Diffusion kurtosis imaging predicts neoadjuvant chemotherapy responses within 4 days in advanced nasopharyngeal carcinoma patients

MR Diffusion Kurtosis Imaging (DKI) of the Normal Human Uterus in Vivo During the Menstrual Cycle

BACKGROUND

The uterus undergoes dynamic changes throughout the menstrual cycle. Diffusion kurtosis imaging (DKI) is based on the non-Gaussian distribution of water molecules and can perhaps represent the changes of uterine microstructure.

PURPOSE

To investigate the temporal changes in DKI-parameters of the normal uterine corpus and cervix during the menstrual cycle.

STUDY TYPE

Prospective.

POPULATION

21 healthy female volunteers (26.64 ± 4.72 years) with regular menstrual cycles (28 ± 7 days).

FIELD STRENGTH/SEQUENCE

Readout segmentation of long variable echo-trains (RESOLVE)-based DKI and fast spin-echo T2-weighted sequences at 3.0T.

ASSESSMENT

Each volunteer was scanned during the menstrual phase, ovulatory phase, and luteal phase. Regions of interest (ROI) were manually delineated in the endometrium, junctional zone, and myometrium of the uterine body, and in the mucosal layer, fibrous stroma layer, and loose stroma layer of the cervix. The mean Kapp (diffusion kurtosis coefficient), Dapp (diffusion coefficient), and ADC (apparent diffusion coefficient) values were measured in the ROI.

STATISTICAL TESTS

ANOVA with Bonferroni or Tamhane correction. Intraclass correlation coefficient (ICC) for assessing agreement. P < 0.05 was considered statistically significant.

RESULTS

During the menstrual cycle, the highest Kapp (0.848 ± 0.184) and lowest Dapp (1.263 ± 0.283 *10-3 mm2/sec) values were found in the endometrium during the menstrual phase. The Dapp values for the myometrium were significantly higher than those of the endometrium and the junctional zone in every phase. Meanwhile, the Dapp values for the three zonal structures of the cervix during ovulation were significantly higher than those during the luteal phase. However, there was no significant difference in the ADC values of the loose stroma between ovulation and the luteal phase (P = 0.568). The reproducibility of DKI parameters was good (ICC, 0.857-0.944).

DATA CONCLUSION

DKI can show dynamic changes of the normal uterus during the menstrual cycle.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

A review of diffusion-weighted magnetic resonance imaging in head and neck cancer patients for treatment evaluation and prediction of radiation-induced xerostomia

The incidence of head and neck cancers (HNC) is rising worldwide especially with HPV-related oropharynx squamous cell carcinoma. The standard of care for the majority of patients with locally advanced pharyngeal disease is curative-intent radiotherapy (RT) with or without concurrent chemotherapy. RT-related toxicities remain a concern due to the close proximity of critical structures to the tumour, with xerostomia inflicting the most quality-of-life burden. Thus, there is a paradigm shift towards research exploring the use of imaging biomarkers in predicting treatment outcomes. Diffusion-weighted imaging (DWI) is a functional MRI feature of interest, as it quantifies cellular changes through computation of apparent diffusion coefficient (ADC) values. DWI has been used in differentiating HNC lesions from benign tissues, and ADC analyses can be done to evaluate tumour responses to RT. It is also useful in healthy tissues to identify the heterogeneity and physiological changes of salivary glands to better understand the inter-individual differences in xerostomia severity. Additionally, DWI is utilised in irradiated salivary glands to produce ADC changes that correlate to clinical xerostomia. The implementation of DWI into multi-modal imaging can help form prognostic models that identify patients at risk of severe xerostomia, and thus guide timely interventions to mitigate these toxicities.

A comparative study of functional MRI in predicting response of regional nodes to induction chemotherapy in patients with nasopharyngeal carcinoma

Purpose

To identify and compare the value of functional MRI (fMRI) in predicting the early response of metastatic cervical lymph nodes (LNs) to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC) patients.

Methods

This prospective study collected 94 metastatic LNs from 40 consecutive NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion-weighted imaging, diffusion kurtosis imaging, intravoxel incoherent motion, and dynamic contrast-enhanced magnetic resonance imaging were performed before and after IC. The parameter maps apparent diffusion coefficient (ADC), mean diffusion coefficient (MD), mean kurtosis (MK), Dslow, Dfast, perfusion fraction (PF), Ktrans, Ve, and Kep) of the metastatic nodes were calculated by the Functool postprocessing software. All LNs were classified as the responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between the RG and the NRG. The significant parameters are fitted by logistic regression analysis to produce new predictive factor (PRE)–predicted probabilities. Logistic regression analysis and receiver operating characteristic (ROC) curves were performed to further identify and compare the efficacy of the parameters.

Results

After IC, the mean values of ADC, MD, and Dslow significantly increased, while MK, Dfast, and Ktrans values decreased dramatically, while no significant difference was detected in Ve and Kep. Compared with NRG, PF-pre and Ktrans-pre values in the RG were higher statistically. The areas under the ROC for the pretreatment PF, Ktrans, and PRE were 0.736, 0.722, and 0.810, respectively, with the optimal cutoff value of 222 × 10-4, 934 × 10-3/min, and 0.6624, respectively.

Conclusions

The pretreatment fMRI parameters PF and Ktrans showed promising potential in predicting the response of the metastatic LNs to IC in NPC patients.

Clinical Trial Registration

This study was approved by the ethics board of the Chinese PLA General Hospital, and registered on 30 January 2021, in the Chinese Clinical Trial Registry; http://www.chictr.org.cn/showproj.aspx?proj=121198, identifier (ChiCTR2100042863).

Optimization of scan parameters to reduce acquisition time for RESOLVE-based diffusion kurtosis imaging (DKI) in nasopharyngeal carcinoma (NPC)

OBJECTIVE

To shorten acquisition time of readout segmentation of long variable echo trains (RESOLVE)-based diffusion kurtosis imaging (DKI) via Readout Partial Fourier (RPF) and b-value combinations.

METHODS

The RESOLVE-based DKI images of 38 patients with nasopharyngeal carcinoma (NPC) were prospectively enrolled. For RESOLVE-based DKI images with 5/8 RPF and without RPF, objective and subjective evaluations of image quality were performed. A total of nine groups with different b-value combinations were simulated, and the influence of different b-value combinations for RESOLVE-RPF-based DKI sequences was assessed using the intraclass correlation coefficient (ICC).

RESULTS

The mean values of signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) in DKI images without RPF were higher than those with 5/8 RPF (252.9 ± 77.7 vs 247.3 ± 85.5 and 5.8 ± 2.8 vs 5.4 ± 2.3, respectively), but not significantly (p = 0.460 and p = 0.180, respectively). In comparing the ICCs between nine groups of different b-value combinations in RESOLVE-RPF-based DKI, group (200, 800, 2000 s/mm2), group (200, 400, 800, 2000 s/mm2) and group (200, 800, 1500, 2000 s/mm2) were not significantly different (p > 0.001) and showed excellent agreement (0.81-1.00) with that of group (200, 400, 800, 1500, 2000 s/mm2). Using b-value optimization and RPF technology, the group with RPF (200, 400, 800, 2000 s/mm2) showed a 56% reduced scanning compared with the group without RPF (200, 400, 800, 1500, 2000 s/mm2; 3 min 46 s vs 8 min 31 s, respectively).

CONCLUSION

DKI with RPF did not significantly affect image quality, but both RPF and different b-value combinations can affect the scanning time. The combination of RPF and b-value optimization can ensure the stability of DKI parameters and reduce the scanning time by 56%.

ADVANCES IN KNOWLEDGE

This work is to optimize scan parameters, e.g. RPF and b-value combinations, to reduce acquisition time for RESOLVE-based DKI in NPC. To our knowledge, the effect of RESOLVE-RPF and b-value combinations on DKI has not been reported.

Arterial spin labeling of nasopharyngeal carcinoma shows early therapy response

OBJECTIVE

This study aimed to determine the value of arterial spin labeling (ASL) perfusion imaging in assessing the early efficacy of chemoradiotherapy for nasopharyngeal carcinoma (NPC).

METHODS

Fifty-five patients with locoregionally advanced NPC underwent conventional 3.0-T magnetic resonance imaging (MRI) and ASL before and after chemoradiotherapy (prescribed dose reached 40 Gy). Based on the response evaluation criteria for solid tumors (RECIST 1.1), the patients were divided into the partial response and stable disease groups. MRI re-examination was performed one month after chemoradiotherapy completion, and patients were divided into residual and non-residual groups. We investigated inter-group differences in ASL-based tumor blood flow (TBF) parameters (pre-treatment tumor blood flow, post-treatment tumor blood flow, and changes in tumor blood flow, i.e., Pre-TBF, Post-TBF, ΔTBF), correlation between TBF parameters and tumor atrophy rate, and value of TBF parameters in predicting sensitivity to chemoradiotherapy.

RESULTS

There were differences in Pre-TBF, Post-TBF, and ΔTBF between the partial response and stable disease groups (p < 0.01). There were also differences in Pre-TBF and ΔTBF between the residual and non-residual groups (p < 0.01). Pre-TBF and ΔTBF were significantly correlated with the tumor atrophy rate; the correlation coefficients were 0.677 and 0.567, respectively (p < 0.01). Pre-TBF had high diagnostic efficacies in predicting sensitivity to chemoradiotherapy and residual tumors, with areas under the curve of 0.845 and 0.831, respectively.

CONCLUSION

ASL permits a noninvasive approach to predicting the early efficacy of chemoradiotherapy for NPC.

Advances in Imaging in Evaluating the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer

Neoadjuvant chemotherapy (NAC) is increasingly widely used in breast cancer treatment, and accurate evaluation of its response provides essential information for treatment and prognosis. Thus, the imaging tools used to quantify the disease response are critical in evaluating and managing patients treated with NAC. We discussed the recent progress, advantages, and disadvantages of common imaging methods in assessing the efficacy of NAC for breast cancer.

Comparison of the pre-treatment functional MRI metrics' efficacy in predicting Locoregionally advanced nasopharyngeal carcinoma response to induction chemotherapy

Background

Functional MRI (fMRI) parameters analysis has been proven to be a promising tool of predicting therapeutic response to induction chemotherapy (IC) in nasopharyngeal carcinoma (NPC). The study was designed to identify and compare the value of fMRI parameters in predicting early response to IC in patients with NPC.

Methods

This prospective study enrolled fifty-six consecutively NPC patients treated with IC from January 2021 to May 2021. Conventional diffusion weighted imaging (DWI), diffusion kurtosis imaging (DKI), intravoxel incoherent motion (IVIM) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) protocols were performed before and after IC. Parameters maps (ADC, MD, MK, D_slow, D_fast, PF, K^trans, V_e and K_ep) of the primary tumor were calculated by the Functool post-processing software. The participants were classified as responding group (RG) and non-responding group (NRG) according to Response Evaluation Criteria in Solid Tumors 1.1. The fMRI parameters were compared before and after IC and between RG with NRG. Logistic regression analysis and ROC were performed to further identify and compare the efficacy of the parameters.

Results

After IC, the mean values of ADC(p < 0.001), MD(p < 0.001), D_slow(p = 0.001), PF(p = 0.030) and V_e(p = 0.003) significantly increased, while MK(p < 0.001), D_fast(p = 0.009) and K_ep(p = 0.003) values decreased dramatically, while no significant difference was detected in K^trans(p = 0.130). Compared with NRG, ADC-pre(p < 0.001), MD-pre(p < 0.001) and D_slow-pre(p = 0.002) values in RG were lower, while MK-pre(p = 0.017) values were higher. The areas under the ROC curves for the ADC-pre, MD-pre, MK-pre, D_slow-pre and PRE were 0.885, 0.855, 0.809, 0.742 and 0.912, with the optimal cutoff value of 1210 × 10^− 6 mm²/s, 1010 × 10^− 6 mm²/s, 832 × 10^− 6, 835 × 10^− 6 mm²/s and 0.799 respectively.

Conclusions

The pretreatment conventional DWI (ADC), DKI (MD and MK), and IVIM (D_slow) values derived from fMRI showed a promising potential in predicting the response of the primary tumor to IC in NPC patients.

Trial registration

This study was approved by ethics board of the Chinese PLA General Hospital, and registered on January 30, 2021, in Chinese Clinical Trial Registry (ChiCTR2100042863).

Supplementary Information

The online version contains supplementary material available at 10.1186/s40644-021-00428-0.

Diffusion-weighted MRI for predicting treatment response in patients with nasopharyngeal carcinoma: a systematic review and meta-analysis

Early prediction of treatment response in nasopharyngeal carcinoma is clinically relevant for optimizing treatment strategies. This meta-analysis was performed to evaluate whether apparent diffusion coefficient (ADC) from diffusion-weighted imaging (DWI) can predict treatment response of patients with nasopharyngeal carcinoma. A systematic search of PubMed-MEDLINE and Embase was performed to identify relevant original articles until July 22, 2021. We included studies which performed DWI for predicting locoregional treatment response in nasopharyngeal carcinoma treated with neoadjuvant chemotherapy, definitive chemoradiation, or radiation therapy. Hazard ratios were meta-analytically pooled using a random-effects model for the pooled estimates of overall survival, local relapse-free survival, distant metastasis-free survival and their 95% CIs. ADC showed a pooled sensitivity of 87% (95% CI 72–94%) and specificity of 70% (95% CI 56–80%) for predicting treatment response. Significant between-study heterogeneity was observed for both pooled sensitivity (I² = 68.5%) and specificity (I² = 92.2%) (P < 0.01). The pooled hazard ratios of low pretreatment ADC for assessing overall survival, local relapse-free survival, and distant metastasis-free survival were 1.42 (95% CI 1.09–1.85), 2.31 (95% CI 1.42–3.74), and 1.35 (95% CI 1.05–1.74), respectively. In patients with nasopharyngeal carcinoma, pretreatment ADC demonstrated good predictive performance for treatment response.

Pretreatment MRI-Derived Radiomics May Evaluate the Response of Different Induction Chemotherapy Regimens in Locally advanced Nasopharyngeal Carcinoma

RATIONALE AND OBJECTIVES

To evaluate and compare the performance of radiomics in predicting induction chemotherapy response treated with two different regimens in patients with advanced nasopharyngeal carcinoma.

MATERIALS AND METHODS

A total of 265 patients with pathologically confirmed locally advanced nasopharyngeal carcinoma (stage II-IV), including 115 treated with gemcitabine plus cisplatin (GP group) and 150 treated with docetaxel plus cisplatin (TP group) were retrospectively enrolled. Radiomics features were extracted from the volume of interest delineated in multi-MR sequences on a 3T scanner. After random stratified grouping (training and validation cohorts) and logistic regression based on selected features, the association between the radiomics signature and the early response to induction chemotherapy were established for GP and TP regiments, respectively.

RESULTS

Clinical factors showed no significant difference between the response and non-response groups for the GP and TP regiments (all p > 0.05). The accuracy of the radiomics signature consisting of selected features from the joint T1, T2, and T1C in the GP group (0.852 in the training cohort vs. 0.853 in the validation cohort) was significantly higher than that in the TP group (0.774 vs 0.727). The overall performance of the GP model was steady, with efficiency to distinguish responders from nonresponders with an AUC reaching 0.907 (95% confidence interval [CI] [0.843-0.970]) in the training cohort and 0.886 (95% CI [0.772-0.998]) in the validation cohort, while leveling at 0.800 (95% CI [0.712-0.888]) in the training cohort and 0.863 (95% CI [0.758-0.967]) in the validation cohort in the TP group.

CONCLUSION

Pretreatment MR radiomics signature can better predict the early response to IC in the GP regimen than the TP regimen, which may be helpful to guide IC management.

Comparative Study of Monoexponential, Intravoxel Incoherent Motion, Kurtosis, and IVIM-Kurtosis Models for the Diagnosis and Aggressiveness Assessment of Prostate Cancer

Objective: This study aimed to compare the potential of monoexponential model (MEM), intravoxel incoherent motion (IVIM) model, kurtosis model, and IVIM–kurtosis model in the diagnosis and aggressiveness assessment of prostate cancer (PCa).

Materials and Methods: Thirty-six patients were recruited. Diffusion-weighted images were acquired on a 3.0-T magnetic resonance imaging (MRI) system using 0 b values up to 2,000 s/mm² and analyzed using four models: MEM (ADC_MEM), IVIM (D_IVIM, D*_IVIM, f_IVIM), kurtosis (D_kurtosis, K_kurtosis), and IVIM–kurtosis (D_{IVIM−kurtosis}, D^*_{IVIM−kurtosis}, f_{IVIM−kurtosis}, D_{IVIM−kurtosis}) models. The values of these parameters were calculated and compared between PCa, benign prostatic hyperplasia (BPH), and prostatitis. Correlations between these parameters and the Gleason score (GS) of PCa were evaluated using the Pearson test.

Results: Forty-five lesions were studied, including 18 PCa, 12 prostatitis, and 15 BPH lesions. The ADC_MEM, D_IVIM, f_IVIM, D_kurtosis, and D_{IVIM−kurtosis} values were significantly lower and K_kurtosis and K_{IVIM−kurtosis} values were significantly higher in PCa compared with prostatitis and BPH. The area under the curve (AUC) of ADC_MEM showed significantly higher values than that of f_IVIM and K_{IVIM−kurtosis}, but no statistical differences were found between the other parameters. The D^*_{IVIM−kurtosis} value correlated negatively and f_{IVIM−kurtosis} and K_{IVIM−kurtosis} values correlated positively with the GS.

Conclusion: The MEM, IVIM, kurtosis, and IVIM–kurtosis models were all useful for the diagnosis of PCa, and the diagnostic efficacy seemed to be similar. The IVIM–kurtosis model may be superior to the MEM, IVIM, and kurtosis models in the grading of PCa.

Diffusion kurtosis imaging and tumour microstructure for monitoring response to radiotherapy in human nasopharyngeal carcinoma xenografts

OBJECTIVE

To investigate the correlations and feasibility of diffusion kurtosis imaging (DKI) parameters and tumour histopathology after radiotherapy in human nasopharyngeal carcinoma (NPC) xenografts on nude mice.

MATERIALS AND METHODS

Seventy-two nude mice were used for the construction of CNE-1 (radio-insensitive) and CNE-2 (radio-sensitive) NPC xenograft models, followed by fraction irradiation at different doses of X-ray. The nude mice were randomly divided into six groups in each cell line models according to the dose of X-ray they have received and with six mice in each group. DKI scan was performed after radiation. DKI parameters, tumour histopathology and AQP-1 biomarkers were detected. One-way ANOVA and Pearson's correlation analysis were used in statistical analysis.

RESULTS

In CNE-1 and CNE-2 NPC xenografts, D values were increased (P < 0.01 and P < 0.001), while K values (P < 0.01 and P < 0.001) and tumour size (P < 0.001 and P < 0.001) were reduced during fraction irradiation. Additionally, cell density (CD) and AQP-1 expressions were decreased, and necrosis ratio (NR) was increased in CNE-2 xenografts after fraction irradiation (P < 0.001). The changes in D values were negatively correlated with tumour size (r = -0.856, P < 0.001), CD (r = -0.918, P < 0.001), AQP-1 mRNA (r = -0.856, P < 0.001) and protein (r = -0.381, P = 0.022) expressions while positively correlated with NR (r = 0.908, P < 0.001) in CNE-2 xenografts. The changes in K values were positively correlated with tumour size (r = 0.964, P < 0.001), CD (r = 0.888, P < 0.001), AQP-1 mRNA (r = 0.955, P < 0.001) and protein (r = 0.330, P = 0.049) expression levels while negatively correlated with NR (r = -0.930, P < 0.001). However, in CNE-1 xenografts, there were no correlation between DKI parameters and the expression of AQP-1.

CONCLUSION

Changes in D and K parameters after fractional irradiation are closely related with NPC cellular and pathological characteristics, especially size reduction and necrosis induction. These parameters exhibit potential abilities of monitoring the response to fractional irradiation in radio-sensitive NPC xenografts.

Patient-Centric Head and Neck Cancer Radiation Therapy: Role of Advanced Imaging

The traditional 'one-size-fits-all' approach to H&N cancer therapy is archaic. Advanced imaging can identify radioresistant areas by using biomarkers that detect tumor hypoxia, hypercellularity etc. Highly conformal radiotherapy can target resistant areas with precision. The critical information that can be gleaned about tumor biology from these advanced imaging modalities facilitates individualized radiotherapy. The tumor imaging world is pushing its boundaries. Molecular imaging can now detect protein expression and genotypic variations across tumors that can be exploited for tailoring treatment. The exploding field of radiomics and radiogenomics extracts quantitative, biologic and genetic information and further expands the scope of personalized therapy.

Comparison of intravoxel incoherent motion imaging, diffusion kurtosis imaging, and conventional DWI in predicting the chemotherapeutic response of colorectal liver metastases

PURPOSE

To assess the usefulness and performance of intravoxel incoherent motion imaging (IVIM) with diffusion kurtosis imaging (DKI) and conventional DWI for predicting the chemotherapeutic response of colorectal liver metastases (CRLMs).

METHOD

A prospective study was conducted. Up to February 2018, forty consecutive patients treated with the standard first-line chemotherapy regimens were enrolled. MRI was performed within 1 week before chemotherapy, as well as 2-3 weeks and 6-8 weeks after chemotherapy. The apparent diffusion coefficient map, IVIM and DKI parameter maps were calculated using a prototype postprocessing software. The response was assessed by the Response Evaluation Criteria in Solid Tumors. The parameters were compared between the responding group (complete and partial response) and the nonresponding group (stable and progressive disease).

RESULTS

A total of 15 responding and 25 nonresponding patients were evaluated. Low baseline ADC, D_slow, and D values (P =  0.001, <0.001, and =0.003, respectively) and a high baseline K value (P =  0.002) were independently associated with a good response to chemotherapy. The combination of all the significant parameters yielded an AUC of 0.867. After treatment, the ADC, D_slow, and D values all showed an upward trend, while the K value showed a decreasing trend, but there were no significant differences (P >  0.05).

CONCLUSION

The study showed that the pretreatment IVIM (D_slow), DKI (D and K), and conventional DWI (ADC) parameters all demonstrated a good diagnostic performance in predicting the chemotherapeutic response of CRLMs.

Magnetic resonance imaging in the assessment of pancreatic cancer with quantitative parameter extraction by means of dynamic contrast-enhanced magnetic resonance imaging, diffusion kurtosis imaging and intravoxel incoherent motion diffusion-weighted imaging

BACKGROUND

Despite great technical advances in imaging, such as multidetector computed tomography and magnetic resonance imaging (MRI), diagnosing pancreatic solid lesions correctly remains challenging, due to overlapping imaging features with benign lesions. We wanted to evaluate functional MRI to differentiate pancreatic tumors, peritumoral inflammatory tissue, and normal pancreatic parenchyma by means of dynamic contrast-enhanced MRI (DCE-MRI)-, diffusion kurtosis imaging (DKI)-, and intravoxel incoherent motion model (IVIM) diffusion-weighted imaging (DWI)-derived parameters.

METHODS

We retrospectively analyzed 24 patients, each with histopathological diagnosis of pancreatic tumor, and 24 patients without pancreatic lesions. Functional MRI was acquired using a 1.5 MR scanner. Peritumoral inflammatory tissue was assessed by drawing regions of interest on the tumor contours. DCE-MRI, IVIM and DKI parameters were extracted. Nonparametric tests and receiver operating characteristic (ROC) curves were calculated.

RESULTS

There were statistically significant differences in median values among the three groups observed by Kruskal-Wallis test for the DKI mean diffusivity (MD), IVIM perfusion fraction (fp) and IVIM tissue pure diffusivity (Dt). MD had the best results to discriminate normal pancreas plus peritumoral inflammatory tissue versus pancreatic tumor, to separate normal pancreatic parenchyma versus pancreatic tumor and to differentiate peritumoral inflammatory tissue versus pancreatic tumor, respectively, with an accuracy of 84%, 78%, 83% and area under ROC curve (AUC) of 0.85, 0.82, 0.89. The findings were statistically significant compared with those of other parameters (p value < 0.05 using McNemar's test). Instead, to discriminate normal pancreas versus peritumoral inflammatory tissue or pancreatic tumor and to differentiate normal pancreatic parenchyma versus peritumoral inflammatory tissue, there were no statistically significant differences between parameters' accuracy (p > 0.05 at McNemar's test).

CONCLUSIONS

Diffusion parameters, mainly MD by DKI, could be helpful for the differentiation of normal pancreatic parenchyma, perilesional inflammation, and pancreatic tumor.

Diffusion kurtosis imaging in the prediction of poor responses of locally advanced gastric cancer to neoadjuvant chemotherapy

PURPOSE

To assess the efficacy of diffusion kurtosis imaging (DKI) in the prediction of the treatment response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer (LAGC).

METHODS

A total of 31 LAGC patients were enrolled in this prospective study. All patients underwent diffusion-weighted MRI examination (with b = 0₁, 200₁, 500₁, 800₂, 1000₄, 1500₄, 2000₆ s/mm², the subscript denotes the number of signal averages) before and after chemotherapy. DKI and mono-exponential (b = 0, 800 s/mm²) models were built. Apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) of the LAGC tumors were measured. The absolute change values (ΔX) and percentage change values (%ΔX) of the above parameters post neoadjuvant chemotherapy (NACT) were calculated. The response was evaluated according to the pathological tumor regression grade scores (effective response group: TRG 0-2, poor response group: TRG 3). Mann-Whitney U test and receiver operating characteristic (ROC) curves were applicated for statistical analysis.

RESULTS

There were 17 patients in the effective response group (ERG), and 14 patients in the poor response group (PRG). The MK_pre and MK_post values in PRG were significantly higher than those in ERG [(0.671 ± 0.026) and (0.641 ± 0.019) vs. (0.584 ± 0.023) and (0.519 ± 0.018), p < 0.001]. ADC_post and MD_post in PRG were significantly lower than those in ERG (p = 0.005, p =0.001). Significant differences were also observed for % ΔMK, ΔMD and ΔMK between the two groups (p < 0.05). The area under the curve (AUC) for the prediction of PRG was highest for MK_post (AUC = 0.958, cutoff value = 0.614). The MK_pre and MK_post had the highest sensitivity (91.70 %) and specificity (93.80 %) in the prediction of PRG, respectively.

CONCLUSION

Both DKI and ADC values show potential for the prediction of the PRG in LAGC patients. The DKI parameters, especially MK_post displayed the best performance.

Diffusion kurtosis imaging in head and neck cancer: A correlation study with dynamic contrast enhanced MRI

PURPOSE

To investigate the biophysical meaning of Diffusion Kurtosis Imaging (DKI) parameters via correlations with the perfusion parameters obtained from a long Dynamic Contrast Enhanced MRI scan, in head and neck (HN) cancer.

METHODS

Twenty two patients with newly diagnosed HN tumor were included in the present retrospective study. Some patients had multiple lesions, therefore a total of 26 lesions were analyzed. DKI was acquired using 5b values at 0, 500, 1000,1500 and 2000 s/mm². DCE-MRI was obtained with 130 dynamic volumes, with a temporal resolution of 5 s, to achieve a long scan time (>10 min). The apparent diffusion coefficient D_app and apparent diffusional kurtosis K_app were calculated voxel-by-voxel, removing the point at b value = 0 to eliminate possible perfusion effects on the parameter estimations. The transfer constants K^trans and K_ep, v_e, and the histogram-based entropy (En) and interquartile range (IQR) of each DCE-MRI parameter were quantified. Correlations between all variables were investigated by the Spearman's Rho correlation test.

RESULTS

Moderate relationships emerged between D_app and K_ep (Rho =  - 0.510, p = 0.009), and between D_app and v_e (Rho = 0.418, p = 0.038). En(K_ep) was significantly related to K_app (Rho = 0.407, p = 0.043), while IQR(K_ep) showed an inverse association with D_app (Rho = -0.422, p = 0.035).

CONCLUSIONS

A weak to intermediate correlation was found between DKI parameters and both K_ep and v_e. The kurtosis was associated to the intratumoral heterogeneity and complexity of the capillary permeability, expressed by En(K_ep).

Evaluation of non-Gaussian model-based diffusion-weighted imaging in oral squamous cell carcinoma: comparison with tumour functional information derived from positron-emission tomography

AIM

To evaluate and compare diffusion-weighted imaging (DWI) parameters derived from a non-Gaussian fitting model and positron-emission tomography (PET) parameters derived from ¹⁸F-fluoromisonidazole-PET (FMISO-PET) in patients with oral squamous cell carcinoma (OSCC).

MATERIALS AND METHODS

Primary sites were evaluated prospectively in 18 patients. DWI was performed using six b-values (0-2,500). Diffusion-related parameters of kurtosis value (K), the kurtosis-corrected diffusion coefficient (D_K), diffusion heterogeneity (α), distributed diffusion coefficient (DDC), the slow diffusion coefficient (D_slow), and the apparent diffusion coefficient (ADC) were calculated from four diffusion-fitting models. Maximal standardised uptake values (SUV_max), mean standardised uptake values (SUV_mean), and the tumour-to-muscle ration (TMR) of the SUV value were calculated for FMISO-PET. Spearman's correlation coefficient was used to evaluate the correlation between each non-Gaussian diffusion model parameters and PET parameter.

RESULTS

There was moderate correlation between FMISO-PET SUV_max and D_slow (ρ=-0.45, p=0.06). In addition, there was good correlation between TMR_max and five non-Gaussian diffusion model parameters (K: ρ=0.65, p=0.004, D_K: ρ=-0.72, p=0.0008, DDC: ρ=-0.75, p=0.0003, ADC: ρ=-0.74, p=0.0005, and D_slow: ρ= -0.65, p=0.003), and between TMR_mean and five non-Gaussian model parameters (K: ρ=0.64, p=0.005, D_K: ρ=-0.61, p=0.007, DDC: ρ=-0.63, p=0.005, ADC: ρ=-0.61, p=0.007, and D_slow: ρ=-0.56, p=0.015).

CONCLUSION

Non-Gaussian diffusion model parameters can be related to tumour hypoxia.

Diffusion kurtosis MRI as a predictive biomarker of response to neoadjuvant chemotherapy in high grade serous ovarian cancer

This study assessed the feasibility of using diffusion kurtosis imaging (DKI) as a measure of tissue heterogeneity and proliferation to predict the response of high grade serous ovarian cancer (HGSOC) to neoadjuvant chemotherapy (NACT). Seventeen patients with HGSOC were imaged at 3 T and had biopsy samples taken prior to any treatment. The patients were divided into two groups: responders and non-responders based on Response Evaluation Criteria In Solid Tumours (RECIST) criteria. The following imaging metrics were calculated: apparent diffusion coefficient (ADC), apparent diffusion (Dapp) and apparent kurtosis (Kapp). Tumour cellularity and proliferation were quantified using histology and Ki-67 immunohistochemistry. Mean Kapp before therapy was higher in responders compared to non-responders: 0.69 ± 0.13 versus 0.51 ± 0.11 respectively, P = 0.02. Tumour cellularity correlated positively with Kapp (rho = 0.50, P = 0.04) and negatively with both ADC (rho = -0.72, P = 0.001) and Dapp (rho = -0.80, P < 0.001). Ki-67 expression correlated with Kapp (rho = 0.53, P = 0.03) but not with ADC or Dapp. In conclusion, Kapp was found to be a potential predictive biomarker of NACT response in HGSOC, which suggests that DKI is a promising clinical tool for use oncology and radiology that should be evaluated further in future larger studies.

Machine-Learning-Based Prediction of Treatment Outcomes Using MR Imaging-Derived Quantitative Tumor Information in Patients with Sinonasal Squamous Cell Carcinomas: A Preliminary Study

The purpose of this study was to determine the predictive power for treatment outcome of a machine-learning algorithm combining magnetic resonance imaging (MRI)-derived data in patients with sinonasal squamous cell carcinomas (SCCs). Thirty-six primary lesions in 36 patients were evaluated. Quantitative morphological parameters and intratumoral characteristics from T2-weighted images, tumor perfusion parameters from arterial spin labeling (ASL) and tumor diffusion parameters of five diffusion models from multi-b-value diffusion-weighted imaging (DWI) were obtained. Machine learning by a non-linear support vector machine (SVM) was used to construct the best diagnostic algorithm for the prediction of local control and failure. The diagnostic accuracy was evaluated using a 9-fold cross-validation scheme, dividing patients into training and validation sets. Classification criteria for the division of local control and failure in nine training sets could be constructed with a mean sensitivity of 0.98, specificity of 0.91, positive predictive value (PPV) of 0.94, negative predictive value (NPV) of 0.97, and accuracy of 0.96. The nine validation data sets showed a mean sensitivity of 1.0, specificity of 0.82, PPV of 0.86, NPV of 1.0, and accuracy of 0.92. In conclusion, a machine-learning algorithm using various MR imaging-derived data can be helpful for the prediction of treatment outcomes in patients with sinonasal SCCs.

Treatment Response Prediction of Nasopharyngeal Carcinoma Based on Histogram Analysis of Diffusional Kurtosis Imaging

BACKGROUND AND PURPOSE

The prediction of treatment response is important in planning and modifying the chemoradiation therapy regimen. This study aimed to explore the quantitative histogram indices for treatment-response prediction of nasopharyngeal carcinoma based on diffusional kurtosis imaging compared with a standard ADC value (ADC_standard).

MATERIALS AND METHODS

Thirty-six patients with an initial diagnosis of locoregionally advanced nasopharyngeal carcinoma and diffusional kurtosis imaging acquisitions before and after neoadjuvant chemotherapy were enrolled. Patients were divided into respond-versus-nonrespond groups after neoadjuvant chemotherapy and residual-versus-nonresidual groups after radiation therapy. Histogram parameters of diffusional kurtosis imaging-derived parameters (ADC, ADC coefficient corrected by the non-Gaussain model [D], apparent kurtosis coefficient without a unit [K]) were calculated. The ADC_standard was calculated on the basis of intravoxel incoherent movement data. The intraclass correlation coefficient, Kolmogorov-Smirnov test, Student t test or Mann-Whitney U test, and receiver operating characteristic analysis were performed.

RESULTS

Most of the parameters had good-to-excellent consistency (intraclass correlation coefficient = 0.675-0.998). The pre-ADC_standard, pre-ADC (10th, 25th, 50th percentiles), pre-D (10th, 25th, 50th percentiles), and pre-K_50th were significantly different between the respond and nonrespond groups, while the pre-ADC_10th, pre-K_90th, post-ADC_50th, post-K_75th, post-K_90th, and the percentage change of parameters before and after neoadjuvant chemotherapy (▵ADC_50th%) were significantly different between the residual and nonresidual groups (all P < .05). Receiver operating characteristic analysis indicated that setting pre-D_50th = 0.875 × 10^-3mm²/s as the cutoff value could result in optimal diagnostic performance for neoadjuvant chemotherapy response prediction (area under the curve = 0.814, sensitivity = 0.70, specificity = 0.92), while the post-K_90th = 1.035 (area under the curve = 0.829, sensitivity = 0.78, specificity = 0.72), and▵ADC_50th% = 0.253 (area under the curve = 0.833, sensitivity = 0.94, specificity = 0.72) were optimal for radiation therapy response prediction.

CONCLUSIONS

Histogram analysis of diffusional kurtosis imaging may potentially predict the neoadjuvant chemotherapy and short-term radiation therapy response in locoregionally advanced nasopharyngeal carcinoma, therefore providing evidence for modification of the treatment regimen.

Diffusion kurtosis imaging and conventional diffusion weighted imaging to assess electrochemotherapy response in locally advanced pancreatic cancer

Background The aim of the study was to evaluate diagnostic performance of functional parameters derived by conventional mono-exponential approach of diffusion weighted imaging (DWI) and by diffusion kurtosis imaging (DKI) in the assessment of pancreatic tumours treated with electrochemotherapy (ECT). Patients and methods Twenty-one consecutive patients with locally advanced pancreatic adenocarcinoma subjected to ECT were enrolled in a clinical approved trial. Among twenty-one enrolled patients, 13/21 (61.9%) patients were subjected to MRI before and after ECT. DWI was performed with a 1.5 T scanner; a free breathing axial single shot echo planar DWI pulse sequence parameters were acquired using seven b value = 0, 50, 100, 150, 400, 800, 1000 s/mm2. Apparent diffusion coefficient by conventional mono-exponential approach and mean of diffusion coefficient (MD) and mean of diffusional kurtosis (MK) by DKI approach were derived from DWI. Receiver operating characteristic (ROC) analysis was performed and sensitivity, specificity, positive and negative predictive value were calculated. Results Among investigated diffusion parameters, only the MD derived by DKI showed a significant variation of values between pre and post treatment (p = 0.02 at Wilcoxon test) and a significant statistically difference for percentage change between responders and not responders (p = 0.01 at Kruskal Wallis test). MD had a good diagnostic performance with a sensitivity of 80%, a specificity of 100% and area under ROC of 0.933. Conclusions MD derived by DKI allows identifying responders and not responders patients subject to ECT treatment. MD had higher diagnostic performance to assess ECT response compared to conventional DWI derived parameters.

Clinical application of diffusion-weighted magnetic resonance imaging in radiotherapy for nasopharyngeal carcinoma

OBJECTIVE

To explore the clinical application of diffusion-weighted magnetic resonance imaging (DWI) in nasopharyngeal carcinoma (NPC) diagnosis, detection of lymph node metastasis, radiotherapy and prognosis.

METHODS

Twenty patients with diagnosed NPC in an early stage of radiotherapy were enrolled in our department between May 2010 and May 2013. T1 and T2 weighted magnetic resonance imaging and DWI of the nasopharynx and neck were performed 1 week before radiotherapy, during radiotherapy at a dose of 60 Gy, and 1 month after radiotherapy. Pertinent measurements and related data were recorded.

RESULTS

In comparison with that before radiotherapy, the ADC value of the nasopharyngeal primary lesion increased significantly during radiotherapy at a dose of 60 Gy and at 1 month after radiotherapy (F = 187.160, P = 0.000). When the dose of radiotherapy reached 60 Gy, the DWI signals from both the neck and the retropharyngeal lymph nodes were significantly lower than those before radiotherapy.

CONCLUSION

DWI can be used for sensitive and accurate diagnosis of lymph node metastasis in the neck and retropharyngeal space, monitoring of the radiotherapy effect in early stages of NPC and development of new medical treatment strategies.

Diffusion-weighted imaging and diffusion kurtosis imaging for early evaluation of the response to docetaxel in rat epithelial ovarian cancer

Background

To investigate diffusion-weighted magnetic imaging (DWI) and diffusion kurtosis magnetic imaging (DKI) for the early detection of the response to docetaxel (DTX) chemotherapy in rat epithelial ovarian cancer (EOC).

Methods

7,12-Dimethylbenz[A]anthracene was applied to induce orthotopic EOC in Sprague–Dawley rats. Rats with EOC were treated with DTX on day 0 (treatment group) or were left untreated (control group). DWI and DKI were performed on days 0, 3, 7, 14 and 21 after treatment. On day 21, the tumors were categorized into the sensitive and insensitive groups according to the size change. The cutoff values of the DWI and DKI parameters for the early response were determined. The experiment was repeated, and the treatment group was divided into the sensitive and insensitive groups according to the initially obtained cutoff values. The DWI and DKI parameters were correlated with tumor size, proliferation, apoptosis and tumor necrosis.

Results

In the sensitive vs. insensitive or control group, significant differences were found in the Δ% of the DWI and DKI parameters (ADC, D and K) from day 3 and in tumor size from day 14. Early on day 7, the Δ% of K had an AUC of 1 and sensitivity and specificity values of 100% and 100%, respectively, to detect the response to DTX using a cutoff value of 19.03% reduction in K. From day 7, significant differences were found in the Δ% of Ki-67 and CA125 in the sensitive vs. control group and from day 14 in the sensitive vs. insensitive group. From day 14, there were significant differences in the Δ% of Bcl-2, apoptosis and tumor necrosis in the sensitive vs. control or insensitive group. The Δ% values of ADC and D were negatively correlated with the Δ% values of tumor size, Ki-67, CA125 and Bcl-2 and were positively correlated with the Δ% values of apoptosis and tumor necrosis. The Δ% of K was positively correlated with the Δ% values of tumor size, Ki-67, CA125 and Bcl-2 and was negatively correlated with the Δ% values of apoptosis and tumor necrosis.

Conclusions

DWI and DKI parameters, especially K, are superior for imaging tumor size for the early detection of the response to DTX chemotherapy in induced rat EOC.

Diffusional kurtosis imaging in head and neck cancer: On the use of trace-weighted images to estimate indices of non-Gaussian water diffusion

PURPOSE

While previous studies have demonstrated the feasibility and potential usefulness of quantitative non-Gaussian diffusional kurtosis imaging (DKI) of the brain, more recent research has focused on oncological application of DKI in various body regions such as prostate, breast, and head and neck (HN). Given the need to minimize scan time during most routine magnetic resonance imaging (MRI) acquisitions of body regions, diffusion-weighted imaging (DWI) with only three orthogonal diffusion weighting directions (x, y, z) is usually performed. Moreover, as water diffusion within malignant tumors is generically thought to be almost isotropic, DWI with only three diffusion weighting directions is considered sufficient for oncological application and it represents the de facto standard in body DKI. In this context, since the kurtosis tensor and diffusion tensor cannot be obtained, the averages of the three directional (K_x , K_y , K_z ) and (D_x , D_y , D_z ) - namely K and D, respectively - represent the best-possible surrogates of directionless DKI-derived indices of kurtosis and diffusivity, respectively. This would require fitting the DKI model to the diffusion-weighted images acquired along each direction (x, y, z) prior to averaging. However, there is a growing tendency to perform only a single fit of the DKI model to the geometric means of the images acquired with diffusion-sensitizing gradient along (x, y, z), referred to as trace-weighted (TW) images. To the best of our knowledge, no in vivo studies have evaluated how TW images affect estimates of DKI-derived indices of K and D. Thus, the aim of this study was to assess the potential bias and error introduced in estimated K and D by fitting the DKI model to the TW images in HN cancer patients.

METHODS

Eighteen patients with histologically proven malignant tumors of the HN were enrolled in the study. They underwent pretreatment 3 T MRI, including DWI (b-values: 0, 500, 1000, 1500, 2000 s/mm² ). Some patients had multiple lesions, and thus a total of 34 lesions were analyzed. DKI-derived indices were estimated, voxel-by-voxel, using single diffusion-weighted images along (x, y, z) as well as TW images. A comparison between the two estimation methods was performed by calculating the percentage error in D (D_err ) and K (K_err ). Also, diffusivity anisotropy (D_anis ) and diffusional kurtosis anisotropy (K_anis ) were estimated. Agreements between the two estimation methods were assessed by Bland-Altman plots. The Spearman rank correlation test was used to study the correlations between K_err /D_err and D_anis /K_anis. RESULTS: The median (95% confidence interval) K_err and D_err were 5.1% (0.8%, 32.6%) and 1.7% (-2.5%, 5.3%), respectively. A significant relationship was observed between K_err  and D_anis (correlation coefficient R = 0.694, P < 0.0001), as well as between K_err and K_anis (R = 0.848, P < 0.0001).

CONCLUSIONS

In HN cancer, the fit of the DKI model to TW images can introduce bias and error in the estimation of K and D, which may be non-negligible for single lesions, and should hence be adopted with caution.

In Vivo Imaging Markers for Prediction of Radiotherapy Response in Patients with Nasopharyngeal Carcinoma: RESOLVE DWI versus DKI

In this prospective study, we compared the performance of readout segmentation of long variable echo trains of diffusion-weighted imaging (RESOLVE DWI) and diffusion kurtosis imaging (DKI) for the prediction of radiotherapy response in patients with nasopharyngeal carcinoma (NPC). Forty-one patients with NPC were evaluated. All patients underwent conventional MRI, RESOLVE DWI and DKI, before and after radiotherapy. All patients underwent conventional MRI every 3 months until 1 year after radiotherapy. The patients were divided into response group (RG; 36/41 patients) and no-response group (NRG; 5/41 patients) based on follow-up results. DKI (the mean of kurtosis coefficient, Kmean and the mean of diffusion coefficient, Dmean) and RESOLVE DWI (the minimum apparent diffusion coefficient, ADC_min) parameters were calculated. Parameter values at the pre-treatment period, post-treatment period, and the percentage change between these 2 periods were obtained. All parameters differed between the RG and NRG groups except for the pretreatment Dmean and ADC_min. Kmean-post was considered as an independent predictor of local control, with 87.5% sensitivity and 91.3% specificity (optimal threshold = 0.30, AUC: 0.924; 95% CI, 0.83-1.00). Kmean-post values of DKI have the potential to be used as imaging biomarkers for the early evaluation of treatment effects of radiotherapy on NPC.

Evaluation of Effects of TGF-β1 Inhibition on Gastric Cancer in Nude Mice by Diffusion Kurtosis Imaging and In-Line X-ray Phase Contrast Imaging With Sequential Histology

Background

Accurate and complete response evaluation after treatment is important to implement individualized therapy for gastric cancer.

Purpose

To investigate the effectiveness of diffusion kurtosis imaging (DKI) and in‐line X‐ray phase contrast imaging (ILXPCI) in the assessment of the therapeutic efficacy by transforming growth factor beta 1 (TGF‐β1) inhibition.

Study Type

Prospective animal study.

Animal Model

Thirty nude mice subcutaneous xenotransplantation tumor model of gastric cancer for DKI and 10 peritoneal metastasis nude mice model for ILXPCI.

Field Strength/Sequence

Examinations before and serially at 7, 14, 21, and 28 days after TGF‐β1 inhibition treatment were performed at 3T MRI including T₂‐weighted imaging (T₂WI) and DKI with five b values of 0, 500, 1000, 1500, 2000 s/mm²; ILXPCI examinations were performed at 14 days after treatment.

Assessment

DKI parameters (apparent diffusion coefficient [ADC], diffusivity [D] and kurtosis [K]) were calculated by two experienced radiologists after postprocessing.

Statistical Tests

For the differences in all the parameters between the baseline and each timepoint for both the treated and the control mice, the Mann–Whitney test was used. The Spearman correlation test was used to evaluate correlations among the DKI parameters and corresponding pathologic necrosis fraction (NF).

Results

ADC, D, and K values were significantly different between the two groups after treatment (P < 0.05). Serial measurements in the treated group showed that the ADC, D, and K values were significantly different at 7, 14, 21, and 28 days compared with baseline (P < 0.05). There were significant correlations between DKI parameters and NF (ADC, r = 0.865, P < 0.001; D, r = 0.802, P < 0.001; K, r = –0.944, P < 0.001). The ILXPCI results in the treated group showed a stronger absorption area than the control group.

Data Conclusion

DKI may be used to evaluate the complete course therapeutic effects of gastric cancer induced by TGF‐β1 inhibition, and the ILXPCI technique will improve the tumor microstructure resolution.

Level of Evidence: 1

Technical Efficacy: Stage 4

J. Magn. Reson. Imaging 2019;49:1553–1564.

Early diagnosis of radio-insensitive human nasopharyngeal carcinoma xenograft models by diffusion kurtosis imaging

OBJECTIVE

To investigate the feasibility of DKI in early detection of radio-insensitive nasopharyngeal carcinoma (NPC) xenografts in nude mice.

MATERIALS AND METHODS

Seventy-two nude mice were implanted with CNE-1 (low radio-sensitive) and CNE-2 (high radio-sensitive) NPC cell lines, and their respective xenografts were obtained. Then, the NPC-bearing nude mice were exposed to different doses of fraction irradiation, which are divided into non-irradiated group (G0), 10Gy group (G1), 20Gy group (G2), 30Gy group (G3), 3rd (G4) and 5th (G5) days after the entire dose (30y) of irradiation. Subsequently, DKI was performed on each group. Tumor volumes, shrink rates, D and K parameters were measured by two experienced radiologists. Student's t-test and receiver operating characteristic (ROC) curve analysis were conducted in this study.

RESULTS

The differences of volume shrinkage rate between CNE-1 and -2 were observed in G2 (P = 0.032), with the shrink rates of 5.954% and 27.716%, respectively. The D values were reduced at G1 (D_G1, P = 0.001) and then increased gradually after irradiation. The K values were increased at G1 (K_G1, P = 0.001) and then declined sharply in CNE-2 (P < 0.01), but not in CNE-1 xenografts (P > 0.05). The respective AUC values for D_G1 and K_G1 were 0.875 and 0.917, with 66.7% and 83.3% sensitivity and 100% specificity, at the cutoff values of 1.27 × 10^-3 mm²/s for parameter D and 0.88 for parameter K.

CONCLUSION

DKI can be used for early detection of radio-insensitive NPC xenografts prior to morphological change, where D_G1 and K_G1 may be the most valuable indicators.

Integrating dynamic contrast-enhanced magnetic resonance imaging and diffusion kurtosis imaging for neoadjuvant chemotherapy assessment of nasopharyngeal carcinoma

BACKGROUND

Since neoadjuvant chemotherapy (NAC) has proven a benefit for locally advanced nasopharyngeal carcinoma (NPC), early response evaluation after chemotherapy is important to implement individualized therapy for NPC in the era of precision medicine.

PURPOSE

To determine the combined and independent contribution between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion kurtosis imaging (DKI) in the early monitoring of NAC response for NPC.

STUDY TYPE

Prospective.

POPULATION

Fifty-three locally advanced NPC patients.

FIELD STRENGTH/SEQUENCE

Four examinations before and at 4, 20, and 40 days after NAC initiation were performed at 3T MRI including DCE-MRI and DKI (b values = 0, 500, 1000, 1500 s/mm² ).

ASSESSMENT

DCE-MRI parameters (K^trans [the volume transfer constant of Gd-DTPA], k_ep [rate constant], ν_e [the extracellular volume fraction of the imaged tissue], and ν_p [the blood volume fraction]) and DKI parameters (D_app [apparent diffusion for non-Gaussian distribution] and K_app [apparent kurtosis coefficient]) were analyzed using dedicated software.

STATISTICAL TESTS

MRI parameters and their corresponding changes were compared between responders and nonresponders after one or two NAC cycles treatment using independent-samples Student's t-test or Mann-Whitney U-test depending on the normality contribution test and then followed by logistic regression and receiver operating characteristic curve (ROC) analyses.

RESULTS

The responder group (RG) patients presented significantly higher mean K^trans and D_app values at baseline and larger Δ K ( 0 - 4 ) trans , Δv_p(0-4) , and ΔD_app(0-4) values after either one or two NAC cycles compared with the nonresponder group (NRG) patients (all P < 0.05). ROC analyses demonstrated the higher diagnostic accuracy of combined DCE-MRI and DKI model to distinguish nonresponders from responders after two NAC cycles than using DCE-MRI (0.987 vs. 0.872, P = 0.033) or DKI (0.987 vs. 0.898, P = 0.047) alone.

DATA CONCLUSION

Combined DCE-MRI and DKI models had higher diagnostic accuracy for NAC assessment compared with either model used independently.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1208-1216.

Histogram analysis of diffusion kurtosis imaging of nasopharyngeal carcinoma: Correlation between quantitative parameters and clinical stage

Purpose

To evaluate the correlation between histogram parameters derived from diffusion-kurtosis (DK) imaging and the clinical stage of nasopharyngeal carcinoma (NPC).

Results

High T-stage (T3/4) NPC showed significantly higher K_app-mean (P = 0.018), K_app-median (P = 0.029) and K_app-90th (P = 0.003) than low T-stage (T1/2) NPC. High N-stage NPC (N2/3) showed significantly lower Dapp-mean (P = 0.002), Dapp-median (P = 0.002) and Dapp-10th (P < 0.001) than low N-stage NPC (N0/1). High AJCC-stage NPC (III/IV) showed significantly lower D_app-10th (P = 0.038) than low AJCC-stage NPC (I/II). ROC analyses indicated that Kapp-90th was optimal for predicting high T-stage (AUC, 0.759; sensitivity, 0.842; specificity, 0.607), while Dapp-10th was best for predicting high N- and AJCC-stage (N-stage, AUC, 0.841; sensitivity, 0.875; specificity, 0.807; AJCC-stage, AUC, 0.671; sensitivity, 0.800; specificity, 0.588).

Materials and Methods

DK imaging data of forty-seven consecutive NPC patients were retrospectively analyzed. Apparent diffusion for Gaussian distribution (D_app) and apparent kurtosis coefficient (K_app) were generated using diffusion-kurtosis model. Histogram parameters, including mean, median, 10th, 90th percentiles, skewness and kurtosis of D_app and K_app were calculated. Patients were divided into low and high T, N and clinical stage based on American Joint Committee on Cancer (AJCC) staging system. Differences of histogram parameters between low and high T, N and AJCC stages were compared using t test. Multiple receiver operating characteristic (ROC) curves were used to determine and compare the value of significant parameters in predicting high T, N and AJCC stage, respectively.

Conclusions

DK imaging-derived parameters correlated well with clinical stage of NPC, therefore could serve as an adjunctive imaging technique for evaluating NPC.

Utility of Readout-Segmented Echo-Planar Imaging-Based Diffusion Kurtosis Imaging for Differentiating Malignant from Benign Masses in Head and Neck Region

Objective

To compare the diagnostic performance of readout-segmented echo-planar imaging (RS-EPI)-based diffusion kurtosis imaging (DKI) and that of diffusion-weighted imaging (DWI) for differentiating malignant from benign masses in head and neck region.

Materials and Methods

Between December 2014 and April 2016, we retrospectively enrolled 72 consecutive patients with head and neck masses who had undergone RS-EPI-based DKI scan (b value of 0, 500, 1000, and 1500 s/mm²) for pretreatment evaluation. Imaging data were post-processed by using monoexponential and diffusion kurtosis (DK) model for quantitation of apparent diffusion coefficient (ADC), apparent diffusion for Gaussian distribution (D_app), and apparent kurtosis coefficient (K_app). Unpaired t test and Mann-Whitney U test were used to compare differences of quantitative parameters between malignant and benign groups. Receiver operating characteristic curve analyses were performed to determine and compare the diagnostic ability of quantitative parameters in predicting malignancy.

Results

Malignant group demonstrated significantly lower ADC (0.754 ± 0.167 vs. 1.222 ± 0.420, p < 0.001) and D_app (1.029 ± 0.226 vs. 1.640 ± 0.445, p < 0.001) while higher K_app (1.344 ± 0.309 vs. 0.715 ± 0.249, p < 0.001) than benign group. Using a combination of D_app and K_app as diagnostic index, significantly better differentiating performance was achieved than using ADC alone (area under curve: 0.956 vs. 0.876, p = 0.042).

Conclusion

Compared to DWI, DKI could provide additional data related to tumor heterogeneity with significantly better differentiating performance. Its derived quantitative metrics could serve as a promising imaging biomarker for differentiating malignant from benign masses in head and neck region.

Non-invasive prediction of the tumor growth rate using advanced diffusion models in head and neck squamous cell carcinoma patients

We assessed parameters of advanced diffusion weighted imaging (DWI) models for the prediction of the tumor growth rate in 55 head and neck squamous cell carcinoma (HNSCC) patients. The DWI acquisition used single-shot spin-echo echo-planar imaging with 12 b-values (0−2000). We calculated 14 DWI parameters using mono-exponential, bi-exponential, tri-exponential, stretched exponential and diffusion kurtosis imaging models. We directly measured the tumor growth rate from two sets of different-date imaging data. We divided the patients into a discovery group (n = 40) and validation group (n = 15) based on their MR acquisition dates. In the discovery group, we performed univariate and multivariate regression analyses to establish the multiple regression equation for the prediction of the tumor growth rate using diffusion parameters. The equation obtained with the discovery group was applied to the validation group for the confirmation of the equation's accuracy. After the univariate and multivariate regression analyses in the discovery-group patients, the estimated tumor growth rate equation was established by using the significant parameters of intermediate diffusion coefficient D₂ and slow diffusion coefficient D₃ obtained by the tri-exponential model. The discovery group's correlation coefficient between the estimated and directly measured tumor growth rates was 0.74. In the validation group, the correlation coefficient (r = 0.66) and intra-class correlation coefficient (0.65) between the estimated and directly measured tumor growth rates were respectively good. In conclusion, advanced DWI model parameters can be a predictor for determining HNSCC patients’ tumor growth rate.

Diffusion kurtosis imaging of a human nasopharyngeal carcinoma xenograft model: Initial experience with pathological correlation

PURPOSE

The aim of this study was to investigate the relationship between diffusion kurtosis imaging (DKI)-related parameters and pathological measures using human nasopharyngeal carcinoma (NPC) xenografts in a nude mouse model.

MATERIALS AND METHODS

Twenty-six BALB/c-nu nude mice were divided into two groups that were injected with two different nasopharyngeal squamous cell carcinoma cell lines (CNE1 and CNE2). DK magnetic resonance (MR) imaging was performed on a 3.0 Tesla MR scanner. DWI and DKI-related parameters, including apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) were measured. Mice were euthanatized when the maximum diameter of the primary tumor reached 1.5cm after MR scanning. Tumor tissues were then processed for hematoxylin and eosin staining. The pathological images were analyzed using a computer-aided pixel-wise clustering method to evaluate tumor cellular density, nuclei portion, cytoplasm portion, extracellular space portion, the ratio of nuclei to cytoplasm and the ratio of nuclei to extracellular space. The relationships between DWI and DKI-related parameters and pathological features were analyzed statistically.

RESULTS

The ADC and MD values of the CNE1 group (1.16±0.24×10^-3mm²/s, 2.28±0.29×10^-3mm²/s) was higher than that of the CNE2 group (0.82±0.14×10^-3mm²/s, 1.53±0.24×10^-3mm²/s, P<0.001), but the MK values between the two groups were not significantly different (CNE1: 0.55±0.14; CNE2: 0.47±0.23; P>0.05). A Pearson test showed that the ADC and MD values were significantly correlated with cellular density, nuclei portion, extracellular space portion and the ratio of nuclei to extracellular space (r=-0.861; -0.909, P<0.001; r=-0.487; 0.591, P<0.05; r=0.567; 0.625, P<0.05; r=-0.645; -0.745, P<0.001, respectively). The MK values were significantly correlated with nuclei portion, cytoplasm portion and the ratio of nuclei to cytoplasm (r=-0.475, P<0.05; r=0.665, P<0.001; r=-0.494, P<0.05, respectively).

CONCLUSION

The preliminary animal results suggest that DKI findings can provide valuable bio-information for NPC tissue characterization. DKI imaging might be utilized as a surrogate biomarker for the non-invasive assessment of tumor microstructures.

Diffusion kurtosis imaging evaluating epithelial-mesenchymal transition in colorectal carcinoma xenografts model: a preliminary study

Epithelial-mesenchymal transition (EMT) plays an important role in aggravating invasiveness and metastatic behavior of colorectal cancer (CRC). Identification of EMT is important for structuring treatment strategy, but has not yet been studied by using noninvasive imaging modality. Diffusion kurtosis imaging (DKI) is an advanced diffusion weighted model that could reflect tissue microstructural changes in vivo. In this study, EMT was induced in CRC cells (HCT116) by overexpressing Snail1 gene. We aimed to investigate the value of DKI in identifying EMT in CRC and decipher the correlations between DKI-derived parameters and EMT biomarker E-cadherin and cell proliferative index Ki-67 expression. Our results revealed that HCT116/Snail1 cells presented changes consistent with EMT resulting in significant increase in migration and invasion capacities. DKI could identify CRC with EMT, in which the DKI-derived parameter diffusivity was significantly lower, and kurtosis was significantly higher than those in the CRC/Control. Diffusivity was negatively and kurtosis was positively correlated with Ki-67 expression, whereas diffusivity was positively and kurtosis was negatively correlated with E-cadherin expression. Therefore, our study concluded that DKI can identify EMT in CRC xenograft tumors. EMT-contained CRC tumors with high Ki-67 and low E-cadherin expression were vulnerable to have lower diffusivity and higher kurtosis coefficients.

Diffusion-kurtosis imaging predicts early radiotherapy response in nasopharyngeal carcinoma patients

In this prospective study, we analyzed diffusion kurtosis imaging (DKI) parameters to predict the early response to radiotherapy in 23 nasopharyngeal carcinoma (NPC) patients. All patients underwent conventional magnetic resonance imaging (MRI) and DKI before and after radiotherapy. The patients were divided into response (RG; no residual tumors; 16/23 patients) and no-response (NRG; residual tumors; 7/23 patients) groups, based on MRI and biopsy results 3 months after radiotherapy. The maximum diameter of tumors in RG and NRG patients were similar prior to radiotherapy (p=0.103). The pretreatment diffusion coefficient (D) parameters (D_axis, D_mean and D_rad) were higher in RG than NRG patients (p=0.022, p=0.027 and p=0.027). Conversely, the pre-treatment fractional anisotropy (FA) and kurtosis coefficient (K) parameters (K_axis, K_fa, K_mean, K_rad and Mkt) were lower in RG than NRG patients (p=0.015, p=0.022, p=0.008, p=0.004, p=0.001, p=0.002). The K_rad coefficient (0.76) was the best parameter to predict the radiotherapy response. Based on receiver operating characteristic curve analysis K_rad showed 71.4% sensitivity and 93.7% specificity (AUC: 0.897, 95% CI, 0.756-1). Multivariate analysis indicated DKI parameters were independent prognostic factors for the short-term effect in NPC. Thus, DKI predicts the early response to radiotherapy in NPC patients.

The value of diffusion kurtosis imaging in assessing pathological complete response to neoadjuvant chemoradiation therapy in rectal cancer: a comparison with conventional diffusion-weighted imaging

Objectives

The aim of this study is to comprehensively evaluate the advantage of diffusion kurtosis imaging (DKI) in distinguishing pathological complete response (pCR) from non-pCR patients with locally advanced rectal cancer (LARC) after neoadjuvant chemoradiation therapy (CRT) in comparison to conventional diffusion-weighted imaging (DWI).

Material and Methods

Fifty-six consecutive patients diagnosed with LARC were prospectively enrolled and underwent pre- and post-CRT MRI on a 3.0 T MRI scanner. Apparent diffusion coefficient (ADC), mean diffusion (MD) and mean kurtosis (MK) values of the tumor were measured in pre- and post-CRT phases and then compared to histopathologic findings after total mesorectal excision (TME). Both Mann-Whitney U-test and Kruskal-Wallis test were used as statistical methods. Diagnostic performance was determined using receiver operating characteristic (ROC) curve analysis.

Results

For a total of 56 rectal lesions (pCR, n = 14; non-pCR, n = 42), the MK_pre and MK_post values were much lower for the pCR patients (mean±SD, 0.72±0.09 and 0.56±0.06, respectively) than those for the non-pCR patients (0.89±0.11 and 0.68±0.08, respectively) (p < 0.001). The ADC_post and the change ratio of apparent diffusion coefficient (ADC_ratio) values was significantly higher for the pCR patients (mean±SD, 1.31±0.13 and 0.64±0.34, respectively) than for the non-pCR patients (1.12±0.16 and 0.33±0.27, respectively) (p < 0.001 and p = 0.001, respectively). In addition, the MD_post and the change ratio of mean diffusion (MD_ratio) (2.45±0.33 vs. 1.95±0.30, p < 0.001; 0.80±0.43 vs. 0.35±0.32, p < 0.001, respectively) also increased, whereas the ADC_pre, MD_pre and the change ratio of mean kurtosis (MK_ratio) of the pCR (0.82±0.11, 1.40±0.21, and 0.23±0.010, respectively) exhibited a neglectable difference with that of the non-pCR (p = 0.332, 0.269, and 0.678, respectively). The MK_post showed relatively high sensitivity (92.9%) and high specificity (83.3%) in comparison to other image indices. The area under the receiver operating characteristic curve (AUROC) that is available for the assessment of pCR using MK_post (0.908, cutoff value = 0.6196) were larger than other parameters and the overall accuracy of MK_post (85.7%) was the highest.

Conclusions

Both DKI and conventional DWI hold great potential in predicting treatment response to neoadjuvant chemoradiation therapy in rectal cancer. The DKI parameters, especially MK_post, showed a higher specificity than conventional DWI in assessing pCR and non-pCR in patients with LARC, but the pre-CRT ADC and MD are unreliable.

[Selected clinically established and scientific techniques of diffusion-weighted MRI. In the context of imaging in oncology]

BACKGROUND

Diffusion-weighted imaging (DWI) is a magnetic resonance imaging (MRI) technique that was established in the clinical routine primarily for the detection of brain ischemia. In the past 15 years its clinical use has been extended to oncological radiology, as tumor and metastases can be depicted in DWI due to their hypercellular nature.

PRINCIPLES

The basis of DWI is the Stejskal-Tanner experiment. The diffusion properties of tissue can be visualized after acquisition of at least two diffusion-weighted series using echo planar imaging and a specific sequence of gradient pulses.

CLINICAL APPLICATIONS

The use of DWI in prostate MRI was reported to be one of the first established applications that found its way into internationally recognized clinical guidelines of the European Society of Urological Radiology (ESUR) and the prostate imaging reporting and data system (PI-RADS) scale. Due to recently reported high specificity and negative predictive values of 94% and 92%, respectively, its regular use for breast MRI is expected in the near future. Furthermore, DWI can also reliably be used for whole-body imaging in patients with multiple myeloma or for measuring the extent of bone metastases.

OUTLOOK

New techniques in DWI, such as intravoxel incoherent motion imaging, diffusion kurtosis imaging and histogram-based analyses represent promising approaches to achieve a more quantitative evaluation for tumor detection and therapy response.

Therapy Monitoring with Functional and Molecular MR Imaging

Cancer therapy is mainly based on different combinations of surgery, radiotherapy, and chemotherapy. Additionally, targeted therapies (designed to disrupt specific tumor hallmarks, such as angiogenesis, metabolism, proliferation, invasiveness, and immune evasion), hormonotherapy, immunotherapy, and interventional techniques have emerged as alternative oncologic treatments. Conventional imaging techniques and current response criteria do not always provide the necessary information regarding therapy success particularly to targeted therapies. In this setting, MR imaging offers an attractive combination of anatomic, physiologic, and molecular information, which may surpass these limitations, and is being increasingly used for therapy response assessment.

Functional magnetic resonance imaging techniques and their development for radiation therapy planning and monitoring in the head and neck cancers

Radiation therapy (RT), in particular intensity-modulated radiation therapy (IMRT), is becoming a more important nonsurgical treatment strategy in head and neck cancer (HNC). The further development of IMRT imposes more critical requirements on clinical imaging, and these requirements cannot be fully fulfilled by the existing radiotherapeutic imaging workhorse of X-ray based imaging methods. Magnetic resonance imaging (MRI) has increasingly gained more interests from radiation oncology community and holds great potential for RT applications, mainly due to its non-ionizing radiation nature and superior soft tissue image contrast. Beyond anatomical imaging, MRI provides a variety of functional imaging techniques to investigate the functionality and metabolism of living tissue. The major purpose of this paper is to give a concise and timely review of some advanced functional MRI techniques that may potentially benefit conformal, tailored and adaptive RT in the HNC. The basic principle of each functional MRI technique is briefly introduced and their use in RT of HNC is described. Limitation and future development of these functional MRI techniques for HNC radiotherapeutic applications are discussed. More rigorous studies are warranted to translate the hypotheses into credible evidences in order to establish the role of functional MRI in the clinical practice of head and neck radiation oncology.

Advanced imaging techniques in the therapeutic response of transarterial chemoembolization for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the major causes of morbidity and mortality in patients with chronic liver disease. Transarterial chemoembolization (TACE) can significantly improve the survival rate of patients with HCC and is the first treatment choice for patients who are not suitable for surgical resections. The evaluation of the response to TACE treatment affects not only the assessment of the therapy efficacy but also the development of the next step in the treatment plan. The use of imaging to examine changes in tumor volume to assess the response of solid tumors to treatment has been controversial. In recent years, the emergence of new imaging technology has made it possible to observe the response of tumors to treatment prior to any morphological changes. In this article, the advances in studies reporting the use of computed tomography perfusion imaging, diffusion-weighted magnetic resonance imaging (MRI), intravoxel incoherent motion, diffusion kurtosis imaging, magnetic resonance spectroscopy, magnetic resonance perfusion-weighted imaging, blood oxygen level-dependent MRI, positron emission tomography (PET)/computed tomography and PET/MRI to assess the TACE treatment response are reviewed.

Diffusion-Weighted Imaging of Nasopharyngeal Carcinoma: Can Pretreatment DWI Predict Local Failure Based on Long-Term Outcome?

BACKGROUND AND PURPOSE

Pretreatment prediction of patients with nasopharyngeal carcinoma who will fail conventional treatment would potentially allow these patients to undergo more intensive treatment or closer posttreatment monitoring. The aim of the study was to determine the ability of pretreatment DWI to predict local failure in patients with nasopharyngeal carcinoma based on long-term clinical outcome.

MATERIALS AND METHODS

One hundred fifty-eight patients with pretreatment DWI underwent analysis of the primary tumor to obtain the ADC mean, ADC skewness, ADC kurtosis, volume, and T-stage. Univariate and multivariate analyses using logistic regression were performed to compare the ADC parameters, volume, T-stage, and patient age in primary tumors with local failure and those with local control, by using a minimum of 5-year follow-up to confirm local control.

RESULTS

Local control was achieved in 131/158 (83%) patients (range, 60.3-117.7 months) and local failure occurred in 27/158 (17%) patients (range, 5.2-79.8 months). Compared with tumors with local control, those with local failure showed a significantly lower ADC skewness (ADC values with the greatest frequencies were shifted away from the lower ADC range) (P = .006) and lower ADC kurtosis (curve peak broader) (P = .024). The ADC skewness remained significant on multivariate analysis (P = .044). There was a trend toward higher tumor volumes in local failure, but the volume, together with T-stage and ADC mean, were not significantly different between the 2 groups.

CONCLUSIONS

Pretreatment DWI of primary tumors found that the skewness of the ADC distribution curve was a predictor of local failure in patients with nasopharyngeal carcinoma, based on long-term clinical outcome.

Body diffusion kurtosis imaging: Basic principles, applications, and considerations for clinical practice

Technologic advances enable performance of diffusion-weighted imaging (DWI) at ultrahigh b-values, where standard monoexponential model analysis may not apply. Rather, non-Gaussian water diffusion properties emerge, which in cellular tissues are, in part, influenced by the intracellular environment that is not well evaluated by conventional DWI. The novel technique, diffusion kurtosis imaging (DKI), enables characterization of non-Gaussian water diffusion behavior. More advanced mathematical curve fitting of the signal intensity decay curve using the DKI model provides an additional parameter Kapp that presumably reflects heterogeneity and irregularity of cellular microstructure, as well as the amount of interfaces within cellular tissues. Although largely applied for neural applications over the past decade, a small number of studies have recently explored DKI outside the brain. The most investigated organ is the prostate, with preliminary studies suggesting improved tumor detection and grading using DKI. Although still largely in the research phase, DKI is being explored in wider clinical settings. When assessing extracranial applications of DKI, careful attention to details with which body radiologists may currently be unfamiliar is important to ensure reliable results. Accordingly, a robust understanding of DKI is necessary for radiologists to better understand the meaning of DKI-derived metrics in the context of different tumors and how these metrics vary between tumor types and in response to treatment. In this review, we outline DKI principles, propose biostructural basis for observations, provide a comparison with standard monoexponential fitting and the apparent diffusion coefficient, report on extracranial clinical investigations to date, and recommend technical considerations for implementation in body imaging.