Intravoxel incoherent motion magnetic resonance imaging for differentiating metastatic and non-metastatic lymph nodes in pancreatic ductal adenocarcinoma

A machine learning model based on preoperative multiparametric quantitative DWI can effectively predict the survival and recurrence risk of pancreatic ductal adenocarcinoma

PURPOSE

To develop a machine learning (ML) model combining preoperative multiparametric diffusion-weighted imaging (DWI) and clinical features to better predict overall survival (OS) and recurrence-free survival (RFS) following radical surgery for pancreatic ductal adenocarcinoma (PDAC).

MATERIALS AND METHODS

A retrospective analysis was conducted on 234 PDAC patients who underwent radical resection at two centers. Among 101 ML models tested for predicting postoperative OS and RFS, the best-performing model was identified based on comprehensive evaluation metrics, including C-index, Brier scores, AUC curves, clinical decision curves, and calibration curves. This model's risk stratification capability was further validated using Kaplan-Meier survival analysis.

RESULTS

The random survival forest model achieved the highest C-index (0.828/0.723 for OS and 0.781/0.747 for RFS in training/validation cohorts). Incorporating nine key factors-D value, T-stage, ADC-value, postoperative 7th day CA19-9 level, AJCC stage, tumor differentiation, type of operation, tumor location, and age-optimized the model's predictive accuracy. The model had integrated Brier score below 0.13 and C/D AUC values above 0.85 for both OS and RFS predictions. It also outperformed traditional models in predictive ability and clinical benefit, as shown by clinical decision curves. Calibration curves confirmed good predictive consistency. Using cut-off scores of 16.73/29.05 for OS/RFS, Kaplan-Meier analysis revealed significant prognostic differences between risk groups (p < 0.0001), highlighting the model's robust risk prediction and stratification capabilities.

CONCLUSION

The random survival forest model, combining DWI and clinical features, accurately predicts survival and recurrence risk after radical resection of PDAC and effectively stratifies risk to guide clinical treatment.

CRITICAL RELEVANCE STATEMENT

The construction of 101 ML models based on multiparametric quantitative DWI combined with clinical variables has enhanced the prediction performance for survival and recurrence risks in patients undergoing radical resection for PDAC.

KEY POINTS

This study first develops DWI-based radiological-clinical ML models predicting PDAC prognosis. Among 101 models, RFS is the best and outperforms other traditional models. Multiparametric DWI is the key prognostic predictor, with model interpretations through SurvSHAP.

Multiparametric quantitative diffusion weighted magnetic resonance imaging can effectively predict the response to neoadjuvant therapy in borderline resectable pancreatic ductal adenocarcinoma

PURPOSE

To investigate whether multiparametric quantitative diffusion weighted magnetic resonance imaging (DWI) can effectively predict the neoadjuvant therapy (NAT) response in borderline resectable pancreatic ductal adenocarcinoma (BRPC).

METHODS

The clinicopathological data, including tumor size, location, and CA19-9 values, as well as DWI parameters(ADC, D, and f values) from 72 patients with BRPC, were analyzed. The differences and changes in these factors before and after NAT were compared to identify those most accurately reflect the response to NAT. ROC analysis was used to evaluate the diagnostic efficacy, and Kaplan-Meier survival analysis explored the relationship between DWI parameters and prognosis. Subgroup survival analysis to further identify populations potentially benefiting from NAT based on multiparametric DWI.

RESULTS

After-NAT, the response group showed significantly higher ADC and D values and lower f values compared to the non-response group. The ΔADC (OR: 12.24, P = 0.013) emerged as the most important independent factor for tumor response, demonstrating the highest diagnostic accuracy for NAT response with an AUC of 0.936. Kaplan-Meier showed the high ADC value group, high D value group and low f value group were associated with better prognosis after NAT; and the ΔADC ≥ 0 group, ΔD ≥ 0 group, and Δf < 0 group was significantly associated with better prognosis. In addition, subgroup analysis suggested two groups of patients might potentially benefit from NAT.

CONCLUSIONS

Multiparametric quantitative DWI may offer valuable insights into the efficacy and prognosis of NAT in BRPC. These findings have the potential to support the evaluation and decision-making process for patients undergoing NAT.

Diffusion-weighted imaging based on intravoxel incoherent motion: correlation with molecular prognostic factors and subtypes in breast cancer

BACKGROUND

Intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI), which indicates biological tissue attributes, may be applied to accurately assess breast tumors.

PURPOSE

To analyze the IVIM parameters of different molecular prognostic factors and subtypes to find out whether there are any connections.

MATERIAL AND METHODS

A total of 181 patients enrolled in this retrospective study had preoperative magnetic resonance imaging (MRI) examinations, and pathologies were verified as breast cancers. Regions of interest were placed at all slices of the parameter maps (D, tissue diffusivity; ADC, apparent diffusion coefficient; f, perfusion fraction; and D*, pseudo-diffusivity maps) of IVIM and generated parameter values to be used for comparative analysis among molecular prognostic factors and subtypes.

RESULTS

D and ADC were greater in estrogen receptor (ER)-negative, human epidermal growth factor receptor 2 (HER2)-positive, and Ki67-low expression groups (all P values < 0.05). The progesterone receptor (PR)-negative group had a higher D value (P < 0.05). f was larger in the lymph node metastasis-negative group and the PR-positive group (P = 0.012 and 0.046, respectively). Among breast cancer subtypes, D and ADC were different between the HER2-overexpression and the Luminal B (HER2-negative) subtypes (P = 0.019 and 0.028, respectively). The difference in D between the luminal and non-luminal subtypes was statistically significant (P = 0.008). The triple-negative subtype significantly differs from the other subtypes in D* and f (P = 0.012 and 0.016, respectively).

CONCLUSION

IVIM-related metrics exhibited relationships with breast cancer molecular prognosis factors and subtypes.

Evaluating Mediastinal Lymph Node Metastasis of Non-Small Cell Lung Cancer Using Mono-exponential, Bi-exponential, and Stretched-exponential Models of Diffusion-weighted Imaging

PURPOSE

To explore and compare the diagnostic values of mono-exponential, bi-exponential, and stretched-exponential diffusion-weighted imaging (DWI) parameters of primary lesions and lymph nodes (LNs) to predict mediastinal LN metastasis in patients with non-small cell lung cancer.

PATIENTS AND METHODS

Sixty-one patients with non-small cell lung cancer underwent preoperative magnetic resonance imaging, including multiple b -value DWI. The DWI parameters, including apparent diffusion coefficient (ADC) from a mono-exponential model, true diffusion (D) coefficient, pseudo-diffusion (D*) coefficient, and perfusion fraction (f) from a bi-exponential model, distributed diffusion coefficient (DDC) and intravoxel diffusion heterogeneity index (α) from a stretched-exponential model of primary tumors and LNs and the size characteristics of LNs, were measured and compared. Multivariate logistic regression analysis was used to establish models for predicting mediastinal LN metastasis. Receiver operating characteristic analysis was applied to evaluate diagnostic performances.

RESULTS

The DWI parameters of primary tumors showed no statistical significance between LN metastasis-positive and LN metastasis-negative groups. Nonmetastatic LNs had significantly higher ADC, D, DDC, and α values compared with metastatic LNs (all P < 0.05). The short-dimension, long-dimension, and short-long dimension ratio of metastatic LNs was significantly larger than those of nonmetastatic ones (all P < 0.05). The D value showed the best diagnostic performance among all DWI-derived single parameters, and the short dimension of LNs performed the same among all the size variables. Furthermore, the combination of DWI parameters (ADC and D) and the short dimension of LNs can significantly improve diagnostic efficiency.

CONCLUSIONS

The ADC, D, DDC, and α from the mono-exponential, bi-exponential, and stretched-exponential models were demonstrated efficient in differentiating benign from metastatic LNs, and the combination of ADC, D, and short dimension of LNs may have a better diagnostic performance than DWI or size-derived parameters either in combination or individually.

Intravoxel incoherent motion diffusion-weighted imaging in evaluating preoperative staging of esophageal squamous cell carcinoma : Evaluation of preoperative stage of primary tumour and prediction of lymph node metastases from esophageal cancer using IVIM: a prospective study

BACKGROUND

The aim of this research is to prospectively investigate the diagnostic performance of intravoxel incoherent motion (IVIM) using the integrated slice-specific dynamic shimming (iShim) technique in staging primary esophageal squamous cell carcinoma (ESCC) and predicting presence of lymph node metastases from ESCC.

METHODS

Sixty-three patients with ESCC were prospectively enrolled from April 2016 to April 2019. MR and IVIM using iShim technique (b = 0, 25, 50, 75, 100, 200, 400, 600, 800 s/mm2) were performed on 3.0T MRI system before operation. Primary tumour apparent diffusion coefficient (ADC) and IVIM parameters, including true diffusion coefficient (D), pseudodiffusion coefficient (D*), pseudodiffusion fraction (f) were measured by two independent radiologists. The differences in D, D*, f and ADC values of different T and N stages were assessed. Intraclass correlation coefficients (ICCs) were calculated to evaluate the interobserver agreement between two readers. The diagnostic performances of D, D*, f and ADC values in primary tumour staging and prediction of lymph node metastasis of ESCC were determined using receiver operating characteristic (ROC) curve analysis.

RESULTS

The inter-observer consensus was excellent for IVIM parameters and ADC (D: ICC = 0.922; D*: ICC = 0.892; f: ICC = 0.948; ADC: ICC = 0.958). The ADC, D, D* and f values of group T1 + T2 were significantly higher than those of group T3 + T4a [ADC: (2.55 ± 0.43) ×10- 3 mm2/s vs. (2.27 ± 0.40) ×10- 3 mm2/s, t = 2.670, P = 0.010; D: (1.82 ± 0.39) ×10- 3 mm2/s vs. (1.53 ± 0.33) ×10- 3 mm2/s, t = 3.189, P = 0.002; D*: 46.45 (30.30,55.53) ×10- 3 mm2/s vs. 32.30 (18.60,40.95) ×10- 3 mm2/s, z=-2.408, P = 0.016; f: 0.45 ± 0.12 vs. 0.37 ± 0.12, t = 2.538, P = 0.014]. The ADC, D and f values of the lymph nodes-positive (N+) group were significantly lower than those of lymph nodes-negative (N0) group [ADC: (2.10 ± 0.33) ×10- 3 mm2/s vs. (2.55 ± 0.40) ×10- 3 mm2/s, t=-4.564, P < 0.001; D: (1.44 ± 0.30) ×10- 3 mm2/s vs. (1.78 ± 0.37) ×10- 3 mm2/s, t=-3.726, P < 0.001; f: 0.32 ± 0.10 vs. 0.45 ± 0.11, t=-4.524, P < 0.001]. The combination of D, D* and f yielded the highest area under the curve (AUC) (0.814) in distinguishing group T1 + T2 from group T3 + T4a. D combined with f provided the highest diagnostic performance (AUC = 0.849) in identifying group N + and group N0 of ESCC.

CONCLUSIONS

IVIM may be used as an effective functional imaging technique to evaluate preoperative stage of primary tumour and predict presence of lymph node metastases from ESCC.

Establishment of a multi-parameters MRI model for predicting small lymph nodes metastases (<10 mm) in patients with resected pancreatic ductal adenocarcinoma

PURPOSE

To evaluate the potential role of MR findings and DWI parameters in predicting small regional lymph nodes metastases (with short-axis diameter < 10 mm) in pancreatic ductal adenocarcinomas (PDACs).

METHODS

A total of 127 patients, 82 in training group and 45 in testing group, with histopathologically diagnosed PDACs who underwent pancreatectomy were retrospectively analyzed. PDACs were divided into two groups of positive and negative lymph node metastases (LNM) based on the pathological results. Pancreatic cancer characteristics, short axis of largest lymph node, and DWI parameters of PDACs were evaluated.

RESULTS

Univariate and multivariate analyses showed that extrapancreatic distance of tumor invasion, short-axis diameter of the largest lymph node, and mean diffusivity of tumor were independently associated with small LNM in patients with PDACs. The combining MRI diagnostic model yielded AUCs of 0.836 and 0.873, and accuracies of 81.7% and 80% in the training and testing groups. The AUC of the MRI model for predicting LNM was higher than that of subjective MRI diagnosis in the training group (rater 1, P = 0.01; rater 2, 0.008) and in a testing group (rater 1, P = 0.036; rater 2, 0.024). Comparing the subjective diagnosis, the error rate of the MRI model was decreased. The defined LNM-positive group by the MRI model showed significantly inferior overall survival compared to the negative group (P = 0.006).

CONCLUSIONS

The MRI model showed excellent performance for individualized and noninvasive prediction of small regional LNM in PDACs. It may be used to identify PDACs with small LNM and contribute to determining an appropriate treatment strategy for PDACs.

Preoperative Multiparametric Quantitative Magnetic Resonance Imaging Correlates with Prognosis and Recurrence Patterns in Pancreatic Ductal Adenocarcinoma

Simple Summary

Magnetic resonance imaging (MRI) has been considered a noninvasive prognostic biomarker in some cancers; however, the correlation with pancreatic ductal adenocarcinoma (PDAC) remains inconclusive. The aim of our study was to identify quantitative MRI parameters associated with prognosis and recurrence patterns. In an analysis of data from the 136 patients ultimately included in this study, we found that the value of the pure diffusion coefficient D in intravoxel incoherent MRI is an independent risk factor for overall survival (OS) and recurrence-free survival (RFS), while a low value of D is significantly associated with a higher risk of local recurrence. All the patients have been operated on with histopathology for further evaluation. Based on the results of our research, we believe that it is possible in clinical practice to stratify patients based on quantitative MRI data in order to guide treatment strategies, reduce the risk of local tumor recurrence, and improve patients’ prognosis.

Abstract

Magnetic resonance imaging (MRI) has been shown to be associated with prognosis in some tumors; however, the correlation in pancreatic ductal adenocarcinoma (PDAC) remains inconclusive. In this retrospective study, we ultimately included 136 patients and analyzed quantitative MRI parameters that are associated with prognosis and recurrence patterns in PDAC using survival analysis and competing risks models; all the patients have been operated on with histopathology and immunohistochemical staining for further evaluation. In intravoxel incoherent motion diffusion-weighted imaging (DWI), we found that pure-diffusion coefficient D value was an independent risk factor for overall survival (OS) (HR: 1.696, 95% CI: 1.003–2.869, p = 0.049) and recurrence-free survival (RFS) (HR: 2.066, 95% CI: 1.252–3.409, p = 0.005). A low D value (≤1.08 × 10⁻³ mm²/s) was significantly associated with a higher risk of local recurrence (SHR: 5.905, 95% CI: 2.107–16.458, p = 0.001). Subgroup analysis revealed that patients with high D and f values had significantly better outcomes with adjuvant chemotherapy. Distant recurrence patients in the high-D value group who received chemotherapy may significantly improve their OS and RFS. It was found that preoperative multiparametric quantitative MRI correlates with prognosis and recurrence patterns in PDAC. Diffusion coefficient D value can be used as a noninvasive biomarker for predicting prognosis and recurrence patterns in PDAC.

Feasibility of Predicting Pelvic Lymph Node Metastasis Based on IVIM-DWI and Texture Parameters of the Primary Lesion and Lymph Nodes in Patients with Cervical Cancer

RATIONALE AND OBJECTIVES

To investigate the feasibility and value of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) and texture parameters of primary lesions and lymph nodes for predicting pelvic lymph node metastasis in patients with cervical cancer.

MATERIALS AND METHODS

A total of 143 patients with cervical cancer confirmed by surgical pathology were analyzed retrospectively and 125 patients were enrolled in primary lesions study, 83 patients and 134 lymph nodes were enrolled in lymph nodes study. Patients and lymph nodes were randomly divided into training group and test group at a ratio of 2: 1. The IVIM-DWI parameters and 3D texture features of primary lesions and lymph nodes of all patients were measured. The least absolute shrinkage and selection operator algorithm, spearman's correlation analysis, independent two-sample t-test and Mann-Whitney U-test were used to select texture parameters. Multivariate Logistic regression analysis and receiver operating characteristic curves were used to model and evaluate diagnostic performances.

RESULTS

In primary lesions study, model 1 was constructed by combining f value, original_shape_Sphericity and original_firstorder_Mean of primary lesions. In lymph nodes study, model 2 was constructed by combining short diameter, circular enhancement and rough margin of lymph nodes. Model 3 was constructed by combining ADC, f value and original_glszm_Small Area Emphasis of lymph nodes. The areas under curve of model 1, 2 and 3 in training group and test group were 0.882, 0.798, 0.907 and 0.862, 0.771, 0.937 respectively.

CONCLUSION

Models based on IVIM-DWI and texture parameters of primary lesions and lymph nodes both performed well in diagnosing pelvic lymph node metastasis of cervical cancer and were superior to morphological features of lymph nodes. Especially, parameters of lymph nodes showed higher diagnostic efficiency and clinical significance.

Diagnostic performance of T2-weighted imaging and intravoxel incoherent motion diffusion-weighted MRI for predicting metastatic axillary lymph nodes in T1 and T2 stage breast cancer

BACKGROUND

Non-invasive modalities for assessing axillary lymph node (ALN) are needed in clinical practice.

PURPOSE

To investigate the suspicious ALN on unenhanced T2-weighted (T2W) imaging and intravoxel incoherent motion diffusion-weighted imaging (IVIM DWI) for predicting ALN metastases (ALNM) in patients with T1-T2 stage breast cancer and clinically negative ALN.

MATERIAL AND METHODS

Two radiologists identified the most suspicious ALN or the largest ALN in negative axilla by T2W imaging features, including short axis (Size-S), long axis (Size-L)/S ratio, fatty hilum, margin, and signal intensity on T2W imaging. The IVIM parameters of these selected ALNs were also obtained. The Mann-Whitney U test or t-test was used to compare the metastatic and non-metastatic ALN groups. Finally, logistic regression analysis with T2W imaging and IVIM features for predicting ALNM was conducted.

RESULTS

This study included 49 patients with metastatic ALNs and 50 patients with non-metastatic ALNs. Using the above conventional features on T2W imaging, the sensitivity and specificity in predicting ALNM were not high. Compared with non-metastatic ALNs, metastatic ALNs had lower pseudo-diffusion coefficient (D*) (P = 0.043). Logistic regression analysis showed that the most useful features for predicting ALNM were signal intensity and D*. The sensitivity and specificity predicting ALNM that satisfied abnormal signal intensity and lower D* were 73.5% and 84%, respectively.

CONCLUSIONS

The abnormal signal intensity on T2W imaging and one IVIM feature (D*) were significantly associated with ALNM, with sensitivity of 73.5% and specificity of 84%.

Differential detection of metastatic and inflammatory lymph nodes using inflow-based vascular-space-occupancy (iVASO) MR imaging

PURPOSE

To investigate the potential value of inflow-based vascular-space-occupancy (iVASO) MR imaging in differentiating metastatic from inflammatory lymph nodes (LNs).

METHODS

Ten female New Zealand rabbits with 2.5-3.0 kg body weight were studied. VX2 cells and egg yolk emulsion were inoculated into left and right thighs, respectively, to induce ten metastatic and ten inflammatory popliteal LNs. Conventional MRI and iVASO were performed 2 h prior to, and 10, 20 days after inoculation (D0, D10, D20). The short-axis diameter (S), short- to long-axis diameter ratio (SLR), and arteriolar blood volume (BVa) at each time point and their longitudinal changes of each model were recorded and compared. At D20, all rabbits were sacrificed to perform histological evaluation after the MR scan.

RESULTS

The mean values of S, SLR and BVa showed no significant difference between the two groups at D0 (P = 0.987, P = 0.778, P = 0.975). The BVa of the metastatic group was greater than that of the inflammatory at both D10 and D20 (P < 0.05; P < 0.001), whereas the S and SLR of the metastatic group were greater only at D20 (P < 0.001; P = 0.001). Longitudinal analyses showed that the BVa of the metastatic group increased at both D10 and D20 (P = 0.004; P = 0.001), while that of the inflammatory group only increased at D10 (P = 0.024).

CONCLUSION

The BVa measured with iVASO has the potential to detect early metastatic LNs.

Predictors of early recurrence following neoadjuvant chemotherapy and surgical resection for localized pancreatic adenocarcinoma

BACKGROUND AND OBJECTIVES

Neoadjuvant chemotherapy (NAT) for pancreatic adenocarcinoma (PDAC) is increasingly being utilized. However, a significant number of patients will experience early recurrence, possibly negating the benefit of surgery. We aimed to identify factors implicated in early disease recurrence.

METHODS

A retrospective review of pancreaticoduodenectomies performed between 2005 and 2017 at our institution for PDAC following NAT was performed. A 6-month cut-off was used to stratify patients into early/late recurrence groups. Multivariate analysis was performed to identify predictors of recurrence.

RESULTS

Of 273 patients, 64 (23%) developed early recurrence or died within 90 days of surgery. The median time to recurrence was 4 months (95% confidence interval [CI]: 2.2-4.3) in the early group versus 16 months (95% CI: 13.7-19.9) in the late group. The former had higher baseline and post-NAT Ca19-9 levels than the latter (472 vs. 153 IU/ml, p = 0.001 and 71 vs. 39 IU/ml, p = 0.005, respectively). A higher positive lymph node ratio significantly increased the risk of early recurrence (hazard ratio [HR]: 15.9, p < 0.001) while adjuvant chemotherapy was protective (HR: 0.4, p < 0.001).

CONCLUSION

Our findings acknowledge the limitations of clinically measured factors used to ascertain response to NAT and underline the need for individualized molecular markers that take into consideration the specific tumor biology.

Is the level of diffusion restriction in celiac and cervico-thoracic sympathetic ganglia helpful in their proper recognition on PSMA ligand PET/MR?

AIM

 To check if diffusion weighted imaging (DWI) might be helpful in proper recognition of celiac (CG) and cervicothoracic (CTG) sympathetic ganglia on the whole-body multimodal PSMA-ligand PET/MR imaging, in the view of their common misleading avidity on PET potentially suggestive of malignant lesions, including metastatic lymph nodes.

METHODS

 The thickness and the level of diffusion restriction was assessed qualitatively and quantitatively in 406 sympathetic ganglia (189 CTG in 101 males and 217 CG in 116 males) on DWI maps (b-value 0 and 800 s/mm2) and apparent diffusion coefficient (ADC) maps (mean ADC) of the whole-body PET/MR 68Ga-PSMA-11 PET/MR. To form a reference group of a matching ganglia size, the smallest lymph node was chosen from each patient with metastases and underwent the same procedure.

RESULTS

 Very low and low level of diffusion restriction was noted in the majority of sympathetic ganglia (81.0 % CTG, 67.3 % CG, and 73.6 % of all). In the majority (91.7 %) of metastatic lymph nodes the level of diffusion restriction was moderate to high.The mean ADC values in sympathetic ganglia were statistically significantly higher in CTG, CG and all ganglia than in metastatic lymph nodes (p < 0.001; the effect size was large).

CONCLUSIONS

 Sympathetic celiac and cervicothoracic ganglia present very low and low level of diffusion restriction in visual DWI assessment, and significantly higher than metastatic lymph nodes mean ADC values in the majority of cases, which may serve as additional factors aiding differential diagnosis on multimodal PSMA-ligand PET/MR imaging.Therefore, PSMA-ligand PET/MR appears potentially superior to PSMA-ligand PET/CT in proper identification of sympathetic ganglia.

Value of integrated PET-IVIM MR in assessing metastases in hypermetabolic pelvic lymph nodes in cervical cancer: a multi-parameter study

PURPOSE

To evaluate the value of integrated multi-parameter positron emission tomography-intravoxel incoherent motion magnetic resonance (PET-IVIM MR) imaging for pelvic lymph nodes with high FDG uptake in cervical cancer, and to determine the best combination of parameters.

METHODS

A total of 38 patients with 59 lymph nodes with high FDG uptake were included. The imaging parameters of the lymph nodes were calculated by PET-IVIM MR, and the differences between lymph nodes diagnosed by postoperative pathology as metastasis versus non-metastasis were compared. We used the receiver operating characteristic (ROC) curve and logistic regression to construct a combination prediction model to filter low value and similar parameters, in order to search the optimal combination of PET/MR parameters for predicting pathologically confirmed metastatic lymph nodes. The correlation between diffusion parameters and metabolic parameters was analyzed by Spearman's rank correlation.

RESULTS

The maximum standardized uptake value (SUV_max), mean standardized uptake value (SUV_mean), total metabolic tumor volume (MTV), total lesion glycolysis (TLG), apparent diffusion coefficient (ADC), diffusion-related coefficient (D), and perfusion-related parameter (F) showed significant differences between the metastatic and non-metastatic groups (p < 0.05). The combination of MTV, SUV_max, and D had the strongest predictive value (area under the ROC 0.983, p < 0.05). SUV_max, SUV_mean, and TLG weakly correlated with F (R = - 0.306, - 0.290, and - 0.310; p < 0.05).

CONCLUSIONS

The combination of MTV, SUV_max, and D may have a better diagnostic performance than PET- or IVIM-derived parameters either in combination or individually. No strong correlation exists between diffusion parameters and metabolic parameters.

KEY POINTS

• Integrated PET-IVIM MR may assist to characterize lymph node status. • The combination of MTV, SUV_max, and D may have a better diagnostic performance than PET- or IVIM-derived parameters either in combination or individually for the assessment of pelvic lymph nodes with high FDG uptake. • No strong correlation exists between diffusion parameters and metabolic parameters in pelvic lymph nodes with high FDG uptake.

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

PURPOSE

This study sought to monitor the dynamic process of lymph node (LN) metastasis with intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI), and to investigate the impact of disease course on the detection of metastatic LNs by IVIM-DWI.

METHODS

Twenty female New Zealand rabbits with 2.5-3.0 kg body weight were studied. VX2 cells and egg yolk emulsion were randomly inoculated into one thigh to induce metastatic and inflammatory popliteal LNs, respectively. Eight rabbits underwent IVIM-DWI (14 b values, 0-2000 s/mm²) 2 h prior to, and 14, 21, and 28 days after inoculation (D0, D14, D21, D28). The apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), and perfusion fraction (f) were measured and compared between the metastatic and the inflammatory groups at each time point. Three rabbits randomly chosen from the remaining twelve rabbits were sacrificed at each time point to perform hematoxylin and eosin staining and histologic evaluation.

RESULTS

The patterns of dynamic change of D*, ADC, and D were different between the metastatic and the inflammatory LNs. The metastatic group had a lower D* value at D14 (p = .003), and greater ADC and D values at both D21 (p = .001, p = .001) and D28 (p = .021, p = .001), compared to the inflammatory group. The f value of the metastatic group was greater than that of the inflammatory only at D28 (p = .001).

CONCLUSIONS

IVIM-DWI can reflect the dynamic process of LN metastasis, and disease course has a significant influence on the ability of IVIM-DWI to detect metastatic nodes.

Intravoxel incoherent motion diffusion-weighted magnetic resonance imaging in characterization of axillary lymph nodes: Preliminary animal experience

PURPOSE

To investigate the diagnostic value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) for discriminating axillary metastatic from non-metastatic lymph nodes (LNs) in rabbit models.

MATERIALS AND METHODS

The institutional animal care and use committee approved this study. Forty New Zealand white rabbits were randomly divided into two groups. The axillary LN models were created by inoculating VX2 cell suspension and complete Freund's adjuvant in the mammary glands of 20 female rabbits of each group, respectively. Conventional MRI and IVIM DWI were performed after animal models successfully established. Images of axillary LNs were analyzed with regard to long-axis diameter (L), short-axis diameter (S), apparent diffusion coefficient (ADC) and IVIM parameters (D, D*, f). Receiver operating characteristic analyses were conducted to determine the diagnostic performance of aforementioned criteria.

RESULTS

A total of 42 metastatic and 30 non-metastatic LNs were successfully isolated. ADC and D of metastatic LNs were significantly lower than those of non-metastatic ones (all P < 0.001), whereas D* was statistically higher (P = 0.033). L, S, and f showed no significant difference between the two groups (P = 0.089, 0.058, 0.054, respectively). Optimal cutoff values, area under the curve, sensitivity, and specificity for differentiation were as follows: ADC = 1.101 × 10^-3 mm²/s, 0.886, 78.6%, 90.0%; D = 0.938 × 10^-3 mm²/s, 0.927, 83.3%, 93.3%; and D* = 12.635 × 10^-3 mm²/s, 0.657, 52.4%, 80.0%.

CONCLUSION

IVIM DWI is useful to distinguish metastatic from non-metastatic LNs in axilla. D was the most discriminative variable for predicting metastatic LNs.