Added value of a single-energy projection-based metal-artifact reduction algorithm for the computed tomography evaluation of oral cavity cancers

Deep Learning Reconstruction Plus Single-Energy Metal Artifact Reduction for Supra Hyoid Neck CT in Patients With Dental Metals

Purpose: We investigated the effect of deep learning reconstruction (DLR) plus single-energy metal artifact reduction (SEMAR) on neck CT in patients with dental metals, comparing it with DLR and with hybrid iterative reconstruction (Hybrid IR)-SEMAR. Methods: In this retrospective study, 32 patients (25 men, 7 women; mean age: 63 ± 15 years) with dental metals underwent contrast-enhanced CT of the oral and oropharyngeal regions. Axial images were reconstructed using DLR, Hybrid IR-SEMAR, and DLR-SEMAR. In quantitative analyses, degrees of image noise and artifacts were evaluated. In one-by-one qualitative analyses, 2 radiologists evaluated metal artifacts, the depiction of structures, and noise on five-point scales. In side-by-side qualitative analyses, artifacts and overall image quality were evaluated by comparing Hybrid IR-SEMAR with DLR-SEMAR. Results: Artifacts were significantly less with DLR-SEMAR than with DLR in quantitative (P < .001) and one-by-one qualitative (P < .001) analyses, which resulted in significantly better depiction of most structures (P < .004). Artifacts in side-by-side analysis and image noise in quantitative and one-by-one qualitative analyses (P < .001) were significantly less with DLR-SEMAR than with Hybrid IR-SEMAR, resulting in significantly better overall quality of DLR-SEMAR. Conclusions: Compared with DLR and Hybrid IR-SEMAR, DLR-SEMAR provided significantly better supra hyoid neck CT images in patients with dental metals.

Advances in metal artifact reduction in CT images: A review of traditional and novel metal artifact reduction techniques

Metal artifacts degrade CT image quality, hampering clinical assessment. Numerous metal artifact reduction methods are available to improve the image quality of CT images with metal implants. In this review, an overview of traditional methods is provided including the modification of acquisition and reconstruction parameters, projection-based metal artifact reduction techniques (MAR), dual energy CT (DECT) and the combination of these techniques. Furthermore, the additional value and challenges of novel metal artifact reduction techniques that have been introduced over the past years are discussed such as photon counting CT (PCCT) and deep learning based metal artifact reduction techniques.

Impact of metal artifact reduction algorithm on gross tumor volume delineation in tonsillar cancer: reducing the interobserver variation

BACKGROUND

Patients with tonsillar cancer (TC) often have dental fillings that can significantly degrade the quality of computed tomography (CT) simulator images due to metal artifacts. We evaluated whether the use of the metal artifact reduction (MAR) algorithm reduced the interobserver variation in delineating gross tumor volume (GTV) of TC.

METHODS

Eighteen patients with TC with dental fillings were enrolled in this study. Contrast-enhanced CT simulator images were reconstructed using the conventional (CTCONV) and MAR algorithm (CTMAR). Four board-certified radiation oncologists delineated the GTV of primary tumors using routine clinical data first on CTCONV image datasets (GTVCONV), followed by CTCONV and CTMAR fused image datasets (GTVMAR) at least 2 weeks apart. Intermodality differences in GTV values and Dice similarity coefficient (DSC) were compared using Wilcoxon's signed-rank test.

RESULTS

GTVMAR was significantly smaller than GTVCONV for three observers. The other observer showed no significant difference between GTVCONV and GTVMAR values. For all four observers, the mean GTVCONV and GTVMAR values were 14.0 (standard deviation [SD]: 7.4) cm3 and 12.1 (SD: 6.4) cm3, respectively, with the latter significantly lower than the former (p < 0.001). The mean DSC of GTVCONV and GTVMAR was 0.74 (SD: 0.10) and 0.77 (SD: 0.10), respectively, with the latter significantly higher than that of the former (p < 0.001).

CONCLUSIONS

The use of the MAR algorithm led to the delineation of smaller GTVs and reduced interobserver variations in delineating GTV of the primary tumors in patients with TC.

Reduction of metal artifacts from knee tumor prostheses on CT images: value of the single energy metal artifact reduction (SEMAR) algorithm

Background

To evaluate the effect of the single energy metal artifact reduction (SEMAR) algorithm with a multidetector CT (MDCT) for knee tumor prostheses.

Methods

First, a phantom of knee tumor prosthesis underwent a MDCT scan. The raw data was reconstructed by iterative reconstruction (IR) alone and IR plus SEMAR. The mean value of the CT number and the image noise were measured around the prosthesis at the stem level and articular level. Second, 95 consecutive patients with knee tumor prostheses underwent MDCT scans. The raw data were also reconstructed by the two methods. Periprosthetic structures were selected at the similar two levels. Four radiologists visually graded the image quality on a scale from 0 to 5. Additionally, the readers also assessed the presence of prosthetic complication and tumor recurrence on a same scale.

Results

In the phantom, when the SEMAR was used, the CT numbers were closer to normal value and the noise of images using soft and sharper kernel were respectively reduced by up to 77.1% and 43.4% at the stem level, and by up to 82.2% and 64.5% at the articular level. The subjective scores increased 1 ~ 3 points and 1 ~ 4 points at the two levels, respectively. Prosthetic complications and tumor recurrence were diagnosed in 66 patients. And the SEMAR increased the diagnostic confidence of prosthetic complications and tumor recurrence (4 ~ 5 vs. 1 ~ 1.5).

Conclusions

The SEMAR algorithm can significantly reduce the metal artifacts and increase diagnostic confidence of prosthetic complications and tumor recurrence in patients with knee tumor prostheses.

Metal artefact reduction in the oral cavity using deep learning reconstruction algorithm in ultra-high-resolution computed tomography: a phantom study

OBJECTIVES

This study aimed to improve the impact of the metal artefact reduction (MAR) algorithm for the oral cavity by assessing the effect of acquisition and reconstruction parameters on an ultra-high-resolution CT (UHRCT) scanner.

METHODS

The mandible tooth phantom with and without the lesion was scanned using super-high-resolution, high-resolution (HR), and normal-resolution (NR) modes. Images were reconstructed with deep learning-based reconstruction (DLR) and hybrid iterative reconstruction (HIR) using the MAR algorithm. Two dental radiologists independently graded the degree of metal artefact (1, very severe; 5, minimum) and lesion shape reproducibility (1, slight; 5, almost perfect). The signal-to-artefact ratio (SAR), accuracy of the CT number of the lesion, and image noise were calculated quantitatively. The Tukey-Kramer method with a p-value of less than 0.05 was used to determine statistical significance.

RESULTS

The HR_DLR visual score was better than the NR_HIR score in terms of degree of metal artefact (4.6 ± 0.5 and 2.6 ± 0.5, p < 0.0001) and lesion shape reproducibility (4.5 ± 0.5 and 2.9 ± 1.1, p = 0.0005). The SAR of HR_DLR was significantly better than that of NR_HIR (4.9 ± 0.4 and 2.1 ± 0.2, p < 0.0001), and the absolute percentage error of the CT number in HR_DLR was lower than that in NR_HIR (0.8% in HR_DLR and 23.8% in NR_IR). The image noise of HR_DLR was lower than that of NR_HIR (15.7 ± 1.4 and 51.6 ± 15.3, p < 0.0001).

CONCLUSIONS

Our study demonstrated that the combination of HR mode and DLR in UHRCT scanner improved the impact of the MAR algorithm in the oral cavity.

Subtraction iodine imaging with area detector CT to improve tumor delineation and measurability of tumor size and depth of invasion in tongue squamous cell carcinoma

Purpose

Tumor size and depth of invasion (DOI) are mandatory assessments for tumor classification in tongue cancer but are often non-assessable on CT due to dental artifacts. This study investigated whether subtraction iodine imaging (SII) would improve tumor delineation and measurability.

Materials and methods

Fifty-seven consecutive patients with tongue cancer, who underwent scanning with a 320-row area detector CT with contrast administration and were treated with surgical resection, were retrospectively evaluated. CT was reconstructed with single-energy projection-based metallic artifact reduction (sCT). SII was generated by subtracting the pre-contrast volume scans from the post-contrast volume scans using a high-resolution deformable registration algorithm. MRI scans were also evaluated for comparing the ability of measurements. Two radiologists visually graded the tumor delineation using a 5-point scale. Tumor size and DOI were measured wherever possible. The tumor delineation score was compared using the Wilcoxon signed-rank method. Spearman’s correlations between imaging and pathological measurements were calculated. Intraclass correlation coefficients of measurements between readers were estimated.

Results

The tumor delineation score was greater on sCT-plus-SII than on sCT alone (medians: 3 and 1, respectively; p < 0.001), with higher number of detectable cases observed with sCT-plus-SII (36/57 [63.2%]) than sCT alone (21/57 [36.8%]). Tumor size and DOI measurability were higher with sCT-plus-SII (29/57 [50.9%]) than with sCT alone (17/57 [29.8%]). MRI had the highest detectability (52/57 [91.2%]) and measurability (46/57 [80.7%]). Correlation coefficients between radiological and pathological tumor size and DOI were similar for sCT (0.83–0.88), sCT-plus-SII (0.78–0.84), and MRI (0.78–0.90). Intraclass correlation coefficients were higher than 0.95 for each modality.

Conclusions

SII improves detectability and measurability of tumor size and DOI in patients with oral tongue squamous cell carcinoma, thus increasing the diagnostic potential. SII may also be beneficial for cases unevaluable on MRI due to artifacts or for patients with contraindications to MRI.

Lateral Position With Gantry Tilt Further Improves Computed Tomography Image Quality Reconstructed Using Single-Energy Metal Artifact Reduction Algorithm in the Oral Cavity

OBJECTIVE

To assess the limitations of single-energy metal artifact reduction algorithm in the oral cavity and evaluate the availability of a solution by setting the patient in a lateral position (LP) with the use of a gantry tilt (GT).

METHODS

We analyzed 88 patients with dental metals retrospectively in study 1, and 74 patients prospectively in study 2. Patients were classified: metal I with dental metals in 1 region, metal II in 2 regions, and metal III in 3 regions. Patients underwent neck computed tomography examinations in a supine position (SP) in study 1, and 2 positions, an LP with a GT and an SP, in study 2. All images were reconstructed with this algorithm. Image quality was scored using a 4-point scale: 1 = severe artifact, 2 = moderate artifact, 3 = slight artifact, 4 = no artifact. The scores were compared between metal I, metal II, and metal III using the Mann-Whitney U test in study 1, and between an LP with a GT and an SP using the Wilcoxon signed ranks test in study 2.

RESULTS

The scores outside the dental arch were significantly higher in metal I than in metal II and metal III (3.0 ± 0.6 vs 2.3 ± 0.5 vs 2.2 ± 0.4; P < 0.0001 for metal I vs metal II and for metal I vs metal III) and significantly higher in an LP with a GT than an SP (3.2 ± 0.4 vs 2.3 ± 0.4; P < 0.0001).

CONCLUSIONS

Single-energy metal artifact reduction algorithm could reduce metal artifacts adequately in patients with dental metals in 1 region, but not in 2 or more regions. However, even for the latter, combination of this algorithm and an LP with a GT could further improve the image quality.

Utility of second-generation single-energy metal artifact reduction in helical lung computed tomography for patients with pulmonary arteriovenous malformation after coil embolization

PURPOSE

The quality of images acquired using single-energy metal artifact reduction (SEMAR) on helical lung computed tomography (CT) in patients with pulmonary arteriovenous malformation (PAVM) after coil embolization was retrospectively evaluated.

MATERIALS AND METHODS

CT images were reconstructed with and without SEMAR. Twenty-seven lesions [20 patients (2 males, 18 females), mean age 61.2 ± 11.0 years; number of embolization coils, 9.8 ± 5.0] on contrast-enhanced CT and 18 lesions of non-enhanced lung CT concurrently performed were evaluated. Regions of interest were positioned around the coils and mean standard deviation value was compared as noise index. Two radiologists visually evaluated metallic coil artifacts using a four-point scale: 4 = minimal; 3 = mild; 2 = strong; 1 = extensive.

RESULTS

Noise index was significantly improved with SEMAR versus without SEMAR (median [interquartile range]; 194.4 [161.6-211.9] Hounsfield units [HU] vs. 243.9 [220.4-286.0] HU; p < 0.001). Visual score was significantly improved with SEMAR versus without SEMAR (Reader 1, 3 [3] vs.1 [1]; Reader 2, 3 [3] vs.1 [1]; p < 0.001). Significant differences were similarly demonstrated on lung CT (p < 0.001).

CONCLUSION

SEMAR provided clear chest CT images in patients who underwent PAVM coil embolization.

[Improvement of CT Imaging with a Metal Artifact Reduction Technique for Radiation Treatment Planning-Fundamental Study of Structure Delineation and Dose Calculation]

In radiotherapy planning, CT images are widely used to delineate the gross tumor volume (GTV) and the organs at risks (OARs), which allows for the calculation of the dose distribution to each structure. The delineated contours of the GTV and OARs may become inaccurate, and subsequently result in the inaccurate derivation of the dose distribution, if there are metal artifacts present in the CT image. The metal artifact reduction technique, single energy metal artifact reduction (SEMAR), installed on the CT system (Aquilion ONE^TM Vision Edition, Toshiba Medical Systems Corporation) could potentially reduce metal artifacts. Therefore, we investigated whether SEMAR can improve the accuracy of delineation, and subsequently the dosimetric accuracy, in the treatment planning process. Using an acrylonitrile-butadiene-styrene resin phantom (RT-3000-New, R-Tech. Inc, Tokyo, Japan), titanium bars were inserted on both the left and right sides, and four types of electron density inserts (rods) were separately inserted in the middle. The electron densities of the rods were 0.90, 0.96, 1.07, and 1.09. After CT images were acquired, SEMAR-ON (when applying the SEMAR correction) images were generated. On both SEMAR-ON and SEMAR-OFF (when not applying the SEMAR correction) images, the rod contours were delineated automatically, using a CT value threshold. This threshold was selected so that the area of the automatically delineated contour was 615.4 mm². The difference in the contour area of SEMAR-ON, SEMAR-OFF, and no metal artifact images were compared using the dice coefficient. When SEMAR was used, the dice coefficient improved by 57.4%. Therefore, SEMAR was considered to be useful in improving the accuracy of GTV and OAR delineation.

CT venography after knee replacement surgery: comparison of dual-energy CT-based monochromatic imaging and single-energy metal artifact reduction techniques on a 320-row CT scanner

Background

An optimal metal artifact reduction (MAR) technique is needed for a reliable and accurate image-based diagnosis.

Purpose

Using a 320-row scanner, we compared the dual-energy computed tomography (CT)-based monochromatic and the single-energy metal artifact reduction (SEMAR) techniques for CT venography (CTV) to identify the better imaging method for diagnosing deep vein thrombosis (DVT) in patients who had undergone knee replacement surgery.

Material and Methods

Twenty-three consecutive patients with suspected DVT after unilateral knee replacement surgery underwent dual-energy CT (135/80 kVp). Monochromatic images of 35–135 keV were generated; the monochromatic image with the best signal-to-noise ratio (SNR) of the popliteal vein near the metal prosthesis were selected. The projection data of 80 kVp were reconstructed using MAR algorithm. The mean SNR ON MAR and the best SNR ON monochromatic images were compared. Two radiologists evaluated visualization of the metal artifacts on a four-point scale where 1 = extensive artifacts, 2 = strong artifacts, 3 = mild artifacts, and 4 = minimal artifacts.

Results

The mean SNR was significantly higher on the MAR than the monochromatic images (12.8 ± 4.7 versus 7.7 ± 5.1, P < 0.01) and the visual scores were significantly higher for MAR than monochromatic images (2.6 ± 0.8 versus 1.3 ± 0.4, P < 0.01).

Conclusion

For CTV after knee replacement surgery, the MAR technique is superior to the monochromatic imaging technique.

Reduction of metal artifacts due to dental hardware in computed tomography angiography: assessment of the utility of model-based iterative reconstruction

PURPOSE

The aim of this study is to assess the value of adaptive statistical iterative reconstruction (ASIR) and model-based iterative reconstruction (MBIR) for reduction of metal artifacts due to dental hardware in carotid CT angiography (CTA).

METHODS

Thirty-seven patients with dental hardware who underwent carotid CTA were included. CTA was performed with a GE Discovery CT750 HD scanner and reconstructed with filtered back projection (FBP), ASIR, and MBIR. We measured the standard deviation at the cervical segment of the internal carotid artery that was affected most by dental metal artifacts (SD₁) and the standard deviation at the common carotid artery that was not affected by the artifact (SD₂). We calculated the artifact index (AI) as follows: AI = [(SD₁)2 - (SD₂)2]1/2 and compared each AI for FBP, ASIR, and MBIR. Visual assessment of the internal carotid artery was also performed by two neuroradiologists using a five-point scale for each axial and reconstructed sagittal image. The inter-observer agreement was analyzed using weighted kappa analysis.

RESULTS

MBIR significantly improved AI compared with FBP and ASIR (p < 0.001, each). We found no significant difference in AI between FBP and ASIR (p = 0.502). The visual score of MBIR was significantly better than those of FBP and ASIR (p < 0.001, each), whereas the scores of ASIR were the same as those of FBP. Kappa values indicated good inter-observer agreements in all reconstructed images (0.747-0.778).

CONCLUSIONS

MBIR resulted in a significant reduction in artifact from dental hardware in carotid CTA.

Metal Artifact Reduction in Computed Tomography After Deep Brain Stimulation Electrode Placement Using Iterative Reconstructions

OBJECTIVES

Diagnostic accuracy of intraoperative computed tomography (CT) after deep brain stimulation (DBS) electrode placement is limited due to artifacts induced by the metallic hardware, which can potentially mask intracranial postoperative complications. Different metal artifact reduction (MAR) techniques have been introduced to reduce artifacts from metal hardware in CT. The purpose of this study was to assess the impact of a novel iterative MAR technique on image quality and diagnostic performance in the follow-up of patients with DBS electrode implementation surgery.

MATERIALS AND METHODS

Seventeen patients who had received routine intraoperative CT of the head after implantation of DBS electrodes between March 2015 and June 2015 were retrospectively included. Raw data of all patients were reconstructed with standard weighted filtered back projection (WFBP) and additionally with a novel iterative MAR algorithm. We quantified frequencies of density changes to assess quantitative artifact reduction. For evaluation of qualitative image quality, the visibility of numerous cerebral anatomic landmarks and the detectability of intracranial electrodes were scored according to a 4-point scale. Furthermore, artifact strength overall and adjacent to the electrodes was rated.

RESULTS

Our results of quantitative artifact reduction showed that images reconstructed with iterative MAR (iMAR) contained significantly lower metal artifacts (overall low frequency values, 1608.6 ± 545.5; range, 375.5-3417.2) compared with the WFBP (overall low frequency values, 4487.3 ± 875.4; range, 2218.3-5783.5) reconstructed images (P < 0.004). Qualitative image analysis showed a significantly improved image quality for iMAR (overall anatomical landmarks, 2.49 ± 0.15; median, 3; range, 0-3; overall electrode characteristics, 2.35 ± 0.16; median, 2; range, 0-3; artifact characteristics, 2.16 ± 0.08; median, 2.5; range, 0-3) compared with WFBP (overall anatomical landmarks, 1.21 ± 0.64; median, 1; range, 0-3; overall electrode characteristics, 0.74 ± 0.37; median, 1; range, 0-2; artifact characteristics, 0.51 ± 0.15; median, 0.5; range, 0-2; P < 0.002).

CONCLUSIONS

Reconstructions of cranial CT images with the novel iMAR algorithm in patients after DBS implantation allows an efficient reduction of metal artifacts near DBS electrodes compared with WFBP reconstructions. We demonstrated an improvement of quantitative and qualitative image quality of iMAR compared with WFBP in patients with DBS electrodes.

Coronary CT angiography in patients with implanted cardiac devices: initial experience with the metal artefact reduction technique

OBJECTIVE

Single-energy metal artefact reduction (SEMAR), a new technique that can now be used in routine CT examinations, has recently become applicable to volume data acquired with electrocardiography gating. We evaluated the effect of this technique on the visualization of the coronary arteries in patients harboring cardiac devices.

METHODS

We subjected 8 patients (7 males, 1 female; mean age 65.5 ± 11.3 years) with implanted cardiac devices to coronary CT angiography on a 320-slice CT scanner (Aquilion ONE Vision^™; Toshiba Medical Systems Corp., Tokyo, Japan). Image data sets were reconstructed with and without SEMAR. Two radiologists visually evaluated the image quality based on metal artefacts from the electronic device leads using a four-point scale (1 = vessel not visible to 4 = minimal or no metal artefacts). Images with a score of 3 or 4 were considered diagnostic.

RESULTS

In both SEMAR and non-SEMAR data sets, 94 coronary artery segments were available for evaluation. Without SEMAR, 11 segments (11.7%) were rated as non-diagnostic; SEMAR improved the image quality of 9 of the 11 segments (81.8%), and the images became diagnostic.

CONCLUSION

SEMAR reduced metal artefacts from the electronic device leads and improved the image quality of the coronary arteries in patients with cardiac devices. Advances in knowledge: SEMAR has recently become applicable to volume data acquired with electrocardiography gating. SEMAR reduces metal artefacts elicited by electronic device leads and improves the image quality of the coronary arteries in patients with cardiac devices.

Single-energy metal artifact reduction for helical computed tomography of the pelvis in patients with metal hip prostheses

PURPOSE

To compare the quality of helical computed tomography (CT) images of the pelvis in patients with metal hip prostheses reconstructed using adaptive iterative dose reduction (AIDR) and AIDR with single-energy metal artifact reduction (SEMAR-A).

MATERIALS AND METHODS

This retrospective study included 28 patients (mean age, 64.6 ± 11.4 years; 6 men and 22 women). CT images were reconstructed using AIDR and SEMAR-A. Two radiologists evaluated the extent of metal artifacts and the depiction of structures in the pelvic region and looked for mass lesions. A radiologist placed a region of interest within the bladder and recorded CT attenuation.

RESULTS

The metal artifacts were significantly reduced in SEMAR-A as compared to AIDR (p < 0.0001). The depictions of the bladder, ureter, prostate/uterus, rectum, and pelvic sidewall were significantly better with SEMAR-A than with AIDR (p < 0.02). All lesions were diagnosed with SEMAR-A, while some were not diagnosed with AIDR. The median and interquartile range (in parentheses) of CT attenuation within the bladder for AIDR were -34.0 (-46.6 to -15.0) Hounsfield units (HU) and were more variable than those seen for SEMAR-A [5.4 (-1.3 to 11.1)] HU (p = 0.033).

CONCLUSION

In comparison with AIDR, SEMAR-A provided pelvic CT images of significantly better quality for patients with metal hip prostheses.

Metal artefact reduction for patients with metallic dental fillings in helical neck computed tomography: comparison of adaptive iterative dose reduction 3D (AIDR 3D), forward-projected model-based iterative reconstruction solution (FIRST) and AIDR 3D with single-energy metal artefact reduction (SEMAR)

OBJECTIVES

To compare the differences in metal artefact degree and the depiction of structures in helical neck CT, in patients with metallic dental fillings, among adaptive iterative dose reduction three dimensional (AIDR 3D), forward-projected model-based iterative reconstruction solution (FIRST) and AIDR 3D with single-energy metal artefact reduction (SEMAR-A).

METHODS

In this retrospective clinical study, 22 patients (males, 13; females, 9; mean age, 64.6 ± 12.6 years) with metallic dental fillings who underwent contrast-enhanced helical CT involving the oropharyngeal region were included. Neck axial images were reconstructed with AIDR 3D, FIRST and SEMAR-A. Metal artefact degree and depiction of structures (the apex and root of the tongue, parapharyngeal space, superior portion of the internal jugular chain and parotid gland) were evaluated on a four-point scale by two radiologists. Placing regions of interest, standard deviations of the oral cavity and nuchal muscle (at the slice where no metal exists) were measured and metal artefact indices were calculated (the square root of the difference of the squares of them).

RESULTS

In SEMAR-A, metal artefact was significantly reduced and depictions of all structures were significantly improved compared with those in FIRST and AIDR 3D (p ≤ 0.001, sign test). Metal artefact index for the oral cavity in AIDR 3D/FIRST/SEMAR-A was 572.0/477.7/88.4, and significant differences were seen between each reconstruction algorithm (p < 0.0001, Wilcoxon signed-rank test).

CONCLUSIONS

SEMAR-A could provide images with lesser metal artefact and better depiction of structures than AIDR 3D and FIRST.

Multiparametric Evaluation of Head and Neck Squamous Cell Carcinoma Using a Single-Source Dual-Energy CT with Fast kVp Switching: State of the Art

There is an increasing body of evidence establishing the advantages of dual-energy CT (DECT) for evaluation of head and neck squamous cell carcinoma (HNSCC). Focusing on a single-source DECT system with fast kVp switching, we will review the principles behind DECT and associated post-processing steps that make this technology especially suitable for HNSCC evaluation and staging. The article will review current applications of DECT for evaluation of HNSCC including use of different reconstructions to improve tumor conspicuity, tumor-normal soft tissue interface, accuracy of invasion of critical structures such as thyroid cartilage, and reduce dental artifact. We will provide a practical approach for DECT implementation into routine clinical use and a multi-parametric approach for scan interpretation based on the experience at our institution. The article will conclude with a brief overview of potential future applications of the technique.