Diffusion-weighted imaging in head and neck cancers

Differentiation of Benign and Malignant Neck Neoplastic Lesions Using Diffusion-Weighted Magnetic Resonance Imaging

The most difficult diagnostic challenge in neck imaging is the differentiation between benign and malignant neoplasms. The purpose of this work was to study the role of the ADC (apparent diffusion coefficient) value in discriminating benign from malignant neck neoplastic lesions. The study was conducted on 53 patients with different neck pathologies (35 malignant and 18 benign/inflammatory). In all of the subjects, conventional MRI (magnetic resonance imaging) sequences were performed apart from DWI (diffusion-weighted imaging). The mean ADC values in the benign and malignant groups were compared using the Mann-Whitney test. The ADCs of malignant lesions (mean 0.86 ± 0.28) were significantly lower than the benign lesions (mean 1.43 ± 0.57), and the mean ADC values of the inflammatory lesions (1.19 ± 0.75) were significantly lower than those of the benign lesions. The cutoff value of 1.1 mm2/s effectively differentiated benign and malignant lesions with a 97.14% sensitivity, a 77.78% specificity, and an 86.2% accuracy. There were also statistically significant differences between the ADC values of different malignant tumors of the neck (p, 0.001). NHL (0.59 ± 0.09) revealed significantly lower ADC values than SCC (0.93 ± 0.15). An ADC cutoff point of 0.7 mm2/s was the best for differentiating NHL (non-Hodgkin lymphoma) from SCC (squamous cell carcinoma); it provided a diagnostic ability of 100.0% sensitivity and 89.47% specificity. ADC mapping may be an effective MRI tool for the differentiation of benign and inflammatory lesions from malignant tumors in the neck.

Evaluation of the efficacy of diffusion-weighted magnetic resonance imaging and apparent diffusion coefficients in the diagnosis of maxillary diseases

OBJECTIVE

We investigated the efficacy of using diffusion-weighted imaging (DWI) with quantitative apparent diffusion coefficient (ADC) mapping in the diagnosis of maxillary diseases.

STUDY DESIGN

We evaluated 146 cases of maxillary diseases (32 malignant tumors, 11 benign tumors, 28 maxillary cysts, 60 cases of maxillary sinusitis, and 15 maxillary sinus retention cysts) that had been examined using magnetic resonance imaging. The DWI sequence was obtained with b values of 0 and 800 s/mm2 and ADC values were calculated. We used one-way analysis of variance and the Tukey honestly significant difference test to identify differences within and between the types of diseases.

RESULTS

Mean ADC values for malignant tumors (1.07 × 10-3 mm2 s-1) were significantly lower than ADCs for benign tumors (1.85 × 10-3 mm2 s-1), maxillary cysts (1.77 × 10-3 mm2 s-1), maxillary sinusitis (2.34 × 10-3 mm2 s-1), and maxillary sinus retention cysts (2.52 × 10-3 mm2 s-1), with P < 0.001.   Mean ADC differed significantly between all disease types except between maxillary sinusitis and maxillary sinus retention cysts. ADC values also significantly differed between specific lesions within the malignant tumor and maxillary cyst groups.

CONCLUSIONS

The use of ADC values can be useful in the differential diagnosis of malignant maxillary diseases, benign lesions, cysts, and inflammatory and reactive conditions.

A Quantitative Multiparametric MRI Analysis Platform for Estimation of Robust Imaging Biomarkers in Clinical Oncology

There is a need to develop user-friendly imaging tools estimating robust quantitative biomarkers (QIBs) from multiparametric (mp)MRI for clinical applications in oncology. Quantitative metrics derived from (mp)MRI can monitor and predict early responses to treatment, often prior to anatomical changes. We have developed a vendor-agnostic, flexible, and user-friendly MATLAB-based toolkit, MRI-Quantitative Analysis and Multiparametric Evaluation Routines ("MRI-QAMPER", current release v3.0), for the estimation of quantitative metrics from dynamic contrast-enhanced (DCE) and multi-b value diffusion-weighted (DW) MR and MR relaxometry. MRI-QAMPER's functionality includes generating numerical parametric maps from these methods reflecting tumor permeability, cellularity, and tissue morphology. MRI-QAMPER routines were validated using digital reference objects (DROs) for DCE and DW MRI, serving as initial approval stages in the National Cancer Institute Quantitative Imaging Network (NCI/QIN) software benchmark. MRI-QAMPER has participated in DCE and DW MRI Collaborative Challenge Projects (CCPs), which are key technical stages in the NCI/QIN benchmark. In a DCE CCP, QAMPER presented the best repeatability coefficient (RC = 0.56) across test-retest brain metastasis data, out of ten participating DCE software packages. In a DW CCP, QAMPER ranked among the top five (out of fourteen) tools with the highest area under the curve (AUC) for prostate cancer detection. This platform can seamlessly process mpMRI data from brain, head and neck, thyroid, prostate, pancreas, and bladder cancer. MRI-QAMPER prospectively analyzes dose de-escalation trial data for oropharyngeal cancer, which has earned it advanced NCI/QIN approval for expanded usage and applications in wider clinical trials.

Response Assessment of Primary Liver Tumors to Novel Therapies: an Imaging Perspective

The latest developments in cancer immunotherapy, namely the introduction of immune checkpoint inhibitors, have led to a fundamental change in advanced cancer treatments. Imaging is crucial to identify tumor response accurately and delineate prognosis in immunotherapy-treated patients. Simultaneously, advances in image acquisition techniques, notably functional and molecular imaging, have facilitated more accurate pretreatment evaluation, assessment of response to therapy, and monitoring for tumor recurrence. Traditional approaches to assessing tumor progression, such as RECIST, rely on changes in tumor size, while new strategies for evaluating tumor response to therapy, such as the mRECIST and the EASL, rely on tumor enhancement. Moreover, the assessment of tumor volume, enhancement, cellularity, and perfusion are some novel techniques that have been investigated. Validation of these novel approaches should rely on comparing their results with those of standard evaluation methods (EASL, mRECIST) while considering the ultimate outcome, which is patient survival. More recently, immunotherapy has been used in the management of primary liver tumors. However, little is known about its efficacy. This article reviews imaging modalities and techniques for assessing tumor response and survival in immunotherapy-treated patients with primary hepatic malignancies.

Multi-parametric MRI for radiotherapy simulation

Magnetic resonance imaging (MRI) has become an important imaging modality in the field of radiotherapy (RT) in the past decade, especially with the development of various novel MRI and image-guidance techniques. In this review article, we will describe recent developments and discuss the applications of multi-parametric MRI (mpMRI) in RT simulation. In this review, mpMRI refers to a general and loose definition which includes various multi-contrast MRI techniques. Specifically, we will focus on the implementation, challenges, and future directions of mpMRI techniques for RT simulation.

Precise differentiation between jugular foramen paragangliomas and metastases: utility of diffusion-weighted and dynamic contrast-enhanced magnetic resonance imaging

PURPOSE

This study tested the utility of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced imaging (DCE-MRI) in differentiating paragangliomas and metastases in the jugular foramen in combination with conventional imaging.

METHODS

Forty-nine consecutive patients with paragangliomas or metastases between January 2015 and April 2022 were included in this retrospective study. All patients had pretreatment DWI and DCE-MRI. Between paragangliomas and metastases, normalized apparent diffusion coefficient (nADCmean) and DCE-MRI parameters were compared along with conventional imaging features (enhancement pattern, presence of flow voids, cystic/necrotic change, and bone erosion). The diagnostic performance was tested using receiver operating characteristic (ROC) analysis.

RESULTS

Thirty-five paragangliomas (5 male; median 49 years) and 14 metastases (9 male; median 61 years) were analyzed. The most common 3 primary cancers included 4 lung cancers, 3 breast cancers, and 3 melanomas. The presence of flow void was significantly different between paragangliomas and metastases (21/35 vs 2/14; P = 0.0047) in conventional imaging features, while fractional plasma volume (Vp) was significantly different between the two tumor types (median 0.46 vs 0.19; P < 0.001) in DWI and DCE-MRI parameters. The areas under the ROC curves (AUCs) of the presence of flow void and Vp were 0.72 and 0.93, respectively. The AUC of the combination of the presence of flow void and Vp was 0.95 and significantly improved compared to that of the presence of flow void (P < 0.001).

CONCLUSION

Adding DCE-MRI to the head and neck protocol can aid in the precise differentiation between jugular foramen paragangliomas and metastases.

Quality assurance assessment of intra-acquisition diffusion-weighted and T2-weighted magnetic resonance imaging registration and contour propagation for head and neck cancer radiotherapy

BACKGROUND/PURPOSE

Adequate image registration of anatomical and functional magnetic resonance imaging (MRI) scans is necessary for MR-guided head and neck cancer (HNC) adaptive radiotherapy planning. Despite the quantitative capabilities of diffusion-weighted imaging (DWI) MRI for treatment plan adaptation, geometric distortion remains a considerable limitation. Therefore, we systematically investigated various deformable image registration (DIR) methods to co-register DWI and T2-weighted (T2W) images.

MATERIALS/METHODS

We compared three commercial (ADMIRE, Velocity, Raystation) and three open-source (Elastix with default settings [Elastix Default], Elastix with parameter set 23 [Elastix 23], Demons) post-acquisition DIR methods applied to T2W and DWI MRI images acquired during the same imaging session in twenty immobilized HNC patients. In addition, we used the non-registered images (None) as a control comparator. Ground-truth segmentations of radiotherapy structures (tumour and organs at risk) were generated by a physician expert on both image sequences. For each registration approach, structures were propagated from T2W to DWI images. These propagated structures were then compared with ground-truth DWI structures using the Dice similarity coefficient and mean surface distance.

RESULTS

19 left submandibular glands, 18 right submandibular glands, 20 left parotid glands, 20 right parotid glands, 20 spinal cords, and 12 tumours were delineated. Most DIR methods took <30 s to execute per case, with the exception of Elastix 23 which took ∼458 s to execute per case. ADMIRE and Elastix 23 demonstrated improved performance over None for all metrics and structures (Bonferroni-corrected p < 0.05), while the other methods did not. Moreover, ADMIRE and Elastix 23 significantly improved performance in individual and pooled analysis compared to all other methods.

CONCLUSIONS

The ADMIRE DIR method offers improved geometric performance with reasonable execution time so should be favoured for registering T2W and DWI images acquired during the same scan session in HNC patients. These results are important to ensure the appropriate selection of registration strategies for MR-guided radiotherapy.

Correlation Between Apparent Diffusion Coefficient and the Ki-67 Proliferation Index in Grading Pediatric Glioma

OBJECTIVE

This study aimed to investigate the correlation between apparent diffusion coefficient (ADC) and the Ki-67 proliferation index with the pathologic grades of pediatric glioma and to compare their diagnostic performance in differentiating grades of pediatric glioma.

PATIENTS AND METHODS

Magnetic resonance imaging examinations and histopathologies of 121 surgically treated pediatric gliomas (87 low-grade gliomas [LGGs; grades 1 and 2] and 34 high-grade gliomas [HGGs; grades 3 and 4]) were retrospectively reviewed. The mean tumor ADC (ADCmean), minimum tumor ADC (ADCmin), tumor/normal brain ADC ratio (ADC ratio), and value of the Ki-67 proliferation index of LGGs and HGGs were compared. Correlation coefficients were calculated for ADC parameters and Ki-67 values. The receiver operating characteristic curve was used to determine the diagnostic value of ADCmean, ADCmin, ADC ratio, and Ki-67 proliferation index for differentiating LGGs and HGGs.

RESULTS

The ADC values were significantly negatively correlated with glioma grade, and the Ki-67 proliferation index had a significant positive correlation with glioma grade. A significant negative correlation was observed between ADCmean and Ki-67 proliferation index, between ADCmin and Ki-67 proliferation index, and between ADC ratio and Ki-67 proliferation index. The receiver operating characteristic analysis demonstrated moderate to good accuracy for ADCmean in discriminating LGGs from HGGs (area under the curve [AUC], 0.875; sensitivity, 79.3%; specificity, 82.4%; accuracy, 80.2%; positive predictive value [PPV], 92.0%; and negative predictive value [NPV], 60.9% [cutoff value, 1.187] [×10-3 mm2/s]). Minimum tumor ADC showed very good to excellent accuracy with AUC of 0.946, sensitivity of 86.2%, specificity of 94.1%, accuracy of 88.4%, PPV of 97.4%, and NPV of 72.7% (cutoff value, 0.970) (×10-3 mm2/s). The ADC ratio showed moderate to good accuracy with AUC of 0.854, sensitivity of 72.4%, specificity of 88.2%, accuracy of 76.9%, PPV of 94.0%, and NPV of 55.6% (cutoff value, 1.426). For the parameter of the Ki-67 proliferation index, in discriminating LGGs from HGGs, very good to excellent diagnostic accuracy was observed (AUC, 0.962; sensitivity, 94.1%; specificity, 89.7%; accuracy, 90.9%; PPV, 97.5%; and NPV, 78.0% [cutoff value, 7]).

CONCLUSIONS

Apparent diffusion coefficient parameters and the Ki-67 proliferation index were significantly correlated with histological grade in pediatric gliomas. Apparent diffusion coefficient was closely correlated with the proliferative potential of pediatric gliomas. In addition, ADCmin showed superior performance compared with ADCmean and ADC ratio in differentiating pediatric glioma grade, with a close diagnostic efficacy to the Ki-67 proliferation index.

Assessing the variability and correlation between SUV and ADC parameters of head and neck cancers derived from simultaneous PET/MRI: A single-center study

OBJECTIVE

Intratumoral heterogeneity is associated with poor outcomes in head and neck cancer (HNC) patients owing to chemoradiotherapy resistance. [¹⁸ F]-FDG positron emission tomography (PET) / Magnetic Resonance Imaging (MRI) provides spatial information about tumor mass, allowing intratumor heterogeneity assessment through histogram analysis. However, variability in quantitative PET/MRI parameter measurements could influence their reliability in assessing patient prognosis. Therefore, to use standardized uptake value (SUV) and apparent diffusion coefficient (ADC) parameters for assessing tumor response, this study aimed to measure SUV and ADC's variability and assess their relationship in HNC.

METHODS

First, ADC variability was measured in an in-house diffusion phantom and in five healthy volunteers. The SUV variability was only measured with the NEMA phantom using a clinical imaging protocol. Furthermore, simultaneous PET/MRI data of 11 HNC patients were retrospectively collected from the National Cyclotron and PET center in Chulabhorn Hospital. Tumor contours were manually drawn from PET images by an experienced nuclear medicine radiologist before tumor volume segmentation. Next, SUV and ADC's histogram were used to extract statistic variables of ADC and SUV: mean, median, min, max, skewness, kurtosis, and 5^th , 10^th , 25^th , 50^th , 75^th , 90^th , and 95^th percentiles. Finally, the correlation between the statistic variables of ADC and SUV, as well as Metabolic Tumor volume and Total Lesion Glycolysis parameters was assessed using Pearson's correlation.

RESULTS

This pilot study showed that both parameters' maximum coefficient of variation was 13.9% and 9.8% in the phantom and in vivo, respectively. Furthermore, we found a strong and negative correlation between SUV_max and ADV_med (r = -0.75, P = 0.01).

CONCLUSION

The SUV and ADC obtained by simultaneous PET/MRI can be potentially used as an imaging biomarker for assessing intratumoral heterogeneity in patients with HNC. The low variability and relationship between SUV and ADC could allow multimodal prediction of tumor response in future studies.

Contemporary Imaging and Reporting Strategies for Head and Neck Cancer: MRI, FDG PET/MRI, NI-RADS, and Carcinoma of Unknown Primary-AJR Expert Panel Narrative Review

CT, MRI, and FDG PET/CT play major roles in the diagnosis, staging, treatment planning, and surveillance of head and neck cancers. Nonetheless, an evolving understanding of head and neck cancer pathogenesis, advances in imaging techniques, changing treatment regimens, and a lack of standardized guidelines have led to areas of uncertainty in the imaging of head and neck cancer. This narrative review aims to address four issues in the contemporary imaging of head and neck cancer. The first issue relates to the standard and advanced sequences that should be included in MRI protocols for head and neck cancer imaging. The second issue relates to approaches to surveillance imaging after treatment of head and neck cancer, including the choice of imaging modality, the frequency of surveillance imaging, and the role of standardized reporting through the Neck Imaging Reporting and Data System. The third issue relates to the role of imaging in the setting of neck carcinoma of unknown primary. The fourth issue relates to the role of simultaneous PET/MRI in head and neck cancer evaluation. The authors of this review provide consensus opinions for each issue.

The diagnostic value of ADC histogram and direct ADC measurements for coexisting isocitrate dehydrogenase mutation and O6-methylguanine-DNA methyltransferase promoter methylation in glioma

Objectives

To non-invasively predict the coexistence of isocitrate dehydrogenase (IDH) mutation and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation in adult-type diffuse gliomas using apparent diffusion coefficient (ADC) histogram and direct ADC measurements and compare the diagnostic performances of the two methods.

Materials and methods

A total of 118 patients with adult-type diffuse glioma who underwent preoperative brain magnetic resonance imaging (MRI) and diffusion weighted imaging (DWI) were included in this retrospective study. The patient group included 40 patients with coexisting IDH mutation and MGMT promoter methylation (IDHmut/MGMTmet) and 78 patients with other molecular status, including 32 patients with IDH wildtype and MGMT promoter methylation (IDHwt/MGMTmet), one patient with IDH mutation and unmethylated MGMT promoter (IDHmut/MGMTunmet), and 45 patients with IDH wildtype and unmethylated MGMT promoter (IDHwt/MGMTunmet). ADC histogram parameters of gliomas were extracted by delineating the region of interest (ROI) in solid components of tumors. The minimum and mean ADC of direct ADC measurements were calculated by placing three rounded or elliptic ROIs in solid components of gliomas. Receiver operating characteristic (ROC) curve analysis and the area under the curve (AUC) were used to evaluate the diagnostic performances of the two methods.

Results

The 10th percentile, median, mean, root mean squared, 90th percentile, skewness, kurtosis, and minimum of ADC histogram analysis and minimum and mean ADC of direct measurements were significantly different between IDHmut/MGMTmet and the other glioma group (P < 0.001 to P = 0.003). In terms of single factors, 10th percentile of ADC histogram analysis had the best diagnostic efficiency (AUC = 0.860), followed by mean ADC obtained by direct measurements (AUC = 0.844). The logistic regression model combining ADC histogram parameters and direct measurements had the best diagnostic efficiency (AUC = 0.938), followed by the logistic regression model combining the ADC histogram parameters with statistically significant difference (AUC = 0.916) and the logistic regression model combining minimum ADC and mean ADC (AUC = 0.851).

Conclusion

Both ADC histogram analysis and direct measurements have potential value in predicting the coexistence of IDHmut and MGMTmet in adult-type diffuse glioma. The diagnostic performance of ADC histogram analysis was better than that of direct ADC measurements. The combination of the two methods showed the best diagnostic performance.

Diffusion-weighted imaging and apparent diffusion coefficient mapping of head and neck lymph node metastasis: a systematic review

AIM

Head and neck squamous cell cancer (HNSCC) is the ninth most common tumor worldwide. Neck lymph node (LN) status is the major indicator of prognosis in all head and neck cancers, and the early detection of LN involvement is crucial in terms of therapy and prognosis. Diffusion-weighted imaging (DWI) is a non- invasive imaging technique used in magnetic resonance imaging (MRI) to characterize tissues based on the displacement motion of water molecules. This review aims to provide an overview of the current literature concerning quantitative diffusion imaging for LN staging in patients with HNSCC.

METHODS

This systematic review performed a literature search on the PubMed database (https://pubmed.ncbi.nlm.nih.gov/) for all relevant, peer-reviewed literature on the subject following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) criteria, using the keywords: DWI, MRI, head and neck, staging, lymph node.

RESULTS

After excluding reviews, meta-analyses, case reports, and bibliometric studies, 18 relevant papers out of the 567 retrieved were selected for analysis.

CONCLUSIONS

DWI improves the diagnosis, treatment planning, treatment response evaluation, and overall management of patients affected by HNSCC. More robust data to clarify the role of apparent diffusion coefficient (ADC) and DWI parameters are needed to develop models for prognosis and prediction in HNSCC cancer using MRI.

A joint linear reconstruction for multishot diffusion weighted non-Carr-Purcell-Meiboom-Gill fast spin echo with full signal

PURPOSE

Diffusion weighted Fast Spin Echo (DW-FSE) is a promising approach for distortionless DW imaging that is robust to system imperfections such as eddy currents and off-resonance. Due to non-Carr-Purcell-Meiboom-Gill (CPMG) magnetization, most DW-FSE sequences discard a large fraction of the signal (2 - 2 × $$ \sqrt{2}-2\times $$ ), reducing signal-to-noise ratio (SNR) efficiency compared to DW-EPI. The full FSE signal can be preserved by quadratically incrementing the transmit phase of the refocusing pulses, but this method of resolving non-CPMG magnetization has only been applied to single-shot DW-FSE due to challenges associated with image reconstruction. We present a joint linear reconstruction for multishot quadratic phase increment data that addresses these challenges and corrects ghosting from both shot-to-shot phase and intrashot signal oscillations. Multishot imaging reduces T2 blur and joint reconstruction of shots improves g-factor performance. A thorough analysis on the condition number of the proposed linear system is described.

METHODS

A joint multishot reconstruction is derived from the non-CPMG signal model. Multishot quadratic phase increment DW-FSE was tested in a standardized diffusion phantom and compared to single-shot DW-FSE and DW-EPI in vivo in the brain, cervical spine, and prostate. The pseudo multiple replica technique was applied to generate g-factor and SNR maps.

RESULTS

The proposed joint shot reconstruction eliminates ghosting from shot-to-shot phase and intrashot oscillations. g-factor performance is improved compared to previously proposed reconstructions, permitting efficient multishot imaging. apparent diffusion coefficient estimates in phantom experiments and in vivo are comparable to those obtained with conventional methods.

CONCLUSION

Multi-shot non-CPMG DW-FSE data with full signal can be jointly reconstructed using a linear model.

Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma

Pseudoprogression (PsP) refers to treatment-related clinico-radiologic changes mimicking true progression (TP) that occurs in patients with glioblastoma (GBM), predominantly within the first 6 months after the completion of surgery and concurrent chemoradiation therapy (CCRT) with temozolomide. Accurate differentiation of TP from PsP is essential for making informed decisions on appropriate therapeutic intervention as well as for prognostication of these patients. Conventional neuroimaging findings are often equivocal in distinguishing between TP and PsP and present a considerable diagnostic dilemma to oncologists and radiologists. These challenges have emphasized the need for developing alternative imaging techniques that may aid in the accurate diagnosis of TP and PsP. In this review, we encapsulate the current state of knowledge in the clinical applications of commonly used metabolic and physiologic magnetic resonance (MR) imaging techniques such as diffusion and perfusion imaging and proton spectroscopy in distinguishing TP from PsP. We also showcase the potential of promising imaging techniques, such as amide proton transfer and amino acid-based positron emission tomography, in providing useful information about the treatment response. Additionally, we highlight the role of "radiomics", which is an emerging field of radiology that has the potential to change the way in which advanced MR techniques are utilized in assessing treatment response in GBM patients. Finally, we present our institutional experiences and discuss future perspectives on the role of multiparametric MR imaging in identifying PsP in GBM patients treated with "standard-of-care" CCRT as well as novel/targeted therapies.

Diffusion and perfusion imaging biomarkers of H3 K27M mutation status in diffuse midline gliomas

PURPOSE

H3K27M-mutant diffuse midline gliomas (M-DMGs) exhibit a clinically aggressive course. We studied diffusion-weighted imaging (DWI) and perfusion (PWI) MRI features of DMG with the hypothesis that DWI-PWI metrics can serve as biomarkers for the prediction of the H3K27M mutation status in DMGs.

METHODS

A retrospective review of the institutional database (imaging and histopathology) of patients with DMG (July 2016 to July 2020) was performed. Tumoral apparent diffusion coefficient (ADC) and peritumoral ADC (PT ADC) values and their normalized values (nADC and nPT ADC) were computed. Perfusion data were analyzed with manual arterial input function (AIF) and leakage correction (LC) Boxerman-Weiskoff models. Normalized maximum relative CBV (rCBV) was evaluated. Intergroup analysis of the imaging variables was done between M-DMGs and wild-type (WT-DMGs) groups.

RESULTS

Ninety-four cases (M-DMGs-n = 48 (51%) and WT-DMGs-n = 46(49%)) were included. Significantly lower PT ADC (mutant-1.1 ± 0.33, WT-1.23 ± 0.34; P = 0.033) and nPT ADC (mutant-1.64 ± 0.48, WT-1.83 ± 0.54; P = 0.040) were noted in the M-DMGs. The rCBV (mutant-25.17 ± 27.76, WT-13.73 ± 14.83; P = 0.018) and nrCBV (mutant-3.44 ± 2.16, WT-2.39 ± 1.25; P = 0.049) were significantly higher in the M-DMGs group. Among thalamic DMGs, the min ADC, PT ADC, and nADC and nPT ADC were lower in M-DMGs while nrCBV (corrected and uncorrected) was significantly higher. Receiver operator characteristic curve analysis demonstrated that PT ADC (cut-off-1.245), nPT ADC (cut-off-1.853), and nrCBV (cut-off-1.83) were significant independent predictors of H3K27M mutational status in DMGs.

CONCLUSION

DWI and PWI features hold value in preoperative prediction of H3K27M-mutation status in DMGs.

Advanced MRI to differentiate schwannomas and metastases in the cerebellopontine angle/internal auditory canal

BACKGROUND AND PURPOSE

Differentiating schwannomas and metastases in the cerebellopontine angles (CPA)/internal auditory canals (IAC) can be challenging. This study aimed to assess the role of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced MRI (DCE-MRI) to differentiate schwannomas and metastases in the CPA/IAC.

METHODS

We retrospectively reviewed 368 patients who were diagnosed with schwannomas or metastases in the CPA/IAC between April 2017 and February 2022 in a single academic center. Forty-three patients had pretreatment DWI and DCE-MRI along with conventional MRI. Normalized mean apparent diffusion coefficient ratio (nADCmean) and DCE-MRI parameters of fractional plasma volume (Vp), flux rate constant (Kep), and forward volume transfer constant were compared along with patients' demographics and conventional imaging features between schwannomas and metastases as appropriate. The diagnostic performances and multivariate logistic regression analysis were performed using the significantly different values.

RESULTS

Between 23 schwannomas (15 males; median 48 years) and 20 metastases (9 males; median 61 years), nADCmean (median: 1.69 vs. 1.43; p = .002), Vp (median: 0.05 vs. 0.20; p < .001), and Kep (median: 0.41 vs. 0.81 minute^-1 ; p < .001) were significantly different. The diagnostic performances of nADCmean, Vp, and Kep were 0.77, 0.90, and 0.83 area under the curves, with cutoff values of 1.68, 0.12, and 0.53, respectively. Vp was identified as the most significant parameter for the tumor differentiation in the multivariate logistic regression analysis (p < .001).

CONCLUSIONS

DWI and DCE-MRI can help differentiate CPA/IAC schwannomas and metastases, and Vp is the most significant parameter.

The ability of post-chemoradiotherapy DWI ADCmean and 18F-FDG SUVmax to predict treatment outcomes in head and neck cancer: impact of human papilloma virus oropharyngeal cancer status

OBJECTIVES

To evaluate the ability of post-chemo-radiotherapy (CRT) diffusion-weighted-MRI apparent diffusion coefficient (ADCmean) and 18F-FDG PET maximum standardized uptake value (SUVmax) to predict disease-free survival (DFS) in head and neck squamous cell carcinoma (HNSCC), and to determine whether this ability is influenced by human papillomavirus oropharyngeal cancer (HPV-OPC) status.

METHODS

This prospective cohort observational study included 65 participants (53 male, mean ± SD age 59.9 ± 7.9 years, 46 HPV-OPC) with stage III or IV HNSCC. Primary tumour and nodal ADCmean (pre-treatment, 6- and 12-weeks post-CRT) and SUVmax (12-weeks post-CRT) were measured. Variables were compared with 2-year DFS (independent t-test/Mann-Whitney test) and overall DFS (Cox regression), before and after accounting for HPV-OPC status. Variables were also compared between HPV-OPC and other HNSCC subgroups after stratifying for DFS.

RESULTS

Absolute post-CRT ADCmean values predicted 2-year DFS and overall DFS for all participants (p = 0.03/0.03, 6-week node; p = 0.02/0.03 12-week primary tumour) but not in the HPV-OPC subgroup. In participants with DFS, percentage interval changes in primary tumour ADCmean at 6- and 12-weeks were higher in HPV-OPC than other HNSCC (p = 0.01, 6 weeks; p = 0.005, 12 weeks). The 12-week post-CRT SUVmax did not predict DFS.

CONCLUSION

Absolute post-CRT ADCmean values predicted DFS in HNSCC but not in the HPV-OPC subgroup. Amongst participants with DFS, post-CRT percentage interval changes in primary tumour ADCmean were significantly higher in HPV-OPC than in other HNSCC. Knowledge of HPV-OPC status is crucial to the clinical utilisation of post-CRT DWI-MRI for the prediction of outcomes.

Diffusion-weighted magnetic resonance imaging for differentiating between benign and malignant thoracic lymph nodes: a meta-analysis

OBJECTIVE

To establish the diagnostic performance of diffusion-weighted magnetic resonance imaging (DWI) in discriminating malignant from non-malignant thoracic lymph nodes.

MATERIALS AND METHODS

This was a meta-analysis involving systematic searches of the MEDLINE, EMBASE, and Web of Science databases up through April 2020. Studies reporting thoracic DWI and lymph node evaluation were included. The pooled sensitivity, specificity, diagnostic odds ratio, positive predictive value, negative predictive value, and area under the receiver operating characteristic curve (AUC) were calculated.

RESULTS

We evaluated six studies, involving a collective total of 356 mediastinal lymph nodes in 214 patients. Thoracic DWI had a pooled sensitivity and specificity of 92% (95% confidence interval [95% CI]: 71-98%) and 93% (95% CI: 79-98%), respectively. The positive and negative likelihood ratios were 13.2 (95% CI: 4.0-43.8) and 0.09 (95% CI: 0.02-0.36), respectively. The diagnostic odds ratio was 149 (95% CI: 18-1,243), and the AUC was 0.97 (95% CI: 0.95-0.98).

CONCLUSION

DWI is a reproducible technique and has demonstrated high accuracy for differentiating between malignant and benign states in thoracic lymph nodes.

The Diagnostic Value of Apparent Diffusion Coefficient and Proton Magnetic Resonance Spectroscopy in the Grading of Pediatric Gliomas

The aims of this retrospective study were to assess the value of the quantitative analysis of apparent diffusion coefficient (ADC) and proton magnetic resonance spectroscopy (¹H-MRS) metabolites in differentiating grades of pediatric gliomas.

Actual applications of magnetic resonance imaging in dentomaxillofacial region

Magnetic resonance imaging (MRI) is a versatile imaging modality utilized in various medical fields. Specifically used for evaluation of soft tissues, with non-ionizing radiation and multiplanar sections that has provided great guidance to diagnosis. Nowadays, use of MRI in dental practice is becoming more pervasive, especially for the evaluation of head-and-neck cancer, detection of salivary gland lesions, lymphadenopathy, and temporomandibular joint disorders. Understanding the basic principles, its recent advances, and multiple applications in dentomaxillofacial region helps significantly in the diagnostic decision making. In this article, the principle of MRI and its recent advances are reviewed, with further discussion on the appearance of various maxillofacial pathosis.

Diffusion-Weighted Imaging (DWI) derived from PET/MRI for lymph node assessment in patients with Head and Neck Squamous Cell Carcinoma (HNSCC)

BACKGROUND

To determine the usefulness of Diffusion Weighted Imaging (DWI) derived from PET/MRI in discriminating normal from metastatic lymph nodes and the correlation between the metastatic lymph nodes with the grade and the localization of the primary tumor.

METHODS

Retrospective study of 90 lymph nodes from 90 subjects; 65 patients who had proven histopathological metastatic lymph nodes from (HNSCC) who had undergone 18F- PET/MRI for clinical staging and assessment and twenty-five lymph nodes were chosen from 25 healthy subjects. Apparent Diffusion Coefficient (ADC) map was generated from DWI with b values (0 and 800 s/mm2). ADC values of the metastatic lymph nodes were calculated and compared to the normal lymph nodes ADC values, ROC was used to determine the best cut-off values to differentiate between the two group. Metastatic lymph nodes ADC mean values were compared to primary tumor grade and localization.

RESULTS

ADCmean value of the metastatic lymph nodes in the overall sample (0.899 ± 0.98*10- 3 mm2/sec) was significantly lower than the normal lymph nodes' ADCmean value (1.267 ± 0.88*10- 3 mm2/sec); (P = 0.001). The area under the curve (AUC) was 98.3%, sensitivity and specificity were 92.3 and 98.6%, respectively, when using a threshold value of (1.138 ± 0.75*10- 3 mm2/sec) to differentiate between both groups. Significant difference was found between metastatic lymph nodes (short-axis diameter < 10 mm), ADCmean (0.898 ± 0.72*10- 3 mm2/sec), and the benign lymph nodes ADCmean, (P = 0.001). No significant difference was found between ADCmean of the metastatic lymph nodes < 10 mm and the metastatic lymph nodes > 10 mm, ADCmean (0.899 ± 0.89*10- 3 mm2/sec), (P = 0.967). No significant differences were found between metastatic lymph nodes ADCmean values and different primary tumor grades or different primary tumor localization, (P > 0.05).

CONCLUSION

DWI-ADC is an effective and efficient imaging technique in differentiating between normal and malignant lymph nodes, and might be helpful to discriminate sub-centimeters lymph nodes.

TRIAL REGISTRATION

The trial is registered in clinical trials under ID: NCT04360993 , registration date: 17/04/2020.

Prediction of distant metastases in patients with squamous cell carcinoma of head and neck using DWI and DCE-MRI

BACKGROUND

The primary purpose was to evaluate the prognostic potential of diffusion imaging (DWI) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in predicting distant metastases in squamous cell carcinoma of head and neck (HNSCC) patients. The secondary aim was to examine differences in DWI and DCE-MRI-derived parameters on the basis of human papilloma virus (HPV) status, differentiation grade, and nodal stage of HNSCC.

METHODS

Fifty-six patients underwent pretreatment DWI and DCE-MRI. Patients were divided into groups who subsequently did (n = 12) or did not develop distant metastases (n = 44). Median values of apparent diffusion coefficient (ADC), volume transfer constant (K^trans ), and mean intracellular water-lifetime (τ_i ) and volume were computed from metastatic lymph nodes and were compared between two groups. Prognostic utility of HPV status, differentiation grading, and nodal staging was also evaluated both in isolation or in combination with MRI parameters in distinguishing patients with and without distant metastases. Additionally, MRI parameters were compared between two groups based on dichotomous HPV status, differentiation grade, and nodal stage.

RESULTS

Lower but not significantly different K^trans (0.51 ± 0.15 minute^-1 vs 0.60 ± 0.05 minute^-1 ) and not significantly different τ_i (0.13 ± 0.03 second vs 0.19 ± 0.02 second) were observed in patients who developed distant metastases than those who did not. Additionally, no significant differences in ADC or volume were found. τ_i, was the best parameter in discriminating two groups with moderate sensitivity (67%) and specificity (61.4%). Multivariate logistic regression analyses did not improve the overall prognostic performance for combination of all variables. A trend toward higher τ_i was observed in HPV-positive patients than those with HPV-negative patients. Also, a trend toward higher K^trans was observed in poorly differentiated HNSCCs than those with moderately differentiated HNSCCs.

CONCLUSION

Pretreatment DCE-MRI may be useful in predicting distant metastases in HNSCC.

Response Evaluation of Choroidal Melanoma After Brachytherapy Using Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI): Preliminary Findings

Purpose: To evaluate the role of diffusion-weighted magnetic resonance imaging (DW-MRI) in the assessment of therapeutic response in patients with choroidal melanoma treated with brachytherapy.

Materials and Methods: We performed a prospective, unicentric study which included patients with choroidal melanoma and indication for brachytherapy. Three DW-MRI examinations were proposed for each patient, one before and two after treatment. The apparent diffusion coefficient (ADC) value was calculated on DW-MRI and compared with local tumor control assessed by ophthalmologic follow-up.

Results: From 07/2018 to 06/2019, 19 patients were recruited, 13 of whom underwent follow-up examinations. Patients' ages ranged from 24 to 78 years and 52.9% were male. At the ocular ultrasound, the mean tumor thickness and diameter were 6.3 and 11.5 mm, respectively. Two patients (15.4%) showed signs of tumor progression during follow-up (7 and 9 months after treatment). There was no statistically significant difference in tumor size between MR before and after treatment, however, there was a significant reduction in mean ADC in patients with progression (p = 0.02).

Conclusion: DW-MRI is a promising method for monitoring patients with choroidal melanoma; reduction in the mean ADC values between pre-treatment MRI and the first post-treatment MRI may be related to the lack of response to brachytherapy and increased risk of disease progression.

Image Quality and ADC Assessment in Turbo Spin-Echo and Echo-Planar Diffusion-Weighted MR Imaging of Tumors of the Head and Neck

RATIONALE AND OBJECTIVES

We aimed to compare the distortion ratio (DR), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) between turbo spin-echo (TSE)-diffusion-weighted imaging (DWI) and echo-planar imaging (EPI)-DWI of the orofacial region and prove the usefulness of TSE-DWI for the differential diagnosis of orofacial lesions.

MATERIALS AND METHODS

The DR, SNR, and CNR of both sequences were compared in 42 cases. Then, the apparent diffusion coefficient (ADC) of various orofacial lesions obtained by TSE-DWI was investigated in 143 lesions.

RESULTS

In the first study, 38 of 42 cases were analyzed. TSE-DWI showed a significantly lower DR (p < 0.05) and higher SNR and CNR than EPI-DWI (p < 0.05), indicating the superiority of TSE-DWI. In the second study, 114 cases (79.3%) were successfully analyzed. When lesions were divided into cysts, benign tumors, squamous cell carcinoma, malignant lymphoma, and other malignant tumors (OT), significant differences were observed in all pairs of lesions (p < 0.05) except squamous cell carcinoma and OT (p = 0.877). The area under the curve for distinguishing benign from malignant tumors was 0.80 with a cutoff ADC of 1.29 × 10^-3 mm²/s.

CONCLUSION

TSE-DWI produced better quality images than EPI-DWI. TSE-DWI yields the high possibility of obtaining ADC in the orofacial region, and this value was considered useful for the differential diagnosis of orofacial lesions.

Predictive value of quantitative diffusion-weighted imaging and 18-F-FDG-PET in head and neck squamous cell carcinoma treated by (chemo)radiotherapy

BACKGROUND AND PURPOSE

In head and neck squamous cell carcinoma (HNSCC) (chemo)radiotherapy is increasingly used to preserve organ functionality. The purpose of this study was to identify predictive pretreatment DWI- and ¹⁸F-FDG-PET/CT-parameters for treatment failure (TF), locoregional recurrence (LR) and death in HNSCC patients treated by (chemo)radiotherapy.

MATERIALS AND METHODS

We retrospectively included 134 histologically proven HNSCC patients treated with (chemo)radiotherapy between 2012-2017. In 58 patients pre-treatment DWI and ¹⁸F-FDG-PET/CT were performed, in 31 patients DWI only and in 45 patients ¹⁸F-FDG-PET/CT only. Primary tumor (_PT) and largest lymph node (_LN) metastasis were quantitatively assessed for TF, LR and death. Multivariate analysis was performed for ¹⁸F-FDG-PET/CT and DWI separately and thereafter combined. In patients with both imaging modalities, positive and negative predictive value in TF and differences in LR and death, were assessed.

RESULTS

Mean follow-up was 25.6 months (interquartile-range; 14.0-37.1 months). Predictors of treatment failure, corrected for TNM-stage and HPV-status, were SUV_max-PT, ADC_max-PT, total lesion glycolysis (TLG_-LN), ADCp20_-LN (P = 0.049, P = 0.024, P = 0.031, P = 0.047, respectively). TLG_-PT was predictive for LR (P = 0.003). Metabolic active tumor volume (MATV_-PT) (P = 0.003), ADC_GTV-PT (P < 0.001), ADCSD (P = 0.048) were significant predictors for death. In patients with both imaging modalities SUV_max-PT remained predictive for treatment failure (P = 0.049), TLG-_LN for LR (P = 0.003) and ADC_GTV-PT for death (P < 0.001). Higher predictive value for treatment failure was found for the combination of SUV_max-PT and ADC_max-PT, compared to either one separately.

CONCLUSION

Both DWI- and ¹⁸F-FDG-PET/CT-parameters appear to have predictive value for treatment failure, locoregional recurrence and death. Combining SUV_max-PT and ADC_max-PT resulted in better prediction of treatment failure compared to single parameter assessment.

The interobserver agreement in the detection of recurrent HNSCC using MRI including diffusion weighted MRI

INTRODUCTION

For the detection of local recurrences of head and neck squamous cell carcinomas (HNSCC) after (chemo)radiation, diagnostic imaging is generally performed. Diffusion weighted magnetic resonance imaging (DW-MRI) has been proven to be able to adequately diagnose the presence of cancer. However evaluation of DW-MR images for recurrences is difficult and could be subject to individual interpretation.

AIM

To determine the interobserver agreement, intraobserver agreement and influence of experience of radiologists in the assessment of DW-MRI in patients clinically suspected of local recurrent HNSCC after (chemo)radiation.

METHODS

Ten experienced head and neck radiologists assessed follow-up MRI including DW-MRI series of 10 patients for the existence of local recurrence on a two point decision scale (local recurrence or local control). Patients were clinically suspected for a recurrence of laryngeal (n = 3), hypopharyngeal (n = 3) or oropharyngeal (n = 4) cancer after (chemo)radiation with curative intent. Fleiss' and Cohen's Kappa were used to determine interobserver agreement and intraobserver agreement, respectively.

RESULTS

Interobserver agreement was κ = 0.55. Intraobserver agreement was κ = 0.80. Prior experience within the field of radiology and with DW-MRI had no significant influence on the scoring.

CONCLUSION

For the assessment of HNSCC recurrence after (chemo)radiation by DW-MRI, moderate interobserver agreement and substantial intraobserver agreement was found.

Stability assessment of first order statistics features computed on ADC maps in soft-tissue sarcoma

Radiomics extracts a large number of features from medical images to perform a quantitative characterization. Aim of this study was to assess radiomic features stability and relevance. Apparent diffusion coefficient (ADC) maps were computed from diffusion-weighted magnetic resonance images (DW-MRI) of 18 patients diagnosed with soft-tissue sarcomas (STSs). Thirty-seven intensity-based features were computed on the regions of interest (ROIs). First, ROIs of the images were subjected to translations and rotations in specific ranges. The 37 features computed on the original and transformed ROIs were compared in terms of percentage of variations. The intra-class correlation coefficient (ICC) was computed. To be accepted, a feature should satisfy the following conditions: the ICC after a minimum entity transformation is > 0.6 and the ICC after a maximum entity translation is <; 0.4. In total, 31 features out of 37 were accepted by the algorithm. This stability analysis can be used as a first step in the features selection process.

The diagnostic role of diffusion-weighted magnetic resonance imaging in hypopharyngeal carcinoma

The aim of the present study was to assess the role of diffusion-weighted magnetic resonance imaging (DWI) and apparent diffusion coefficient (ADC) values in hypopharyngeal carcinoma. A total of 40 hypopharyngeal carcinoma tissues and 15 benign lesion tissues were retrospectively analyzed. DWI, and T1- and T2-weighted magnetic resonance imaging (MRI) was performed. The sensitivity, specificity and accuracy of conventional MRI were 97.5, 66.7, and 89.1%, respectively. The mean ADC value [diffusion sensitive factor (b)=1,000× sec/mm²) for hypopharyngeal carcinomas was (1.0285±0.0328)×10⁻³ mm²/sec, which was significantly lower than the mean ADC value for benign lesions [(1.5333±0.1061)×10⁻³ mm²/sec; P<0.001]. Receiver operating characteristic (ROC) curve analysis revealed that the area under the curve (AUC) was 0.921 while the optimal threshold for the cut-off point of the ADC was 1.075×10⁻³ mm²/sec. The mean ADC value of the metastatic nodes was (0.9184±0.0538)×10⁻³ mm²/sec, lower than the mean value for the benign nodes [(1.2538±0.1145)×10⁻³ mm²/sec; P=0.005]. Two groups were created according to the mean of the ADC value of hypopharyngeal carcinomas [≤(1.0285±0.0328)×10⁻³ mm²/sec vs. >(1.0285±0.0328)×10⁻³ mm²/sec]. The 2-year survival rates of the two groups were 55.6 and 100.0%, respectively (P=0.024). ADC values may aid in distinguishing hypopharyngeal carcinomas from benign lesions and differentiating metastatic lymph nodes of hypopharyngeal squamous cell carcinomas from reactive cervical lymph nodes. In conclusion, mean ADC values may be useful prognostic factors in univariate analysis of hypopharyngeal carcinoma.

A case study of primary malignancy of buccal mucosa using proton HR-MAS NMR spectroscopy on tissue specimens

The diagnosis and confirmation of oral SCC (squamous cell carcinoma) is still dependent on histopathology report in spite of development of radiological investigations. It is, thus important to understand the underlying molecular mechanisms and how the alterations in metabolic pathways effect the tumor development and progression. The simultaneous and comprehensive information about the presence and absence of small molecule metabolites and their relative concentrations has been provided by ¹H HR-MAS NMR spectroscopy on tissue specimens. In this paper a unique case study was presented in order to correlate histological and NMR spectroscopic findings. The patient's initially lesion was found to be non-malignant in nature based on histological findings but its periodic localized recurrence even after laser ablation prompted us to perform HR-MAS based analysis and its role in identifying the metabolic alterations in known pathways occurring during its progressions. Thus it was confirmed after analysis that HR-MAS NMR can also be used as an analytical tool which is reliable in order to distinguish between malignant and non-malignant tissues, in combination with histopathology.

Diffusion magnetic resonance imaging: A molecular imaging tool caught between hope, hype and the real world of “personalized oncology”

“Personalized oncology” is a multi-disciplinary science, which requires inputs from various streams for optimal patient management. Humongous progress in the treatment modalities available and the increasing need to provide functional information in addition to the morphological data; has led to leaping progress in the field of imaging. Magnetic resonance imaging has undergone tremendous progress with various newer MR techniques providing vital functional information and is becoming the cornerstone of “radiomics/radiogenomics”. Diffusion-weighted imaging is one such technique which capitalizes on the tendency of water protons to diffuse randomly in a given system. This technique has revolutionized oncological imaging, by giving vital qualitative and quantitative information regarding tumor biology which helps in detection, characterization and post treatment surveillance of the lesions and challenging the notion that “one size fits all”. It has been applied at various sites with different clinical experience. We hereby present a brief review of this novel functional imaging tool, with its application in “personalized oncology”.

Radiomic analysis of soft tissues sarcomas can distinguish intermediate from high-grade lesions

PURPOSE

To assess the feasibility of grading soft tissue sarcomas (STSs) using MRI features (radiomics).

MATERIALS AND METHODS

MRI (echo planar SE, 1.5T) from 19 patients with STSs and a known histological grading, were retrospectively analyzed. The apparent diffusion coefficient (ADC) maps, obtained by diffusion-weighted imaging acquisitions, were analyzed through 65 radiomic features, intensity-based (first order statistics, FOS) and texture (gray level co-occurrence matrix, GLCM; and gray level run length matrix, GLRLM) features. Feature selection (sequential forward floating search) and classification (k-nearest neighbor classifier) were performed to distinguish intermediate- from high-grade STSs. Classification was performed using the three different sub-groups of features separately as well as all the features together. The entire dataset was divided in three subsets: the training, validation and test set, containing, respectively, 60, 30, and 10% of the data.

RESULTS

Intermediate-grade lesions had a higher and less disperse ADC values compared with high-grade ones: most of FOS related to intensity are higher for the intermediate-grade STSs, while FOS related to signal variability were higher in the high grade (e.g., the feature variance is 2.6*10⁵  ± 0.9*10⁵ versus 3.3*10⁵  ± 1.6*10⁵ , P = 0.3). The GLCM features related to entropy and dissimilarity were higher in the high-grade. When performing classification, the best accuracy is obtained with a maximum of three features for each subgroup, FOS features being those leading to the best classification (validation set: FOS accuracy 0.90 ± 0.11, area under the curve [AUC] 0.85 ± 0.16; test set: FOS accuracy 0.88 ± 0.25, AUC 0.87 ± 0.34).

CONCLUSION

Good accuracy and AUC could be obtained using only few Radiomic features, belonging to the FOS class.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:829-840.

Diagnostic accuracy of magnetic resonance imaging techniques for treatment response evaluation in patients with head and neck tumors, a systematic review and meta-analysis

Background

Novel advanced MRI techniques are investigated in patients treated for head and neck tumors as conventional anatomical MRI is unreliable to differentiate tumor from treatment related imaging changes.

Purpose

As the diagnostic accuracy of MRI techniques to detect tumor residual or recurrence during or after treatment is variable reported in the literature, we performed a systematic meta-analysis.

Data sources

Pubmed, EMBASE and Web of Science were searched from their first record to September 23^th 2014.

Study selection

Studies reporting diagnostic accuracy of anatomical, ADC, perfusion or spectroscopy to identify tumor response confirmed by histology or follow-up in treated patients for head and neck tumors were selected by two authors independently.

Data analysis

Two authors independently performed data extraction including true positives, false positives, true negatives, false negatives and general study characteristics. Meta-analysis was performed using bivariate random effect models when ≥5 studies per test were included.

Data synthesis

We identified 16 relevant studies with anatomical MRI and ADC. No perfusion or spectroscopy studies were identified. Pooled analysis of anatomical MRI of the primary site (11 studies, N = 854) displayed a sensitivity of 84% (95%CI 72–92) and specificity of 82% (71–89). ADC of the primary site (6 studies, N = 287) showed a pooled sensitivity of 89% (74–96) and specificity of 86% (69–94).

Limitations

Main limitation are the low, but comparable quality of the included studies and the variability between the studies.

Conclusions

The higher diagnostic accuracy of ADC values over anatomical MRI for the primary tumor location emphases the relevance to include DWI with ADC for response evaluation of treated head and neck tumor patients.

The emerging potential of magnetic resonance imaging in personalizing radiotherapy for head and neck cancer: an oncologist's perspective

Head and neck cancer (HNC) is a challenging tumour site for radiotherapy delivery owing to its complex anatomy and proximity to organs at risk (OARs) such as the spinal cord and optic apparatus. Despite significant advances in radiotherapy planning techniques, radiation-induced morbidities remain substantial. Further improvement would require high-quality imaging and tailored radiotherapy based on intratreatment response. For these reasons, the use of MRI in radiotherapy planning for HNC is rapidly gaining popularity. MRI provides superior soft-tissue contrast in comparison with CT, allowing better definition of the tumour and OARs. The lack of additional radiation exposure is another attractive feature for intratreatment monitoring. In addition, advanced MRI techniques such as diffusion-weighted, dynamic contrast-enhanced and intrinsic susceptibility-weighted MRI techniques are capable of characterizing tumour biology further by providing quantitative functional parameters such as tissue cellularity, vascular permeability/perfusion and hypoxia. These functional parameters are known to have radiobiological relevance, which potentially could guide treatment adaptation based on their changes prior to or during radiotherapy. In this article, we first present an overview of the applications of anatomical MRI sequences in head and neck radiotherapy, followed by the potentials and limitations of functional MRI sequences in personalizing therapy.

Image denoising substantially improves accuracy and precision of intravoxel incoherent motion parameter estimates

Applicability of intravoxel incoherent motion (IVIM) imaging in the clinical setting is hampered by the limited reliability in particular of the perfusion-related parameter estimates. To alleviate this problem, various advanced postprocessing methods have been introduced. However, the underlying algorithms are not readily available and generally suffer from an increased computational burden. Contrary, several computationally fast image denoising methods have recently been proposed which are accessible online and may improve reliability of IVIM parameter estimates. The objective of the present work is to investigate the impact of image denoising on accuracy and precision of IVIM parameter estimates using comprehensive in-silico and in-vivo experiments. Image denoising is performed with four different algorithms that work on magnitude data: two algorithms which are based on nonlocal means (NLM) filtering, one algorithm that relies on local principal component analysis (LPCA) of the diffusion-weighted images, and another algorithms that exploits joint rank and edge constraints (JREC). Accuracy and precision of IVIM parameter estimates is investigated in an in-silico brain phantom and an in-vivo ground truth as a function of the signal-to-noise ratio for spatially homogenous and inhomogenous levels of Rician noise. Moreover, precision is evaluated using bootstrap analysis of in-vivo measurements. In the experiments, IVIM parameters are computed a) by using a segmented fit method and b) by performing a biexponential fit of the entire attenuation curve based on nonlinear least squares estimates. Irrespective of the fit method, the results demonstrate that reliability of IVIM parameter estimates is substantially improved by image denoising. The experiments show that the LPCA and the JREC algorithms perform in a similar manner and outperform the NLM-related methods. Relative to noisy data, accuracy of the IVIM parameters in the in-silico phantom improves after image denoising by 76–79%, 79–81%, 84–99% and precision by 74–80%, 80–83%, 84–95% for the perfusion fraction, the diffusion coefficient, and the pseudodiffusion coefficient, respectively, when the segmented fit method is used. Beyond that, the simulations reveal that denoising performance is not impeded by spatially inhomogeneous levels of Rician noise in the image. Since all investigated algorithms are freely available and work on magnitude data they can be readily applied in the clinical setting which may foster transition of IVIM imaging into clinical practice.

Intravoxel incoherent motion diffusion-weighted MRI during chemoradiation therapy to characterize and monitor treatment response in human papillomavirus head and neck squamous cell carcinoma

PURPOSE

Characterize and monitor treatment response in human papillomavirus (HPV) head and neck squamous cell carcinoma (HNSCC) using intra-treatment (intra-TX) imaging metrics derived from intravoxel incoherent motion (IVIM) diffusion-weighted magnetic resonance imaging (DW-MRI).

MATERIALS AND METHODS

Thirty-four (30 HPV positive [+] and 4 HPV negative [-]) HNSCC patients underwent a total of 136 MRI including multi-b value DW-MRI (pretreatment [pre-TX] and intra-TX weeks 1, 2, and 3) at 3.0 Tesla. All patients were treated with chemo-radiation therapy. Monoexponential (yielding apparent diffusion coefficient [ADC]) and bi-exponential (yielding perfusion fraction [f], diffusion [D], and pseudo-diffusion [D*] coefficients) fits were performed on a region of interest and voxel-by-voxel basis, on metastatic neck nodes. Response was assessed using RECISTv1.1. The relative percentage change in D, f, and D* between the pre- and intra-TX weeks were used for hierarchical clustering. A Wilcoxon rank-sum test was performed to assess the difference in metrics within and between the complete response (CR) and non-CR groups.

RESULTS

The delta (Δ) change in volume (V)_1wk-0wk for the CR group differed significantly (P = 0.016) from the non-CR group, while not for V_2wk-0wk and V_3wk-0wk (P > 0.05). The mean increase in ΔD_3wk-0wk for the CR group was significantly higher (P = 0.017) than the non-CR group. ADC and D showed an increasing trend at each intra-TX week when compared with pre-TX in CR group (P < 0.003). Hierarchical clustering demonstrated the existence of clusters in HPV + patients.

CONCLUSION

After appropriate validation in a larger population, these IVIM imaging metrics may be useful for individualized treatment in HNSCC patients.

LEVEL OF EVIDENCE

2 J. Magn. Reson. Imaging 2017;45:1013-1023.

Differentiating recurrent tumours from post-treatment changes in head and neck cancers: does diffusion-weighted MRI solve the eternal dilemma?

AIM

To evaluate the utility of diffusion-weighted imaging (DWI) in differentiating post-treatment changes from tumour recurrence in head and neck cancers and to establish a threshold apparent diffusion coefficient (ADC) value to differentiate the two conditions.

MATERIALS AND METHODS

This was a prospective study of 80 treated head and neck cancer patients. The patient cohort consisted of a wide spectrum of head and neck sites, including the oral cavity, oropharynx, larynx, hypopharynx, paranasal sinuses, orbits, salivary glands, and infra-temporal fossa. Qualitative analysis of the diffusion images and quantitative analysis of the corresponding ADC maps was performed and the data were correlated with histopathological findings and clinical examinations.

RESULTS

The mean ADC value of recurrent tumours in the present cohort was 0. 932±0.19×10^-3 mm²/s and the mean ADC value of lesions representing post-treatment changes was 1.394±0.32×10^-3 mm²/s. A threshold ADC value of 1.2×10^-3mm²/s used to differentiate post-treatment changes from recurrent head and neck cancers showed the highest combined sensitivity of 90.13%, specificity of 82.5%, accuracy of 86.4%, positive predictive value of 84.4%, negative predictive value of 88.9%, and mean kappa measurement of agreement of 72.8.

CONCLUSION

Combined qualitative and quantitative analysis of DWI is a useful non-invasive technique to differentiate recurrent head and neck malignancies from post-treatment changes using a threshold ADC value.

Evaluation of Head and Neck Tumors with Functional MR Imaging

Head and neck cancer is one of the most common cancers worldwide. MR imaging-based diffusion and perfusion techniques enable the noninvasive assessment of tumor biology and physiology, which supplement information obtained from standard structural scans. Diffusion and perfusion MR imaging techniques provide novel biomarkers that can aid monitoring in pretreatment, during treatment, and posttreatment stages to improve patient selection for therapeutic strategies; provide evidence for change of therapy regime; and evaluate treatment response. This review discusses pertinent aspects of the role of diffusion and perfusion MR imaging and computational analysis methods in studying head and neck cancer.

Assessment of serial multi-parametric functional MRI (diffusion-weighted imaging and R2*) with (18)F-FDG-PET in patients with head and neck cancer treated with radiation therapy

OBJECTIVE

To evaluate the serial changes and correlations between readout-segmented technique with navigated phase correction diffusion-weighted MRI (DWI), R2*-MRI and (18)F-FDG positron emission tomography (PET) CT performed before and during radiation therapy (RT) in patients with mucosal primary head and neck cancer.

METHODS

The mean apparent diffusion coefficient (ADCmean) from DWI (at b = 50 and 800 s mm(-2)), the mean R2* values derived from T2(*)-MRI, and PET metabolic parameters, including maximum standardized uptake value (SUVmax), metabolic tumour volume (MTV) and total lesional glycolysis (TLG) were measured for the primary tumour. Spearman correlation coefficients were calculated to evaluate correlations between ADCmean, R2*, SUVmax, MTV and TLG. A paired t-test was performed to assess the MRI changes and the slope of serial MRI changes during RT.

RESULTS

Pre-treatment scans were performed in 28 patients and mid-treatment scans in 20 patients. No significant correlation was found between ADCmean and either R2* values or PET parameters. There were significant negative correlations of R2* values with pre-treatment PET parameters but not with mid-RT PET parameters: pre-SUVmax (p = 0.008), pre-MTV (p = 0.006) and pre-TLG (p = 0.008). A significant rise in ADCmean was found during the first half (p < 0.001) of RT but not in the second half (p = 0.215) of the treatment. There was an increase of the ADCmean values of 279.4 [95% confidence interval (95% CI): 210-348] in the first half of the treatment (Weeks 0-3). However, during the second-half period of treatment, the mean ADC value (Weeks 3-6) was 24.0 and the 95% CI (-40 to 88) included zero. This suggests that there was no significant change in ADC values during the second half of the treatment.

CONCLUSION

A significant negative correlation was found between pre-treatment R2*-MRI and PET parameters. DWI appeared to demonstrate potentially predictable changes during RT.

ADVANCES IN KNOWLEDGE

Understanding the correlation and changes that occur with time between potential imaging biomarkers may help us establish the most appropriate biomarkers to consider in future research.

Diffusion-weighted and PET/MR Imaging after Radiation Therapy for Malignant Head and Neck Tumors

Interpreting imaging studies of the irradiated neck constitutes a challenge because of radiation therapy-induced tissue alterations, the variable appearances of recurrent tumors, and functional and metabolic phenomena that mimic disease. Therefore, morphologic magnetic resonance (MR) imaging, diffusion-weighted (DW) imaging, positron emission tomography with computed tomography (PET/CT), and software fusion of PET and MR imaging data sets are increasingly used to facilitate diagnosis in clinical practice. Because MR imaging and PET often yield complementary information, PET/MR imaging holds promise to facilitate differentiation of tumor recurrence from radiation therapy-induced changes and complications. This review focuses on clinical applications of DW and PET/MR imaging in the irradiated neck and discusses the added value of multiparametric imaging to solve diagnostic dilemmas. Radiologists should understand key features of radiation therapy-induced tissue alterations and potential complications seen at DW and PET/MR imaging, including edema, fibrosis, scar tissue, soft-tissue necrosis, bone and cartilage necrosis, cranial nerve palsy, and radiation therapy-induced arteriosclerosis, brain necrosis, and thyroid disorders. DW and PET/MR imaging also play a complementary role in detection of residual and recurrent disease. Interpretation pitfalls due to technical, functional, and metabolic phenomena should be recognized and avoided. Familiarity with DW and PET/MR imaging features of expected findings, potential complications, and treatment failure after radiation therapy increases diagnostic confidence when interpreting images of the irradiated neck. Online supplemental material is available for this article.

Repeatability Investigation of Reduced Field-of-View Diffusion-Weighted Magnetic Resonance Imaging on Thyroid Glands

OBJECTIVE

To investigate the repeatability of the quantitative magnetic resonance imaging (MRI) metric (apparent diffusion coefficient [ADC]) derived from reduced field-of-view diffusion-weighted (rFOV DWI) on thyroid glands in a clinical setting.

MATERIALS AND METHODS

Ten healthy human volunteers were enrolled in MRI studies performed on a 3-T MRI scanner. Each volunteer was designed to undergo 3 longitudinal examinations (2 weeks apart) with 2 repetitive sessions within each examination, which included rFOV and conventional full field-of-view (fFOV) DWI scans. Diffusion-weighted images were assessed and scored based on image characteristics. Apparent diffusion coefficient values of thyroid glands from all participants were calculated based on regions of interest. Repeatability analysis was performed based on the framework proposed by the Quantitative Imaging Biomarker Alliance, generating 4 repeatability metrics: within-participant variance ((Equation is included in full-text article.)), repeatability coefficients, intraclass correlation coefficient, and within-participant coefficient of variation. Student t test was used to compare the performance difference between rFOV and fFOV DWI.

RESULTS

The overall image quality from rFOV DWI was significantly higher than that from fFOV DWI (P = 0.04). The ADC values calculated from rFOV DWI were significantly lower than corresponding values from fFOV DWI (P < 0.001). There was no significant difference in ADC values across sessions and examinations in either rFOV or fFOV DWI (P > 0.05). Reduced field-of-view DWI had lower values of (Equation is included in full-text article.), repeatability coefficient, and within-participant coefficient of variation and had a higher value of intraclass correlation coefficient compared with fFOV DWI across either sessions or examinations.

CONCLUSIONS

This study demonstrated that rFOV DWI produced more superior-quality DWI images and more repeatable ADC measurements compared with fFOV DWI, thus providing a feasible quantitative imaging tool for investigating thyroid glands in clinical settings.