An update on advanced dual-energy CT for head and neck cancer imaging

Dual-energy computed tomography for predicting cervical lymph node metastasis in laryngeal squamous cell carcinoma

Rationale and objectives

We constructed a dual-energy computed tomography (DECT)-based model to assess cervical lymph node metastasis (LNM) in patients with laryngeal squamous cell carcinoma (LSCC).

Materials and methods

We retrospectively analysed 164 patients with LSCC who underwent preoperative DECT from May 2019 to May 2023. The patients were randomly divided into training (n = 115) and validation (n = 49) cohorts. Quantitative DECT parameters of the primary tumours and their clinical characteristics were collected. A logistic regression model was used to determine independent predictors of LNM, and a nomogram was constructed along with a corresponding online model. Model performance was assessed using the area under the curve (AUC) and the calibration curve, and the clinical value was evaluated using decision curve analysis (DCA).

Results

In total, 64/164 (39.0 %) patients with LSCC had cervical LNM. Independent predictors of LNM included normalized iodine concentration in the arterial phase (odds ratio [OR]: 8.332, 95 % confidence interval [CI]: 2.813-24.678, P < 0.001), normalized effective atomic number in the arterial phase (OR: 5.518, 95 % CI: 1.095-27.818, P = 0.002), clinical T3-4 stage (OR: 5.684, 95 % CI: 1.701-18.989, P = 0.005), and poor histological grade (OR: 5.011, 95 % CI: 1.003-25.026, P = 0.049). These predictors were incorporated into the DECT-based nomogram and the corresponding online model, showing good calibration and favourable performance (training AUC: 0.910, validation AUC: 0.918). The DCA indicated a significant clinical benefit of the nomogram for estimating LNM.

Conclusions

DECT parameters may be useful independent predictors of LNM in patients with LSCC, and a DECT-based nomogram may be helpful in clinical decision-making.

Quantitative parameter analysis of pretreatment dual-energy computed tomography in nasopharyngeal carcinoma cervical lymph node characteristics and prediction of radiotherapy sensitivity

BACKGROUND

Treatment efficacy may differ among patients with nasopharyngeal carcinoma (NPC) at similar tumor-node-metastasis stages. Moreover, end-of-treatment tumor regression is a reliable indicator of treatment sensitivity. This study aimed to investigate whether quantitative dual-energy computed tomography (DECT) parameters could predict sensitivity to neck-lymph node radiotherapy in patients with NPC.

METHODS

Overall, 388 lymph nodes were collected from 98 patients with NPC who underwent pretreatment DECT. The patients were divided into complete response (CR) and partial response (PR) groups. Clinical characteristics and quantitative DECT parameters were compared between the groups, and the optimal predictive ability of each parameter was determined using receiver operating characteristic (ROC) analysis. A nomogram prediction model was constructed and validated using univariate and binary logistic regression.

RESULTS

DECT parameters were higher in the CR group than in the PR group. The iodine concentration (IC), normalized IC, Mix-0.6, spectral Hounsfield unit curve slope, effective atomic number, and virtual monoenergetic images were significantly different between the groups. The area under the ROC curve of the DECT parameters was 0.73-0.77. Based on the binary logistic regression, a column chart was constructed using 10 predictive factors, including age, sex, N stage, maximum lymph node diameter, arterial phase NIC, venous phase NIC, λHU and spectral Hounsfield units at 70 keV. The area under the ROC curve value of the constructed model was 0.813, with a sensitivity and specificity of 85.6% and 81.3%, respectively.

CONCLUSION

Quantitative DECT parameters could effectively predict the sensitivity of NPC to radiotherapy. Therefore, DECT parameters and NPC clinical features can be combined to construct a nomogram with high predictive power and used as a clinical analytical tool.

Detection of malignant lesions in cytologically indeterminate thyroid nodules using a dual-layer spectral detector CT-clinical nomogram

Purpose

To evaluate the capability of dual-layer detector spectral CT (DLCT) quantitative parameters in conjunction with clinical variables to detect malignant lesions in cytologically indeterminate thyroid nodules (TNs).

Materials and methods

Data from 107 patients with cytologically indeterminate TNs who underwent DLCT scans were retrospectively reviewed and randomly divided into training and validation sets (7:3 ratio). DLCT quantitative parameters (iodine concentration (IC), NICP (IC nodule/IC thyroid parenchyma), NICA (IC nodule/IC ipsilateral carotid artery), attenuation on the slope of spectral HU curve and effective atomic number), along with clinical variables, were compared between benign and malignant cohorts through univariate analysis. Multivariable logistic regression analysis was employed to identify independent predictors which were used to construct the clinical model, DLCT model, and combined model. A nomogram was formulated based on optimal performing model, and its performance was assessed using receiver operating characteristic curve, calibration curve, and decision curve analysis. The nomogram was subsequently tested in the validation set.

Results

Independent predictors associated with malignant TNs with indeterminate cytology included NICP in the arterial phase, Hashimoto's Thyroiditis (HT), and BRAF V600E (all p < 0.05). The DLCT-clinical nomogram, incorporating the aforementioned variables, exhibited superior performance than the clinical model or DLCT model in both training set (AUC: 0.875 vs 0.792 vs 0.824) and validation set (AUC: 0.874 vs 0.792 vs 0.779). The DLCT-clinical nomogram demonstrated satisfactory calibration and clinical utility in both training set and validation set.

Conclusion

The DLCT-clinical nomogram emerges as an effective tool to detect malignant lesions in cytologically indeterminate TNs.

Diagnosis of cervical lymphoma using a YOLO-v7-based model with transfer learning

To investigate the ability of an auxiliary diagnostic model based on the YOLO-v7-based model in the classification of cervical lymphadenopathy images and compare its performance against qualitative visual evaluation by experienced radiologists. Three types of lymph nodes were sampled randomly but not uniformly. The dataset was randomly divided into for training, validation, and testing. The model was constructed with PyTorch. It was trained and weighting parameters were tuned on the validation set. Diagnostic performance was compared with that of the radiologists on the testing set. The mAP of the model was 96.4% at the 50% intersection-over-union threshold. The accuracy values of it were 0.962 for benign lymph nodes, 0.982 for lymphomas, and 0.960 for metastatic lymph nodes. The precision values of it were 0.928 for benign lymph nodes, 0.975 for lymphomas, and 0.927 for metastatic lymph nodes. The accuracy values of radiologists were 0.659 for benign lymph nodes, 0.836 for lymphomas, and 0.580 for metastatic lymph nodes. The precision values of radiologists were 0.478 for benign lymph nodes, 0.329 for lymphomas, and 0.596 for metastatic lymph nodes. The model effectively classifies lymphadenopathies from ultrasound images and outperforms qualitative visual evaluation by experienced radiologists in differential diagnosis.

Effect of Hashimoto's thyroiditis on the dual-energy CT quantitative parameters and performance in diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer

BACKGROUND

To evaluate the effect of Hashimoto's thyroiditis (HT) on dual-energy computed tomography (DECT) quantitative parameters of cervical lymph nodes (LNs) in patients with papillary thyroid cancer (PTC), and its effect on the diagnostic performance and threshold of DECT in preoperatively identifying metastatic cervical LNs.

METHODS

A total of 479 LNs from 233 PTC patients were classified into four groups: HT+/LN+, HT+/LN-, HT-/LN + and HT-/LN - group. DECT quantitative parameters including iodine concentration (IC), normalized IC (NIC), effective atomic number (Zeff), and slope of the spectral Hounsfield unit curve (λHU) in the arterial phase (AP) and venous phase were compared. Receiver operating characteristic curve analyses were performed to evaluate DECT parameters' diagnostic performance in differentiating metastatic from nonmetastatic LNs in the HT - and HT + groups.

RESULTS

The HT+/LN + group exhibited lower values of DECT parameters than the HT-/LN + group (all p < 0.05). Conversely, the HT+/LN - group exhibited higher values of DECT parameters than the HT-/LN - group (all p < 0.05). In the HT + group, if an AP-IC of 1.850 mg/mL was used as the threshold value, then the optimal diagnostic performance (area under the curve, 0.757; sensitivity, 69.4%; specificity, 71.0%) could be obtained. The optimal threshold value of AP-IC in the HT - group was 2.050 mg/mL. In contrast, in the HT - group, AP-NIC demonstrated the highest area under the curve of 0.988, when an optimal threshold of 0.243 was used. The optimal threshold value of AP-NIC was 0.188 in the HT + group.

CONCLUSIONS

HT affected DECT quantitative parameters of LNs and subsequent the diagnostic thresholds. When using DECT to diagnose metastatic LNs in patients with PTC, whether HT is coexistent should be clarified considering the different diagnostic thresholds.

Development and Validation of a Dual-Energy CT-Based Model for Predicting the Number of Central Lymph Node Metastases in Clinically Node-Negative Papillary Thyroid Carcinoma

RATIONALE AND OBJECTIVES

This study aimed to develop and validate a dual-energy CT (DECT)-based model for preoperative prediction of the number of central lymph node metastases (CLNMs) in clinically node-negative (cN0) papillary thyroid carcinoma (PTC) patients.

MATERIALS AND METHODS

Between January 2016 and January 2021, 490 patients who underwent lobectomy or thyroidectomy, CLN dissection, and preoperative DECT examinations were enrolled and randomly allocated into the training (N = 345) and validation cohorts (N = 145). The patients' clinical characteristics and quantitative DECT parameters obtained on primary tumors were collected. Independent predictors of> 5 CLNMs were identified and integrated to construct a DECT-based prediction model, for which the area under the curve (AUC), calibration, and clinical usefulness were assessed. Risk group stratification was performed to distinguish patients with different recurrence risks.

RESULTS

More than 5 CLNMs were found in 75 (15.3%) cN0 PTC patients. Age, tumor size, normalized iodine concentration (NIC), normalized effective atomic number (nZeff) and the slope of the spectral Hounsfield unit curve (λHu) in the arterial phase were independently associated with> 5 CLNMs. The DECT-based nomogram that incorporated predictors demonstrated favorable performance in both cohorts (AUC: 0.842 and 0.848) and significantly outperformed the clinical model (AUC: 0.688 and 0.694). The nomogram showed good calibration and added clinical benefit for predicting> 5 CLNMs. The KaplanMeier curves for recurrence-free survival showed that the high- and low-risk groups stratified by the nomogram were significantly different.

CONCLUSION

The nomogram based on DECT parameters and clinical factors could facilitate preoperative prediction of the number of CLNMs in cN0 PTC patients.

Dual-energy computed tomography for improved visualization of internal jugular chain neck lymph node metastasis and nodal necrosis in head and neck squamous cell carcinoma

PURPOSE

To evaluate and compare the utility of 40-keV virtual monochromatic imaging (VMI) reconstructed from dual-energy computed tomography (DECT) in the assessment of neck lymph node metastasis with 70-keV VMI, which is reportedly equivalent to conventional 120-kVp single-energy computed tomography.

MATERIALS AND METHODS

Patients with head and neck squamous cell carcinoma who had neck lymph node metastasis in contact with the sternocleidomastoid muscle (SCM) and underwent contrast-enhanced DECT were included. In 40- and 70-keV VMI, contrast differences and contrast noise ratio (CNR) between the solid component of neck lymph node metastasis (SC) and the SCM and between SC and nodal necrosis (NN) were calculated. Two board-certified radiologists independently and qualitatively evaluated the boundary discrimination between SC and SCM and the diagnostic certainty of NN.

RESULTS

We evaluated 45 neck lymph node metastases. The contrast difference between SC and SCM and SC and NN were significantly higher at 40-keV VMI than at 70-keV VMI (p < 0.001). The CNR between SC and SCM was significantly higher at 40-keV VMI than at 70-keV VMI (p < 0.001). Scoring of the boundary discrimination between SC and SCM as well as the diagnostic certainty of NN at 40-keV VMI was significantly higher than that at 70-keV VMI (p < 0.001). The inter-rater agreements for these scores were higher at 40-keV VMI than at 70-keV VMI.

CONCLUSION

Additional employing 40-keV VMI in routine clinical practice may be useful in the diagnosis of head and neck lymph node metastases and nodal necrosis.

The diagnostic value of dual-layer CT in the assessment of lymph nodes in lymphoma patients with PET/CT as a reference standard

This study aimed to evaluate the diagnostic performances of dual-layer CT (DLCT) for the identification of positive lymph nodes (LNs) in patients with lymphoma and retrospectively included 1165 LNs obtained by biopsy from 78 patients with histologically proven lymphoma, who underwent both pretreatment DLCT and 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT). According to 18F-FDG PET/CT findings as a reference standard, cases were categorized into the LN-negative and LN-positive groups. LNs were then randomly divided at a ratio of 7:3 into the training (n = 809) and validation (n = 356) cohorts. The patients' clinical characteristics and quantitative parameters including spectral curve slope (λHU), iodine concentration (IC) on arterial phase (AP) and venous phase (VP) images were compared between the LN-negative and LN-positive groups using Chi-square test, t-test or Mann-Whitney U test for categorical variables or quantitative parameters. Multivariate logistic regression analysis with tenfold cross-validation was performed to establish the most efficient predictive model in the training cohort. The area under the curve (AUC) was used to evaluate the diagnostic value of the predictive model, and differences in AUC were determined by the DeLong test. Moreover, the predictive model was validated in the validation cohort. Repeatability analysis was performed for LNs using intraclass correlation coefficients (ICCs). In the training cohort, long diameter (LD) had the highest AUC as an independent factors compared to other parameter in differentiating LN positivity from LN negativity (p = 0.006 to p < 0.001), and the AUC of predictive model jointly involving LD and λHU-AP was significantly elevated (AUC of 0.816, p < 0.001). While the AUC of predictive model in the validation cohort was 0.786. Good to excellent repeatability was observed for all parameters (ICC > 0.75). The combination of DLCT with morphological and functional parameters may represent a potential imaging biomarker for detecting LN positivity in lymphoma.

Development of a dual energy CT based model to assess response to treatment in patients with high grade serous ovarian cancer: a pilot cohort study

BACKGROUND

In patients with cancer, the current gold standard for assessing response to treatment involves measuring cancer lesions on computed tomography (CT) imaging. The percentage change in size of specific lesions determines whether patients have had a complete/partial response or progressive disease, according to RECIST criteria. Dual Energy CT (DECT) permits additional measurements of iodine concentration, a surrogate marker of vascularity. Here we explore the role of changes in iodine concentration within cancer tissue on CT scans to assess its suitability for determining treatment response in patients with high grade serous ovarian cancer (HGSOC).

METHODS

Suitable RECIST measurable lesions were identified from the CT images of HGSOC patients, taken at 2 different time points (pre and post treatment). Changes in size and iodine concentration were measured for each lesion. PR/SD were classified as responders, PD was classified as non-responder. Radiological responses were correlated with clinical and CA125 outcomes.

RESULTS

62 patients had appropriate imaging for assessment. 22 were excluded as they only had one DECT scan. 32/40 patients assessed (113 lesions) had received treatment for relapsed HGSOC. RECIST and GCIG (Gynaecologic Cancer Inter Group) CA125 criteria / clinical assessment of response for patients was correlated with changes in iodine concentration, before and after treatment. The prediction of median progression free survival was significantly better associated with changes in iodine concentration (p = 0.0001) and GCIG Ca125 / clinical assessment (p = 0.0028) in comparison to RECIST criteria (p = 0.43).

CONCLUSION

Changes in iodine concentration from dual energy CT imaging may be more suitable than RECIST in assessing response to treatment in patients with HGSOC.

TRIAL REGISTRATION

CICATRIx IRAS number 198179, 14 Dec 2015, https://www.myresearchproject.org.uk/ .

Nomogram based on spectral CT quantitative parameters and typical radiological features for distinguishing benign from malignant thyroid micro-nodules

PURPOSE

To analyse the predictive effect of a nomogram combining dual-layer spectral computed tomography (DSCT) quantitative parameters with typical radiological features in distinguishing benign micro-nodule from thyroid microcarcinoma (TMC).

METHODS

Data from 342 instances with thyroid micro-nodules (≤1 cm) who underwent DSCT (benign group: n = 170; malignant group: n = 172) were reviewed. Typical radiological features including micro-calcification and enhanced blurring, and DSCT quantitative parameters including attenuation on virtual monoenergetic images (40 keV, 70 keV and 100 keV), the slope of the spectral HU curve (λHU), normalized iodine concentration (NIC), and normalized effective atomic number (NZeff) in the arterial phase (AP) and venous phase (VP), were measured and compared between the benign and malignant groups. The receiver operating characteristic (ROC) curve was used to assess the diagnostic performance of significant quantitative DSCT parameters or the models combining DSCT parameters respectively and typical radiological features based on multivariate logistic regression (LR) analysis. A nomogram was developed using predictors with the highest diagnostic performance in the above model, as determined by multivariate LR analysis.

RESULTS

The DSCT parameter APλHU showed the greatest diagnostic efficiency in identifying patients with TMC, with an area under the ROC curve (AUC) of 0.829, a sensitivity and specificity of 0.738 and 0.753, respectively. Then, APλHU was combined with the two radiological features to construct the DSCT-Radiological nomogram, which had an AUC of 0.858, a sensitivity of 0.791 and a specificity of 0.800. The calibration curve of the nomogram demonstrated that the prediction result was in good agreement with the actual observation. The decision curve revealed that the nomogram can result in a greater net benefit than the all/none-intervention strategy for all threshold probabilities.

CONCLUSION

As a valid and visual noninvasive prediction tool, the DSCT-Radiological nomogram incorporating DSCT quantitative parameters and radiological features shows favourable predictive efficiency for identifying benign and malignant thyroid micro-nodules.

Spectral CT-based radiomics signature for distinguishing malignant pulmonary nodules from benign

OBJECTIVES

To evaluate the discriminatory capability of spectral CT-based radiomics to distinguish benign from malignant solitary pulmonary solid nodules (SPSNs).

MATERIALS AND METHODS

A retrospective study was performed including 242 patients with SPSNs who underwent contrast-enhanced dual-layer Spectral Detector CT (SDCT) examination within one month before surgery in our hospital, which were randomly divided into training and testing datasets with a ratio of 7:3. Regions of interest (ROIs) based on 40-65 keV images of arterial phase (AP), venous phases (VP), and 120kVp of SDCT were delineated, and radiomics features were extracted. Then the optimal radiomics-based score in identifying SPSNs was calculated and selected for building radiomics-based model. The conventional model was developed based on significant clinical characteristics and spectral quantitative parameters, subsequently, the integrated model combining radiomics-based model and conventional model was established. The performance of three models was evaluated with discrimination, calibration, and clinical application.

RESULTS

The 65 keV radiomics-based scores of AP and VP had the optimal performance in distinguishing benign from malignant SPSNs (AUC_65keV-AP = 0.92, AUC_65keV-VP = 0.88). The diagnostic efficiency of radiomics-based model (AUC = 0.96) based on 65 keV images of AP and VP outperformed conventional model (AUC = 0.86) in the identification of SPSNs, and that of integrated model (AUC = 0.97) was slightly further improved. Evaluation of three models showed the potential for generalizability.

CONCLUSIONS

Among the 40-65 keV radiomics-based scores based on SDCT, 65 keV radiomics-based score had the optimal performance in distinguishing benign from malignant SPSNs. The integrated model combining radiomics-based model based on 65 keV images of AP and VP with Z_eff-AP was significantly superior to conventional model in the discrimination of SPSNs.

Diagnosing cervical lymph node metastasis in oral squamous cell carcinoma based on third-generation dual-source, dual-energy computed tomography

OBJECTIVES

To investigate the potential of dual-energy computed tomography (DECT) parameters in identifying metastatic cervical lymph nodes in oral squamous cell carcinoma (OSCC) patients and to explore the relationships between DECT and pathological features.

METHODS

Clinical and DECT data were collected from patients who underwent radical resection of OSCC and cervical lymph node dissection between November 2019 and June 2021. Microvascular density was assessed using the Weidner counting method. The electron density (ED) and effective atomic number (Z_eff) in non - contrast phase and iodine concentration (IC), normalized IC, slope of the energy spectrum curve (λ_HU), and dual-energy index (DEI) in parenchymal phase were compared between metastatic and non - metastatic lymph nodes. Student's t-test, Pearson's rank correlation, and receiver operating characteristic curves were performed.

RESULTS

The inclusion criteria were met in 399 lymph nodes from 103 patients. Metastatic nodes (n = 158) displayed significantly decreased ED, IC, normalized IC, λ_HU, and DEI values compared with non-metastatic nodes (n = 241) (all p < 0.01). Strong correlations were found between IC (r = 0.776), normalized IC (r = 0.779), λ_HU (r = 0.738), DEI (r = 0.734), and microvascular density. Area under the curve (AUC) for normalized IC performed the highest (0.875) in diagnosing metastatic nodes. When combined with the width of nodes, AUC increased to 0.918.

CONCLUSION

DECT parameters IC, normalized IC, λ_HU, and DEI reflect pathologic changes in lymph nodes to a certain extent, and aid for detection of metastatic cervical lymph nodes from OSCC.

KEY POINTS

• Electron density, iodine concentration, normalized iodine concentration, λ_HU, and dual-energy index values showed significant differences between metastatic and non-metastatic nodes. • Strong correlations were found between iodine concentration, normalized iodine concentration, slope of the spectral Hounsfield unit curve, dual-energy index, and microvascular density. • DECT qualitative parameters reflect the pathologic changes in lymph nodes to a certain extent, and aid for the detection of metastatic cervical lymph nodes from oral squamous cell carcinoma.

Laryngeal and hypopharyngeal squamous cell carcinoma: association between quantitative parameters derived from dual-energy CT and histopathological prognostic factors

BACKGROUND

Dual-energy computed tomography (DECT) can provide objective evaluation of laryngeal and hypopharyngeal squamous cell carcinoma (LHSCC).

PURPOSE

To investigate the relationship between quantitative parameters acquired from DECT and histopathological prognostic factors in LHSCC.

MATERIAL AND METHODS

A total of 65 patients with LHSCC who underwent arterial phase and venous phase DECT scans were retrospectively enrolled. Iodine concentration (IC) and normalized IC (NIC) of the tumor were calculated in both the arterial (IC_A and NIC_A) and venous (IC_V and NIC_V) phases, and compared among different pathological grades, T stages, and lymph node stages. Receiver operating characteristic (ROC) curves were generated to evaluate their diagnostic performance.

RESULTS

There were significantly differences on IC_A and NIC_A among three pathological grades (IC_A, P = 0.001; NIC_A, P = 0.002). For differentiating moderately and poorly differentiated from well-differentiated LHSCC using IC_A and NIC_A, the areas under curve (AUCs) were 0.753 and 0.726, respectively. High T stage (T3/4) LHSCC showed significantly higher IC_A (P = 0.012) and NIC_A (P = 0.005) than low T stage (T1/2) LHSCC. The AUCs of the IC_A and NIC_A were 0.674 and 0.703, respectively, in discriminating high from low T stage LHSCC. Lymph node metastasis (LNM)-positive (N1/2/3) LHSCC showed significantly higher IC_A (P = 0.008) and NIC_A (P = 0.003) than LNM-negative (N0) LHSCC. For discriminating the LNM-positive from the LNM-negative group using IC_A and NIC_A, the AUCs were 0.697 and 0.744, respectively.

CONCLUSION

IC_A and NIC_A might be helpful in assessing histopathological prognostic factors in patients with LHSCC.

Dual-energy CT-based radiomics nomogram in predicting histological differentiation of head and neck squamous carcinoma: a multicenter study

PURPOSE

To develop and validate a dual-energy CT (DECT)-based radiomics nomogram from multicenter trials for predicting the histological differentiation of head and neck squamous cell carcinoma (HNSCC).

METHODS

A total of 178 patients (112 in the training and 66 in the validation cohorts) from eight institutions with histologically proven HNSCCs were included in this retrospective study. Radiomics-signature models were constructed from features extracted from virtual monoenergetic images (VMI) and iodine-based material decomposition images (IMDI), reconstructed from venous-phase DECT images. Clinical factors were also assessed to build a clinical model. Multivariate logistic regression analysis was used to develop a nomogram combining the radiomics signature models and clinical model for predicting poorly differentiated HNSCC and moderately well-differentiated HNSCC. The predictive performance of the clinical model, radiomics signature models, and nomogram was compared. The calibration degree of the nomogram was also assessed.

RESULTS

The tumor location, VMI-signature, and IMDI-signature were associated with the degree of HNSCC differentiation, and areas under the ROC curves (AUCs) were 0.729, 0.890, and 0.833 in the training cohort and 0.627, 0.859, and 0.843 in the validation cohort, respectively. The nomogram incorporating tumor location and two radiomics-signature models yielded the best performance in training (AUC = 0.987) and validation (AUC = 0.968) cohorts with a good calibration degree.

CONCLUSION

The nomogram that integrated the DECT-based radiomics-signature models and tumor location showed good performance in predicting histological differentiation degree of HNSCC, providing a novel combination for predicting HNSCC differentiation.

Advanced CT and MR Imaging of the Posttreatment Head and Neck

Advances in MR and computed tomography (CT) techniques have resulted in greater fidelity in the assessment of treatment response and residual tumor on one hand and the assessment of recurrent head and neck malignancies on the other hand. The advances in MR techniques primarily are related to diffusion and perfusion imaging which rely on the intrinsic architecture of the tissues and organ systems. The techniques exploit the density of the cellular architecture; and the vascularity of benign and malignant lesions which in turn affect the changes in the passage of contrast through the vascular bed. Dual-energy CT and CT perfusion are the major advances in CT techniques that have found significant applications in the assessment of treatment response and tumor recurrence.

Dual-energy computed tomography: Survey results on current uses and barriers to further implementation

OBJECTIVE

To gauge the current availability of dual-energy computed tomography (DECT) scanners in the UK, establish available technologies, look broadly at current clinical uses in adults and paediatrics, and identify barriers to implementation and potential ways to increase use.

METHODS

A survey was distributed amongst 10 radiology departments and shared on two national professional co-operation mail bases; the survey ran from 20th July to 9th December 2020. It explored current DECT utilisation in adults and paediatrics as well as barriers to use and suggestions to overcome those barriers.

RESULTS

The survey demonstrated DECT availability on 39 (40%) of the 98 CT scanners, but there was limited clinical use in adults and paediatrics. Eighteen (72%) of the 25 respondents had access to at least one DECT scanner, with 14 (56%) having adult DECT protocols in clinical use; <10% head examinations and <50% for other anatomical areas. Only two (8%) respondents had DECT paediatric protocols in clinical use; <10% examinations for all anatomical areas.The main barriers to implementation identified were lack of experience with DECT (8 (44%) users (adult) and 10 (56%) users (paediatric)) and no clinical protocols available (6 (33%) users (adult and paediatric)).Understanding DECT benefits and establishing suitable protocols were the most popular suggestions for increased implementation (10 (40%) of 25 respondents).

CONCLUSION

DECT scanners are available, but clinical use is limited for both adults and paediatrics. The main barriers identified were lack of experience with DECT and the availability of suitable protocols. Further work identified to help implementation included better education on the benefits of DECT, provision of clinical protocols and ensuring a multidisciplinary approach.

ADVANCES IN KNOWLEDGE

Barriers to implementation of clinical DECT protocols were identified, together with potential solutions to overcome these and enable further implementation.

Multiparametric dual-energy CT to differentiate stage T1 nasopharyngeal carcinoma from benign hyperplasia

Background

Stage T1 nasopharyngeal carcinoma (NPC_T1) and benign hyperplasia (BH) are 2 common causes of nasopharyngeal mucosa/submucosa thickening without specific clinical symptoms. The treatment management of these 2 entities is significantly different. Reliable differentiation between the 2 entities is critical for the treatment decision and prognosis of patients. Therefore, our study aims to explore the optimal energy level of noise-optimized virtual monoenergetic images [VMI (+)] derived from dual-energy computed tomography (DECT) to display NPC_T1 and BH and to explore the clinical value of DECT for differentiating these 2 diseases.

Methods

A total of 91 patients (44 NPC_T1, 47 BH) were enrolled. The demarcation of the lesion margins and overall image quality, noise, contrast-to-noise ratio (CNR), and signal-to-noise ratio (SNR) were evaluated for 40-80 kiloelectron volts (keV) VMIs (+) and polyenergetic images in the contrast-enhanced phase. Image features were assessed in the contrast-enhanced images with optimal visualization of NPC_T1 and BH. The demarcation of NPC_T1 and BH in iodine-water maps was also assessed. The contrast-enhanced images were used to calculate the slope of the spectral Hounsfield unit curve (λ_HU) and normalized iodine concentration (NIC). The nonenhanced phase images were used to calculate the normalized effective atomic number (NZ_eff). The attenuation values on 40-80 keV VMIs (+) in the contrast-enhanced phase were recorded. The diagnostic performance was assessed using receiver operating characteristic (ROC) curve analysis.

Results

The 40 keV VMI (+) in the enhanced phase yielded higher demarcation of the lesion margins scores, overall image quality scores, noise, SNR, and CNR values than 50-80 keV VMIs (+) and polyenergetic images. NPC_T1 yielded higher attenuation values on VMI (+) at 40 keV (A₄₀), NIC, λ_HU, and NZ_eff values than BH. The multivariate logistic regression model combining image features (tumor symmetry) with quantitative parameters (A₄₀, NIC, λ_HU, and NZ_eff) yielded the best performance for differentiating the 2 diseases (AUC: 0.963, sensitivity: 89.4%, specificity: 93.2%).

Conclusions

The combination of DECT-derived image features and quantitative parameters contributed to the differentiation between NPC_T1 and BH.

Dual-Layer Spectral CT Imaging of Upper Aerodigestive Tract Cancer: Analysis of Spectral Imaging Parameters and Impact on Tumor Staging

BACKGROUND AND PURPOSE

Dual-layer spectral CT is a novel technology that utilized conventional single-tube CT acquisition with a dual-layer detector for the separation of high and low-energy photons to create spectral data for material decomposition. We evaluated the spectral parameters of iodine density and Z-effective values in primary head and neck squamous cell carcinoma and determined its impact on local tumor staging.

MATERIALS AND METHODS

Twenty-one patients with primary head and neck squamous cell carcinoma and 15 healthy controls were retrospectively evaluated. Iodine density (milligram/milliliter) and Z-effective values were compared quantitatively between head and neck squamous cell carcinoma and normal neck mucosa. The receiver operating characteristic area under the curve determined the diagnostic performance of the spectral data for local staging. We compared conventional CT images without and with iodine density and Z-effective images to determine its impact on local tumor staging.

RESULTS

Primary head and neck squamous cell carcinoma showed higher mean iodine density (2.01 [SD, 0.26] mg/mL, P < .001) and Z-effective values (8.21 [SD, 0.36], P < .001). A high interobserver correlation was demonstrated for ROI measurements for both the control group (iodine density, κ = 0.71, and Z-effective values, κ = 0.78) and head and neck squamous cell carcinoma (iodine density, κ = 0.84, and Z-effective values, κ = 0.75) group. The area under the curve for iodine density and Z-effective values was 0.98 and 0.93, respectively. Optimal thresholds were identified as 1.58 mg/mL (95% CI, 1.45-1.71 mg/mL; P < .001; sensitivity = 1.0; specificity = .0.93) for iodine density and 8.08 (95% CI, 7.96-8.19; P < .001; sensitivity = 0.86; specificity = 0.93) for Z-effective values. Conventional CT with the addition of dual-layer spectral data (iodine density and Z-effective values) improved the accuracy of local tumor staging in 3 of 21 patients (14%) with head and neck squamous cell carcinoma compared with the criterion standard surgical staging/histopathology.

CONCLUSIONS

Dual-layer spectral iodine density and Z-effective values provided increased quantitative and qualitative differentiation between upper aerodigestive head and neck squamous cell carcinoma and normal mucosa. Increased tissue differentiation improved the local tumor staging accuracy.

Dual-energy CT in differentiating benign sinonasal lesions from malignant ones: comparison with simulated single-energy CT, conventional MRI, and DWI

OBJECTIVES

To explore the value of dual-energy CT (DECT) for differentiating benign sinonasal lesions from malignant ones, and to compare this finding with simulated single-energy CT (SECT), conventional MRI (cMRI), and diffusion-weighted imaging (DWI).

METHODS

Patients with sinonasal lesions (38 benign and 34 malignant) who were confirmed by histopathology underwent DECT, cMRI, and DWI. DECT-derived parameters (iodine concentration (IC), effective atomic number (Eff-Z), 40-180 keV (20-keV interval), virtual non-enhancement (VNC), slope (k), and linear-mixed 0.3 (Mix-0.3)), DECT morphological features, cMRI characteristics, and ADC value of benign and malignant tumors were compared using t test or chi-square test. Receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance, and the area under the ROC curve (AUC) was compared using the Z test to select the optimal diagnostic approach.

RESULTS

Significantly higher DECT-derived single parameters (IC, Eff-Z, 40 keV, 60 keV, 80 keV, slope (k), Mix-0.3) were found in malignant lesions than those of benign sinonasal lesions (all p < 0.004, Bonferroni correction). Combined quantitative parameters (IC, Eff-Z, 40 keV, 60 keV, 80 keV, slope (k)) can improve the diagnostic efficiency for discriminating these two entities. Combination of DECT quantitative parameters and morphological features can further improve the overall diagnostic performance, with AUC, sensitivity, specificity, and accuracy of 0.935, 96.67%, 90.00%, and 93.52%. Moreover, the AUC of DECT was higher than those of Mix-0.3 (simulated SECT), cMRI, DWI, and cMRI+DWI.

CONCLUSIONS

Compared with simulated SECT, cMRI, and DWI, DECT appears to be a more accurate imaging technique for differentiating benign from malignant sinonasal lesions.

KEY POINTS

• DE can differentiate benign sinonasal lesions from malignant ones based on DECT-derived qualitative parameters. • DECT appears to be more accurate in the diagnosis of sinonasal lesions when compared with simulated SECT, cMRI, and DWI.

Imaging in head and neck cancers: Update for non-radiologist

Head and neck cancer (HNC) is the fifth most frequent cancer worldwide and associated with significant morbidity. Along with clinical examination and endoscopic evaluation, imaging plays an important role in pre- and posttherapeutic evaluation of patients with HNC. Cross-sectional Imaging techniques such as computed tomography (CT), magnetic resonance imaging (MRI) and positron emission tomography / computed tomography (PET/CT) are routinely used in the assessment of these patients. This review provides an overview of the various cross-sectional imaging modalities used in the evaluation of HNC and will give a short summary of the latest imaging technologies regarding head and neck cancer diagnosis.

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

PURPOSE

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

[Radiotherapy for patients with early-stage glottic squamous cell carcinoma of the larynx: Interest of hypofractionation?]

Hypofractionated radiotherapy of early-stage squamous cell carcinoma of the glottic larynx is a promising treatment option. This can be divided into radiotherapy with moderate hypofractionation (up to 2.5Gy per fraction), more intense hypofractionation (between 2.5 and 4.5Gy per fraction) and stereotactic radiotherapy (above 4.5Gy per fraction). Most studies evaluating moderate hypofractionation show a local control rate between 85 and 95%. Acute laryngeal toxicity is superior to conventional treatment, but only for grades 1 and 2, with no significant difference reported for severe toxicity. Stereotactic radiotherapy in this pathology is also an emerging entity, but some authors have reported significant toxicity. There are currently no standardized guidelines for treatment and management regimen. We conducted a systemic review of published prospective and retrospective trials to evaluate efficacy, toxicity, and discuss future directions.

A New Outlook on the Ability to Accumulate an Iodine Contrast Agent in Solid Lung Tumors Based on Virtual Monochromatic Images in Dual Energy Computed Tomography (DECT): Analysis in Two Phases of Contrast Enhancement

For some time, dual energy computed tomography (DECT) has been an established method used in a vast array of clinical applications, including lung nodule assessment. The aim of this study was to analyze (using monochromatic DECT images) how the X-ray absorption of solitary pulmonary nodules (SPNs) depends on the iodine contrast agent and when X-ray absorption is no longer dependent on the accumulated contrast agent. Sixty-six patients with diagnosed solid lung tumors underwent DECT scans in the late arterial phase (AP) and venous phase (VP) between January 2017 and June 2018. Statistically significant correlations (p ≤ 0.001) of the iodine contrast concentration were found in the energy range of 40–90 keV in the AP phase and in the range of 40–80 keV in the VP phase. The strongest correlation was found between the concentrations of the contrast agent and the scanning energy of 40 keV. At the higher scanning energy, no significant correlations were found. We concluded that it is most useful to evaluate lung lesions in DECT virtual monochromatic images (VMIs) in the energy range of 40–80 keV. We recommend assessing SPNs in only one phase of contrast enhancement to reduce the absorbed radiation dose.

Preoperative Prediction of Cervical Nodal Metastasis in Papillary Thyroid Carcinoma: Value of Quantitative Dual-Energy CT Parameters and Qualitative Morphologic Features

OBJECTIVE. The purpose of our study was to assess the value of combining quantitative dual-energy CT (DECT) parameters with qualitative morphologic parameters for the preoperative prediction of cervical nodal metastasis from papillary thyroid carcinoma (PTC). MATERIALS AND METHODS. Thirty-five patients with pathologically proven PTC underwent single-phase contrast-enhanced DECT before thyroidectomy and cervical lymphadenectomy. Analyses of quantitative DECT parameters and qualitative morphologic features of metastatic and benign lymph nodes (LNs) were independently performed. The diagnostic performances of using only quantitative parameters, only morphologic features, and their combination for predicting cervical nodal metastasis were statistically calculated with ROC curves and logistic regression models. RESULTS. A total of 206 LNs, 80 metastatic and 126 benign, were included. The best single performer in DECT was the normalized iodine concentration in the venous phase, which had low sensitivity (62.5%) but high specificity (85.7%), for diagnosing metastatic cervical LNs. On the other hand, the best single performer in qualitative morphologic parameters was using the criterion of shortest diameter of greater than 5 mm, which had low specificity (69.8%) but high sensitivity (86.3%). Combining these two parameters improved the AUC, sensitivity, and specificity to 0.846, 86.3%, and 72.2%, respectively. The combination of multiple quantitative DECT parameters and all morphologic data further improved AUC, sensitivity, and specificity to 0.878, 87.5%, and 73.8%, respectively, which was significant compared with the use of any single parameter. CONCLUSION. The combination of quantitative DECT parameters with morphologic data improves performance in the preoperative diagnosis of metastatic cervical LNs in patients with PTC.

Dual-energy CT for differentiating early glottic squamous cell carcinoma from chronic inflammation and leucoplakia of vocal cord: comparison with simulated conventional 120 kVp CT

AIM

To evaluate the value of dual-energy (DE) computed tomography (CT) in discriminating early glottic squamous cell carcinoma (eGSCC) from chronic inflammation and leucoplakia of the vocal cord, and to compare the diagnostic efficiency of DECT with that of simulated conventional 120 kVp CT.

MATERIALS AND METHODS

Seventy patients with glottic lesions confirmed by histopathology (38 cases with eGSCC, 11 cases with chronic inflammation, 21 cases with leucoplakia) were enrolled in this prospective study. The DECT-derived parameters were measured and compared using independent sample t-test. Receiver operating characteristic (ROC) curve was performed to evaluate the diagnostic performance, and comparison of the area under the ROC curve (AUC) was made using the Z test to further select the best diagnostic parameters.

RESULTS

Significantly higher iodine concentration (IC), normalised IC (NIC), effective atomic number (Z_eff), 40-100 keV (20 keV-interval), slope(k), and Mix-0.3 values were found in eGSCC than those in chronic inflammation, leucoplakia, and inflammation + leucoplakia (all p<0.05). Compared with attenuation measurement of simulated conventional 120 kVp CT, the NIC, 60 keV values derived from DECT showed significantly higher AUC in discriminating these glottic lesions (p<0.05).

CONCLUSIONS

DECT is more accurate for differentiating eGSCC from chronic inflammation and leucoplakia when compared with simulated conventional 120 kVp CT.

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

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

A Review of the Applications of Dual-Energy CT in Acute Neuroimaging

Dual-energy computed tomography (CT) is a promising tool with increasing availability and multiple emerging and established clinical applications in neuroradiology. With its ability to allow characterization of materials based on their differential attenuation when imaged at two different energy levels, dual-energy CT can help identify the composition of brain, neck, and spinal components. Virtual monoenergetic imaging allows a range of simulated single energy-level reconstructions to be created with postprocessing. Low-energy reconstructions can aid identification of edema, ischemia, and subtle lesions due to increased soft tissue contrast as well as increasing contrast-to-noise ratios on angiographic imaging. Higher energy reconstructions can reduce image artifact from dental amalgam, aneurysm clips and coils, spinal hardware, dense contrast, and dense bones. Differentiating iodine from hemorrhage may help guide management of patients after thrombectomy and aid diagnosis of enhancing tumors within parenchymal hemorrhages. Iodine quantification may predict hematoma expansion in aneurysmal bleeds and outcomes in traumatic brain injury. Calcium and bone subtraction can be used to distinguish hemorrhage from brain parenchymal mineralization as well as improving visualization of extra-axial lesions and vessels adjacent to dense plaque or skull. This article reviews the basics of dual-energy CT and highlights many of its clinical applications in the evaluation of acute neurological presentations.