retrospective study was conducted on a cohort of 85 patients with olfactory neuroblastomas. The immunohistochemical expression of S-100 and Ki-67 was assessed, and the predictive value of S-100 and Ki-67 was further evaluated. The optimal cutoff value of Ki-67 labeling index was determined using time-dependent receiver operating characteristic curve analysis. Overall survival and progression-free survival were assessed using the Kaplan-Meier method.

RESULTS

A cut-off Ki-67 labeling index value of 67.5% was determined for prognosis in patients with olfactory neuroblastomas. There was a significant correlation between Ki-67 expression and cervical lymph node metastasis (P = 0.049). Compared with S-100 (+), S-100 (-) was associated with a higher rate of lymph node metastasis and a higher level of Ki-67 (P = 0.007, < 0.001, respectively), as well as an advanced Kadish stage (P = 0.037). Survival analyses showed that patients with S-100 (+) had better 5-year overall survival than those with S-100 (-) (P = 0.028), and patients with both S-100 (+) and Ki-67 (<67.5%) had superior 5-year overall survival compared with all the other patients (P = 0.0225).

CONCLUSION

Our findings suggest that S-100 combined with Ki-67 labeling index are reliable prognostic factors in patients with olfactory neuroblastomas.

Multi-parametric MRI-based radiomics signature for preoperative prediction of Ki-67 proliferation status in sinonasal malignancies: a two-centre study

OBJECTIVE

To assess the predictive ability of a multi-parametric MRI-based radiomics signature (RS) for the preoperative evaluation of Ki-67 proliferation status in sinonasal malignancies.

METHODS

A total of 128 patients with sinonasal malignancies that underwent multi-parametric MRIs at two medical centres were retrospectively analysed. Data from one medical centre (n = 77) were used to develop the predictive models and data from the other medical centre (n = 51) constitute the test dataset. Clinical data and conventional MRI findings were reviewed to identify significant predictors. Radiomics features were determined using maximum relevance minimum redundancy and least absolute shrinkage and selection operator algorithms. Subsequently, RSs were established using a logistic regression (LR) algorithm. The predictive performance of RSs was assessed using calibration, decision curve analysis (DCA), accuracy, and AUC.

RESULTS

No independent predictors of high Ki-67 proliferation were observed based on clinical data and conventional MRI findings. RS-T1, RS-T2, and RS-T1c (contrast enhancement T1WI) were established based on a single-parametric MRI. RS-Combined (combining T1WI, FS-T2WI, and T1c features) was developed based on multi-parametric MRI and achieved an AUC and accuracy of 0.852 (0.733-0.971) and 86.3%, respectively, on the test dataset. The calibration curve and DCA demonstrated an improved fitness and benefits in clinical practice.

CONCLUSIONS

A multi-parametric MRI-based RS may be used as a non-invasive, dependable, and accurate tool for preoperative evaluation of the Ki-67 proliferation status to overcome the sampling bias in sinonasal malignancies.

KEY POINTS

• Multi-parametric MRI-based radiomics signatures (RSs) are used to preoperatively evaluate the proliferation status of Ki-67 in sinonasal malignancies. • Radiomics features are determined using maximum relevance minimum redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) algorithms. • RSs are established using a logistic regression (LR) algorithm.

Dynamic contrast-enhanced MRI can quantitatively identify malignant transformation of sinonasal inverted papilloma

OBJECTIVE

To investigate the diagnostic performance of quantitative and semi-quantitative parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) in differentiating sinonasal inverted papilloma (SIP) from SIP with coexisting malignant transformation into squamous cell carcinoma (MT-SIP).

METHODS

This retrospective study included 122 patients with 88 SIP and 34 MT-SIP. Quantitative and semi-quantitative parameters derived from DCE-MRI were compared between SIP and MT-SIP. The multivariate logistic regression analysis was performed to identify independent indicators and construct regression model for distinguishing MT-SIP and SIP. Diagnostic performance of independent indicators and regression model were evaluated using receiver operating coefficient (ROC) analysis and compared using DeLong test.

RESULTS

There were significant differences in maximum slope of increase, contrast-enhancement ratio, bolus arrival time, volume of extravascular extracellular space (Ve), and rate constant (Kep) between SIP and MT-SIP (p < 0.05). There were no significant differences in initial area under the gadolinium curve (p = 0.174) and volume transfer constant (p = 0.105) between two groups. Multivariate analysis results showed that Ve and Kep were identified as the independent indicators for differentiating MT-SIP from SIP (p < 0.001). Areas under the ROC curves (AUCs) for predicting MT-SIP were 0.779 for Ve and 0.766 for Kep. The AUC of the combination of Ve and Kep was 0.831, yielding 83% specificity and 76.5% sensitivity.

CONCLUSION

DCE-MRI can quantitatively differentiate between MT-SIP and SIP. The combination of Ve and Kep yielded an optimal performance for discriminating SIP from its malignant mimics.

ADVANCES IN KNOWLEDGE

DCE-MRI with quantitative and semi-quantitative parameters can provide valuable evidences for quantitatively identifying MT-SIP.

Monoexponential, biexponential and diffusion kurtosis MR imaging models: quantitative biomarkers in the diagnosis of placenta accreta spectrum disorders

BACKGROUND

To investigate the diagnostic value of monoexponential, biexponential, and diffusion kurtosis MR imaging (MRI) in differentiating placenta accreta spectrum (PAS) disorders.

METHODS

A total of 65 patients with PAS disorders and 27 patients with normal placentas undergoing conventional DWI, IVIM, and DKI were retrospectively reviewed. The mean, minimum, and maximum parameters including the apparent diffusion coefficient (ADC) and exponential ADC (eADC) from standard DWI, diffusion kurtosis (MK), and mean diffusion coefficient (MD) from DKI and pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) from IVIM were measured from the volumetric analysis and compared between patients with PAS disorders and patients with normal placentas. Univariate and multivariated logistic regression analyses were used to evaluate the value of the above parameters for differentiating PAS disorders. Receiver operating characteristics (ROC) curve analyses were used to evaluate the diagnostic efficiency of different diffusion parameters for predicting PAS disorders.

RESULTS

Multivariate analysis demonstrated that only D mean and D max differed significantly among all the studied parameters for differentiating PAS disorders when comparisons between accreta lesions in patients with PAS (AP) and whole placentas in patients with normal placentas (WP-normal) were performed (all p < 0.05). For discriminating PAS disorders, a combined use of these two parameters yielded an AUC of 0.93 with sensitivity, specificity, and accuracy of 83.08, 88.89, and 83.70%, respectively.

CONCLUSION

The diagnostic performance of the parameters from accreta lesions was better than that of the whole placenta. D mean and D max were associated with PAS disorders.

Application of Simultaneous 18 F-FDG PET With Monoexponential, Biexponential, and Stretched Exponential Model-Based Diffusion-Weighted MR Imaging in Assessing the Proliferation Status of Lung Adenocarcinoma

BACKGROUND

Ki-67 proliferation index (PI) is important for providing information on tumor behavior, treatment response, and prognosis. Integrated positron emission tomography/magnetic resonance (PET/MR) may have the potential to assess Ki-67 PI in patients with lung adenocarcinoma.

PURPOSE

To explore the value of simultaneous ¹⁸ F-fluorodeoxyglucose (¹⁸ F-FDG) PET/MR-derived parameters in assessing the proliferation status of lung adenocarcinoma and to determine the best combination of parameters.

STUDY TYPE

Prospective.

POPULATION

Seventy-eight patients with lung adenocarcinoma and with Ki-67 PI.

FIELD STRENGTH/SEQUENCE

3.0 T, simultaneous PET/MRI including diffusion-weighted imaging (DWI) and ¹⁸ F-FDG PET.

ASSESSMENT

DWI-derived parameters, namely, apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudo diffusion coefficient (D*), perfusion fraction (f), diffusion heterogeneity index (α), and distributed diffusion coefficient (DDC); and PET-derived parameters, namely, maximum standardized uptake value (SUV_max ), metabolic tumor volume (MTV), and total lesion glycolytic volume (TLG), were calculated and compared between the high (>25%) and low (≤25%) Ki-67 PI groups. The correlations between PET-derived parameters and DWI-derived parameters were analyzed.

STATISTICAL TESTS

Student's t-test, Mann-Whitney U test, chi-square test, and receiver operating characteristic (ROC) curves. A P-value <0.05 was considered statistically significant.

RESULTS

The SUV_max , MTV, TLG, ADC, D, and DDC values were significantly different between the high (N = 35) and low Ki-67 PI groups (N = 43). D, SUV_max , and MTV independently predicted the Ki-67 PI status. The combination of D, SUV_max , and MTV had the largest area under the ROC curve (AUC = 0.900), which was significantly larger than the AUC alone of DDC (AUC = 0.725), SUV_max (AUC = 0.815), MTV (AUC = 0.774), or TLG (AUC = 0.783). The perfusion fraction did not correlate with SUV_max , MTV, or TLG (r = -0.03, -0.11, and -0.04, respectively; P = 0.786, 0.348, and 0.733).

DATA CONCLUSION

The combination of D, SUV_max , and MTV may predict Ki-67 PI status. No correlation was observed between perfusion parameters and metabolic parameters.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY: Stage 2.

Standard diffusion-weighted, intravoxel incoherent motion, and dynamic contrast-enhanced MRI of musculoskeletal tumours: correlations with Ki67 proliferation status

AIM

To determine whether quantitative parameters derived from conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) correlate with the Ki67 proliferation status in musculoskeletal tumours.

MATERIALS AND METHODS

Twenty-eight patients with musculoskeletal tumours diagnosed via surgical specimen histological analysis who underwent standard DWI, IVIM, and DCE were reviewed retrospectively. The mean standard DWI (apparent diffusion coefficient [ADC]), IVIM (pure diffusion coefficient [D], pseudo-diffusion coefficient [D∗] and perfusion fraction [ƒ]), and DCE (volume transfer constant [K^trans], rate constant [K_ep], and extravascular extracellular volume fraction [V_e]) parameters were measured and correlated with the Ki67 index. The Ki67 value was categorised as high (>20%) or low (≤20%).

RESULTS

The ADC and D values correlated negatively with the Ki67 index (r=-0.711∼-0.699, p<0.001), whereas the K^trans and K_ep values correlated positively with the Ki67 index (r=0.389-0.434, p=0.021, 0.041). The ADC and D values were lower (p<0.001), whereas the K^trans and K_ep values were higher (p=0.011, 0.005) in musculoskeletal tumours with a high Ki67 status than in those in a low status. The ADC and D demonstrated the largest area under the receiver-operating characteristic curve (AUC = 0.953), which is statistically bigger than the AUC of K^trans and K_ep (0.784 and 0.802, respectively).

CONCLUSION

ADC, D, K^trans, and K_ep correlate with the Ki67 index. ADC and D are the strongest quantitative parameters for predicting Ki67 status.

Grading of Pediatric Intracranial Tumors: Are Intravoxel Incoherent Motion and Diffusional Kurtosis Imaging Superior to Conventional DWI?

BACKGROUND AND PURPOSE

An accurate evaluation of the World Health Organization grade is critical in pediatric intracranial tumors. Our aim was to explore the correlations between parameters derived from conventional DWI, intravoxel incoherent motion, and diffusional kurtosis imaging with histopathologic features to evaluate the accuracy of diffusion parameters for grading of pediatric intracranial tumors.

MATERIALS AND METHODS

Fifty-four pediatric patients with histologically proved intracranial tumors who underwent conventional DWI, intravoxel incoherent motion, and diffusional kurtosis imaging were recruited. The conventional DWI (ADC), intravoxel incoherent motion (pure diffusion coefficient [D], pseudodiffusion coefficient [D*], perfusion fraction [f], diffusional kurtosis imaging [K], and diffusion coefficient [Dk]) parameters in the solid component of tumors were measured. The cellularity, Ki-67, and microvessel density were measured. These parameters were compared between the low- and high-grade pediatric intracranial tumors using the Mann-Whitney U test. Spearman correlations and receiver operating characteristic analysis were performed.

RESULTS

The ADC, D, and Dk values were lower, whereas the K value was higher in high-grade pediatric intracranial tumors than in low-grade tumors (all, P < .001). The K value showed positive correlations (r = 0.674-0.802; all, P < .05), while ADC, D, and Dk showed negative correlations with cellularity and Ki-67 (r = -0.548 to -0.740; all, P < .05). The areas under the curve of ADC_VOI, D_VOI, Dk_VOI, and K_VOI were 0.901, 0.894, 0.863, and 0.885, respectively, for differentiating high- from low-grade pediatric intracranial tumors. The area under the curve difference in grading pediatric intracranial tumors was not significant (all, P > .05).

CONCLUSIONS

Intravoxel incoherent motion- and diffusional kurtosis imaging-derived parameters have similar performance compared with conventional DWI in predicting pediatric intracranial tumor grade. The diffusion metrics may potentially reflect tumor cellularity and Ki-67 in pediatric intracranial tumors.

Dual-energy CT in predicting Ki-67 expression in laryngeal squamous cell carcinoma

PURPOSE

To investigate whether multiple dual-energy computed tomography (DECT) parameters can noninvasively predict the Ki-67 expression (associated with survival and prognosis) in laryngeal squamous cell carcinoma (LSCC).

METHODS

Eighty-eight patients with histologically proven LSCC were retrospectively reviewed. Multiple DECT-derived parameters were measured and correlated with Ki-67 expression by Spearman correlation analysis. Comparisons of the DECT-derived parameters between tumors with low- and high-level expression of Ki-67 were made with the t-tests.

RESULTS

The iodine concentration (IC), normalized IC (NIC), effective atomic number (Z_eff), 40-80 keV, and slope (k) values were positively correlated with Ki-67 expression (all p < 0.05, rho=0.367-0.548). Among all DECT-derived parameters, NIC value had the highest r value in correlation with Ki-67 expression. The IC, NIC, Z_eff, 40-80 keV, and slope (k) values were significantly higher in LSCC with high Ki-67 expression than in those with low Ki-67 expression (all p < 0.05).

CONCLUSIONS

Multiple DECT-derived parameters (IC, NIC, Z_eff, 40-80 keV, and slope (k)) can be used as predictors of survival and prognosis in LSCC, among which the NIC value is the strongest.

Evaluation of amide proton transfer-weighted imaging for endometrial carcinoma histological features: a comparative study with diffusion kurtosis imaging

OBJECTIVES

To investigate whether amide proton transfer-weighted imaging (APTWI) and diffusion kurtosis imaging (DKI) can be used to evaluate endometrial carcinoma (EC) in terms of clinical type, histological grade, subtype, and Ki-67 index.

METHODS

Eighty-eight patients with EC underwent pelvic DKI and APTWI. The non-Gaussian diffusion coefficient (D_app), apparent kurtosis coefficient (K_app), and magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)) were calculated and compared based on the clinical type (type I, II), histological grade (high- and low-grade), and subtype (endometrioid adenocarcinoma (EA) and non-EA). Correlation coefficients were calculated for each parameter with histological grades and the Ki-67 index.

RESULTS

The MTRasym (3.5 ppm) and K_app values were higher in the type II group and high-grade group than in the type I and low-grade groups, respectively, while the D_app values were lower in the type I and low-grade groups, respectively (all p < 0.05). The K_app value was higher in the EA group than in the non-EA group (p = 0.022). The K_app value was the only independent predictor for the histological grade of EA and the clinical type of EC. The AUC (DKI) was higher than the AUC (APTWI) in the identification of type I and II EC and high- and low-grade EA (Z = 2.042, 2.013, p = 0.041, 0.044), while in the identification of EA and non-EA, only the difference in K_app was statistically significant. Moreover, the K_app and MTRasym (3.5 ppm) values and D_app values correlated positively and negatively, respectively, with histological grade (r = 0.759, 0.555, 0.624, and 0.462, all p < 0.05) and Ki-67 index (r = -0.704, -0.507, all p < 0.05).

CONCLUSION

Both DKI- and APTWI-related parameters have potential as imaging markers in estimating the histological features of EC, while DKI shows better performance than APTWI in this study.

KEY POINTS

• DKI and APTWI can be used to preliminarily evaluate the histological characteristics of endometrial carcinoma (EC). • The K_app was the only independent predictor for the histological grade of EA and the clinical type of EC. • The K_app, MTRasym (3.5 ppm), and D_app correlated positively and negatively, respectively, with histological grade and Ki-67 index.

Three-dimensional pulsed continuous arterial spin labeling and intravoxel incoherent motion imaging of nasopharyngeal carcinoma: correlations with Ki-67 proliferation status

BACKGROUND

Recurrence and distant metastasis are still the main problems affecting the long-term prognosis of nasopharyngeal carcinoma (NPC) patients, and may be related to the Ki-67 proliferation status. We therefore explored the potential correlation between Ki-67 proliferation status in NPC with the parameters derived from two imaging techniques: three-dimensional pulsed continuous arterial spin labeling (3D pCASL) and intravoxel incoherent motion (IVIM).

METHODS

Thirty-six patients with pathologically confirmed NPC were included, and the Ki-67 labeling index (LI) was measured by immunohistochemistry. All patients underwent plain and contrast-enhanced magnetic resonance imaging (MRI), IVIM, and 3D pCASL examination. The mean, maximum, and minimum of blood flow (BF), minimum of apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) parameters were all measured, and Spearman's correlation analysis was performed to evaluate the relationships between these parameters and the Ki-67 LI. According to the Ki-67 values, the patients were divided into two groups: high (>50%) and low (≤50%). The rank-sum test (Mann-Whitney U test) was then used to compare the differences in quantitative parameters between the high and low Ki-67 groups.

RESULTS

Ki-67 LI was positively correlated with BFmean and BFmax (r=0.415 and 0.425). D*mean and D*min did have positive correlation with Ki-67, but this was not significant (P=0.082 and 0.072). BFmax was significantly different between the high and low Ki-67 groups (P=0.028).

CONCLUSIONS

3D pCASL and IVIM are noninvasive functional MR perfusion imaging techniques that can evaluate perfusion information and perfusion parameters. Our study suggests that 3D pCASL is more effective than IVIM for assessing the proliferation status of NPC, which is beneficial for evaluating the prognosis of patients. Furthermore, BFmax is the best biomarker for distinguishing high from low Ki-67 levels.

Evaluation of gliomas peritumoral diffusion and prediction of IDH1 mutation by IVIM-DWI

Glioma characterized by high morbidity and mortality, is one of the most common brain tumors. The application of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) in differentiating glioma grading and IDH1 mutation status were poorly investigated. 78 glioma patients confirmed by pathological and imaging methods were enrolled. Glioma patients were measured using IVIM-DWI, then related parameters such as cerebral blood flow (CBF), perfusion fraction (f), pseudo diffusivity (D*), and true diffusivity (D), were derived. Receiver operating characteristic (ROC) curves were made to calculate specificity and sensitivity. The values of CBF1, CBF3, D*1, rCBF1-2, rCBF3-2, and age in group high-grade gliomas (HGG) were significantly higher than that of in group low-grade gliomas (LGG). The values of CBF1, CBF3, rCBF1-2, rCBF3-2, D*1, and age in group IDH1^mut were significantly lower than that of in group IDH1^wt. The levels of D1 and f1 were remarkably higher in the group IDH1^mut than group IDH1^wt. rCBF1-2 had a remarkably positive correlation with CBF1 (r=0.852, p<0.001). f1 showed a markedly negative correlation with CBF1 (r= -0.306, p=0.007). IVIM-DWI presented efficacy in differentiating glioma grading and IDH1 mutation status.

Value of intravoxel incoherent motion and diffusion kurtosis imaging in predicting peritumoural infiltration of soft-tissue sarcoma: a prospective study based on MRI-histopathology comparisons

AIM

To investigate the performance of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) in the identification of peritumoural infiltration of soft-tissue sarcoma (STS).

MATERIALS AND METHODS

From July 2018 to January 2020, 34 STS patients who underwent 3-T magnetic resonance imaging (MRI), including IVIM and DKI, were reviewed. The standard apparent diffusion coefficient (ADC), true diffusion (D), pseudo-diffusion coefficient (D∗), perfusion fraction (f), mean kurtosis (MK), and mean diffusion (MD) of each lesion were analysed independently by two observers. An MRI-histopathology control method was used to ensure the correspondence of MRI sections with histopathological sections. Differences in STS with and without infiltration were evaluated. The area under the curve (AUC) was used to determine the best cut-off point for different parameters. Interobserver agreement was assessed using the intraclass correlation coefficient.

RESULTS

Standard ADC, D, MK, and MD values reliably distinguished STS that had positive and negative infiltration. The MD value had the best diagnostic performance. Use of an MD cut-off value of 2.35 × 10^-3 mm²/s to distinguish positive and negative infiltration had an AUC of 0.85, accuracy of 88.2%, sensitivity of 94.4%, and specificity of 81.3%. The two independent observers had nearly perfect agreement for all parameters.

CONCLUSION

The standard ADC and D value of IVIM, and the MK and MD values of DKI reliably identify the presence of peritumoural infiltration of STS.

Predictive Ki-67 Proliferation Index of Cervical Squamous Cell Carcinoma Based on IVIM-DWI Combined with Texture Features

Purpose

This study aims to determine whether IVIM-DWI combined with texture features based on preoperative IVIM-DWI could be used to predict the Ki-67 PI, which is a widely used cell proliferation biomarker in CSCC.

Methods

A total of 70 patients were included. Among these patients, 16 patients were divided into the Ki-67 PI <50% group and 54 patients were divided into the Ki-67 PI ≥50% group based on the retrospective surgical evaluation. All patients were examined using a 3.0T MRI unit with one standard protocol, including an IVIM-DWI sequence with 10 b values (0–1,500 sec/mm²). The maximum level of CSCC with a b value of 800 sec/mm² was selected. The parameters (diffusion coefficient (D), microvascular volume fraction (f), and pseudodiffusion coefficient (D^∗)) were calculated with the ADW 4.6 workstation, and the texture features based on IVIM-DWI were measured using GE AK quantitative texture analysis software. The texture features included the first order, GLCM, GLSZM, GLRLM, and wavelet transform features. The differences in IVIM-DWI parameters and texture features between the two groups were compared, and the ROC curve was performed for parameters with group differences, and in combination.

Results

The D value in the Ki-67 PI ≥50% group was lower than that in the Ki-67 PI <50% group (P < 0.05). A total of 1,050 texture features were obtained using AK software. Through univariate logistic regression, mPMR feature selection, and multivariate logistic regression, three texture features were obtained: wavelet_HHL_GLRLM_ LRHGLE, lbp_3D_k_ firstorder_IR, and wavelet_HLH_GLCM_IMC1. The AUC of the prediction model based on the three texture features was 0.816, and the combined D value and three texture features was 0.834.

Conclusions

Texture analysis on IVIM-DWI and its parameters was helpful for predicting Ki-67 PI and may provide a noninvasive method to investigate important imaging biomarkers for CSCC.

A Correlative Study Between IVIM-DWI Parameters and the Expression Levels of Ang-2 and TKT in Hepatocellular Carcinoma

Background

Noninvasive evaluation of the expression of angiopoietin-2 (Ang-2) and transketolase (TKT) in hepatocellular carcinoma (HCC) is of great significance for the clinical development of individualized treatment plans. However, the correlation between intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) and the expression of Ang-2 and TKT has not been reported. We sought to investigate the correlations between IVIM-DWI parameters and Ang-2 and TKT expression levels in HCCs.

Methods

Conventional non-enhanced magnetic resonance imaging (MRI) and IVIM-DWI and dynamic contrast MRI were performed for 61 patients with HCC before surgical treatment. Various IVIM-DWI parameters, such as apparent diffusion coefficient (ADC), slow apparent diffusion coefficient (D), fast apparent diffusion coefficient (D^*) and fraction of fast apparent diffusion coefficient (f), were calculated using Function-MADC software. Expression levels of Ang-2 and TKT in HCC were detected via immunohistochemical staining and classified into two grades. Independent sample t tests were used to compare differences in parameters between the two groups. The Spearman rank correlation test was used to analyze the correlations between IVIM-DWI parameters and Ang-2 and TKT expression levels in HCCs.

Results

The D^* and f values were significantly higher in the high Ang-2 group than in the low Ang-2 group; there were no obvious between-group differences in ADC and D. Ang-2 expression was positively correlated with D* and f but not with ADC and D. The ADC and D values were significantly lower in the high TKT group than in the low TKT group, whereas the between-group differences for D* and f were not significant. TKT expression was negatively correlated with ADC and D but not with D* and f.

Conclusions

IVIM-DWI can be used to evaluate Ang-2 and TKT expression in HCC.

A Noninvasive Assessment of Tumor Proliferation in Lung cancer Patients using Intravoxel Incoherent Motion Magnetic Resonance Imaging

Ki-67 is a nuclear antigen widely used in routine pathologic analyses as a tumor cell proliferation marker for lung cancer. However, Ki-67 expression analyses using immunohistochemistry (IHC) are invasive and frequently influenced by tissue sampling quality. In this study, we assessed the feasibility of noninvasive magnetic resonance imaging (MRI) in predicting the Ki-67 labeling indices (LIs). A total of 51 lung cancer patients, including 42 non-small cell lung cancer (NSCLC) cases and nine small cell lung cancer (SCLC) cases, were enrolled in this study. Quantitative MRI parameters from conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) were obtained, and their correlations with tumor tissue Ki-67 expression were analyzed. We found that the true diffusion coefficient (D value) from IVIM was negatively correlated with Ki-67 expression (Spearman r = -0.76, P < 0.001). The D values in the high Ki-67 group were significantly lower than those in the low Ki-67 group (0.90 ± 0.21 × 10^-3 mm²/s vs. 1.22 ± 0.30 × 10^-3 mm²/s). Among three MRI techniques used, D values from IVIM showed the best performance for distinguishing the high Ki-67 group from low Ki-67 group in receiver operating characteristic (ROC) analysis with an area under the ROC curve (AUROC) of 0.85 (95% CI: 0.73-0.97, P < 0.05). Moreover, D values performed well for differentiating SCLC from NSCLC with an AUROC of 0.82 (95% CI: 0.68-0.90), Youden index of 0.72, and F1 score of 0.81. In conclusion, D values were negatively correlated with Ki-67 expression in lung cancer tissues and can be used to distinguish high from low proliferation statuses, as well as SCLC from NSCLC.

Differential diagnosis of sinonasal extranodal NK/T cell lymphoma and diffuse large B cell lymphoma on MRI

Purpose

To evaluate whether imaging features on conventional magnetic resonance imaging (MRI) can differentiate sinonasal extranodal natural killer/T cell lymphomas (ENKTL) from diffuse large B cell lymphoma (DLBCL).

Methods

Consecutively, pathology-proven 59 patients with ENKTL and 27 patients with DLBCL in the sinonasal region were included in this study. Imaging features included tumor side, location, margin, pre-contrast T1 and T2 signal intensity and homogeneity, post-contrast enhancement degree and homogeneity, septal enhancement pattern, internal necrosis, mass effect, and adjacent involvements. These imaging features for each ENKTL or DLBCL on total 86 MRI scans were indicated independently by two experienced head and neck radiologists. The MRI-based performance in differential diagnosis of the two types of lymphomas was evaluated by multivariate logistic regression analysis.

Results

All ENKTLs were located in the nasal cavity, with ill-defined margin, heterogeneous signal intensity, internal necrosis, marked enhancement of solid component on MRI, whereas DLBCLs were more often located in the paranasal sinuses, with MR homogenous intensity, mild enhancement, septal enhancement pattern, and intracranial or orbital involvements (all P < 0.05). Using a combination of location, internal necrosis and septal enhancement pattern of the tumor in multivariate logistic regression analysis, sensitivity, specificity, and accuracy in differential diagnosis of ENKTL and DLBCL were 100%, 79.4%, and 91.9%, respectively, for radiologist 1, and were 98.3%, 81.5%, and 93.0%, respectively, for radiologist 2.

Conclusion

MRI can effectively differentiate ENKTL from DLBCL in the sinonasal region with a high diagnostic accuracy.

Diffusion Kurtosis Imaging and Intravoxel Incoherent Motion in Differentiating Nasal Malignancies

OBJECTIVES/HYPOTHESIS

To evaluate the usefulness of diffusion kurtosis imaging (DKI) and intravoxel incoherent motion (IVIM) in the differentiation of sinonasal malignant tumors (SNMTs) with different histological types.

STUDY DESIGN

Retrospective observational and diagnostic study.

METHODS

Sixty-five patients with SNMTs who underwent DKI and IVIM were enrolled in this retrospective study, including 27 squamous cell carcinomas (SCCs), 13 olfactory neuroblastomas (ONBs), 14 malignant melanomas (MMs) and 11 lymphomas. The kurtosis (K) and diffusion coefficient (Dk) from DKI and the pure diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), and the product of D* and f (f∙D*) from IVIM were measured. Kruskal-Wallis and Dunn multiple comparison tests with Bonferroni correction, receiver operating characteristic curve, and logistic regression analyses were used for statistical analysis.

RESULTS

Lymphomas demonstrated the highest K values but lowest Dk, D, D*, f, and f∙D* values among these four malignant tumors. ONBs exhibited high K values and MMs had highest D*, f, and f∙D* values. The cutoff value of ≤0.887 × 10^-3 mm² /sec for f∙D* provided a sensitivity, specificity, and an accuracy of 100%, 98.1%, and 98.5%, respectively, for differentiating lymphomas from the other three entities. The combination of f∙D* and D values showed a sensitivity of 92.9% and a specificity of 92.5% for the discrimination of MMs from ONBs and SCCs. The K value was useful for differentiating ONBs from SCCs, with a threshold value of 0.942 (sensitivity, 84.6%; specificity, 63.0%).

CONCLUSIONS

The combined use of DKI and IVIM is helpful for differentiating among four histological types of SNMTs.

LEVEL OF EVIDENCE

3 Laryngoscope, 2019.

Correlation of apparent diffusion coefficient and intravoxel incoherent motion imaging parameters with Ki-67 expression in extrahepatic cholangiocarcinoma

PURPOSE

To investigate the correlation of magnetic resonance imaging (MRI), apparent diffusion coefficient (ADC) and intravoxel incoherent motion imaging parameters with Ki-67 expression in cholangiocarcinoma.

METHODS

A total of 42 extrahepatic cholangiocarcinoma (EHCC) cases confirmed by surgical pathology were analyzed retrospectively. Subjects underwent MRI at 3.0 T and intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) sequential scanning prior to surgery, and postoperative Ki-67 expression was recorded by immunohistochemistry (IHC). The patients were divided into 4 groups (I-IV) based on increasing Ki-67 expression from - to +++. ADC values and IVIM-DWI parameters were calculated, including true diffusion coefficient (D), perfusion fraction (f), and pseudo-diffusion coefficient (D*). The comparison among groups was analyzed by univariate ANOVA (normal distribution) or Kruskal-Wallis H (non-normal distribution). Spearman correlation analysis was used to analyze the correlation of each parameter with Ki-67 expression. The diagnostic efficiency of each parameter was compared using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

RESULTS

Except for D*, other values had statistically significant differences between groups (P < 0.05). ADC, D and f values had negative correlations with Ki-67 expression (r values were -0.607, -0.795, -0.531, respectively, P < 0.05). The AUCs were 0.701, 0.880, 0.623, respectively (P < 0.0001).

CONCLUSION

IVIM-DWI technology can reflect the proliferative activity of EHCC cells to a certain extent, and has clinical value for predicting the degree of malignancy of a tumor.

Apparent diffusion coefficient (ADC) histogram analysis: differentiation of benign from malignant parotid gland tumors using readout-segmented diffusion-weighted imaging

OBJECTIVES

To explore the utility of whole-lesion apparent diffusion coefficient (ADC) histogram analysis for differentiating parotid gland tumors following readout-segmented diffusion-weighted imaging (RESOLVE).

METHODS

80 patients (40 with pleomorphic adenomas, 14 with Warthin tumors, and 26 with malignant parotid gland tumors) who underwent routine head-and-neck MRI and RESOLVE examinations, were retrospectively evaluated. RESOLVE data were acquired from a MAGNETOM Skyra 3T MR system. Eleven whole-lesion histogram parameters derived from histogram analysis (ADC_mean, ADC_minimum, ADC_maximum, ADC_1th, ADC_10th, ADC_50th, ADC_90th, ADC_99th, skewness, variance and kurtosis) were calculated for each patient using MaZda. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of the ADC for distinguishing among the three groups.

RESULTS

In total, nine parameters (ADC_minimum, ADC_maximum, ADC_mean, ADC_10th, ADC_50th, ADC_90th, ADC_99th, variance, skewness) were statistically significant (all p < 0.05) for all three groups, in the comparison of pleomorphic adenomas to Warthin tumors; the ADC_mean, ADC_50th, and skewness revealed high diagnostic efficiency with areas under the receiver operating characteristic curve of 0.976, 0.970, and 0.970, respectively. In the comparison of pleomorphic adenomas to malignant parotid gland tumors, these nine parameters were also found to be statistically different (all p < 0.05); the ADC_mean, ADC_10th and ADC_50th revealed high diagnostic efficiency with area under the curve of 0.851, 0.866, and 0.841, respectively. However, in the comparison of Warthin tumors to malignant parotid gland tumors, only three parameters (ADC_mean, ADC_50th, skewness) were statistically significant (all p < 0.05).

CONCLUSIONS

Whole-lesion ADC histograms are effective in differentiating common parotid gland tumors.

Whole-tumor histogram analysis of monoexponential and advanced diffusion-weighted imaging for sinonasal malignant tumors: Correlations with histopathologic features

BACKGROUND

The histopathological basis of monoexponential diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) in the characterization of sinonasal malignant tumors is still unclear.

PURPOSE

To explore the correlations of histogram metrics from monoexponential DWI, IVIM, and DKI with histopathologic features in sinonasal malignant tumors.

STUDY TYPE

Retrospective.

SUBJECTS

In all, 76 patients with sinonasal malignant tumors.

FIELD STRENGTH/SEQUENCE

Fourteen different b values (b = 0, 50, 100, 150, 200, 250, 300, 350, 400, 800, 1000, 1500, 2000, and 2500 sec/mm² ) were used to perform different DWI models at 3.0T.

ASSESSMENT

The whole-tumor histogram metrics were calculated on the apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), diffusion kurtosis (K), and diffusion coefficient (Dk) maps. Histopathologic features, including nuclear, cytoplasmic, cellular, stromal fractions, and the nuclear-to-cytoplasmic (N/C) ratio, were measured.

STATISTICAL TESTS

Spearman correlations and stepwise multiple linear regression analyses were performed to determine the correlations between histogram metrics and histopathologic features.

RESULTS

ADC, Dk, and f histogram metrics showed significant correlations with investigated histopathologic features; D and K histogram metrics were significantly correlated with cellular, stromal, and nuclear fractions (all P < 0.05). Significant correlations between the 75th percentile of D and cytoplasmic fraction and between the kurtosis of K and the N/C ratio were observed (P < 0.05). The skewness of Dk, K, and the 75th percentile of D were independently associated with cellular and nuclear fractions; the skewness of Dk and K were independently associated with stromal fraction (P < 0.05).

DATA CONCLUSION

Monoexponential and advanced DWI histogram parameters were significantly correlated with histopathologic features in sinonasal malignancies.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:273-285.

Differentiating between malignant and benign renal tumors: do IVIM and diffusion kurtosis imaging perform better than DWI?

OBJECTIVE

To quantitatively compare the diagnostic values of conventional diffusion-weighted imaging (DWI), intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI) in differentiating between malignant and benign renal tumors.

METHODS

Multiple b value DWIs and DKIs were performed in 180 patients with renal tumors, which were divided into clear cell renal cell carcinoma (ccRCC), non-ccRCC, and benign renal tumor group. The apparent diffusion coefficient (ADC), true diffusivity (D), pseudo-diffusion coefficient (D*), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) maps were calculated. The diagnostic efficacy of various diffusion parameters for predicting malignant renal tumors was compared.

RESULTS

The ADC, D, and MD values of ccRCCs were higher, while D*, f, and MK values were lower than those of benign renal tumors (all p < 0.025). The D* and f values of non-ccRCCs were lower than those of benign renal tumors (p = 0.002 and p < 0.001, respectively). The difference of ADC, D, MD, and MK values between non-ccRCCs and benign renal tumors was not statistically significant (p > 0.05). The ADC, D, MD, and f values of ccRCCs were higher, while MK values were lower than those of non-ccRCCs (all p < 0.001). The AUC values of ADC, D, D*, f, MK, and MD were 0.849, 0.891, 0.708, 0.656, 0.862, and 0.838 for differentiating ccRCCs from benign renal tumors, respectively. The AUC values of D* and f were 0.772 and 0.866 for discrimination between non-ccRCCs and benign renal tumors, respectively.

CONCLUSION

IVIM parameters are the best, while DWI and DKI parameters have similar performance in differentiating malignant and benign renal tumors.

KEY POINTS

• The D value is the best parameter for differentiating ccRCC from benign renal tumors. • The f value is the best parameter for differentiating non-ccRCC from benign renal tumors. • Conventional DWI and DKI have similar performance in differentiating malignant and benign renal tumors.

Inhibition of MALAT1 reduces tumor growth and metastasis and promotes drug sensitivity in colorectal cancer

Human metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) is a long non-coding RNA known to be highly expressed in several tumors. In colorectal cancer (CRC), MALAT1 promotes cell proliferation, metastasis, and invasion in vitro and in vivo. This study aimed to investigate the effect of MALAT1 on the proliferation, migration, and drug sensitivity of CRC cells in vitro and in vivo and the mechanisms involved therein. We observed increased expression of MALAT1 in six CRC cell lines compared to that in normal cells, suggesting its involvement in CRC progression. Downregulation of MALAT1 inhibited cell migration and induced apoptosis in vitro and inhibited tumor growth and metastasis in nude mice. Furthermore, MALAT1 silencing downregulated the expression of ATP-binding cassette transporters (ABC), breast cancer resistance protein (BCRP), and multi-drug resistance proteins including MDR1 and MRP1, resulting in decreased resistance of cancer cells to 5-FU. In addition, the metastasis and invasion of HCT-116 and HCT-116/5-FU cells were regulated via targeting miR-20b-5p. Based on these observations, we infer that inhibition of MALAT1 suppressed CRC progression and metastasis and improved the sensitivity of cancer cells to 5-FU. The present study proposes a new direction to investigate the molecular mechanisms underlying the invasion and metastasis of CRC, whereby the interaction between MALAT1 and miR-20b-5p could be a novel therapeutic target for CRC.

Intravoxel incoherent motion MRI for differentiating sinonasal small round cell malignant tumours (SRCMTs) from Non-SRCMTs: comparison and correlation with dynamic contrast-enhanced MRI

AIM

To investigate the value of intravoxel incoherent motion (IVIM) in the differentiation of sinonasal small round cell malignant tumours (SRCMTs) from non-SRCMTs and to compare and correlate these results with those of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Ninety patients with histologically confirmed sinonasal malignant tumours (53 SRCMTs and 37 non-SRCMTs) who underwent conventional MRI, IVIM, and DCE-MRI before treatment were enrolled. The IVIM and DCE-MRI parameters were measured. Statistical analyses were performed using Student's t-tests, receiver operating characteristic (ROC) curve analyses, and Spearman's correlation coefficients.

RESULTS

A lower pure diffusion coefficient (D) value and a higher pseudo-diffusion coefficient (D*) value were found in the sinonasal SRCMTs than in the non-SRCMTs (p<0.001 and p=0.011, respectively). Moreover, the mean extravascular extracellular space volume ratio (V_e) of the SRCMTs was significantly lower than that of the non-SRCMTs (p=0.020). ROC curve analysis showed that the diagnostic performance of D outperformed those of the other perfusion and diffusion parameters. A cut-off D value of 0.56 ×10^-3 mm²/s yielded a sensitivity of 80.4%, a specificity of 75%, and an accuracy of 78.2%, with an AUC of 0.825. Significant but poor-to-fair correlations were found between the parameters from IVIM and DCE-MRI.

CONCLUSIONS

The D and D* values of IVIM and the V_e value of DCE-MRI are helpful in distinguishing sinonasal SRCMTs from non-SRCMTs, with the D values having the best diagnostic efficiency.