Imaging Modalities for Head and Neck Cancer: Present and Future

Several imaging modalities are utilized in the diagnosis, treatment, and surveillance of head and neck cancer. First-line imaging remains computed tomography (CT); however, MRI, PET with CT (PET/CT), and ultrasound are often used. In the last decade, several new imaging modalities have been developed that have the potential to improve early detection, modify treatment, decrease treatment morbidity, and augment surveillance. Among these, molecular imaging, lymph node mapping, and adjustments to endoscopic techniques are promising. The present review focuses on existing imaging, novel techniques, and the recent changes to imaging practices within the field.

Imaging findings of granular cell tumours of the head and neck

AIM

To review the imaging characteristics of granular cell tumours in the head and neck and assess their associations with pathological findings.

MATERIALS AND METHODS

Eleven patients (10 [91%] women, mean age 43 years) with histopathologically confirmed granular cell tumours were included in this study. Preoperative imaging studies were performed, including computed tomography (CT), magnetic resonance imaging (MRI), or ultrasound. The location of the tumours, their imaging features, and histopathological findings were analysed.

RESULTS

Among the 11 granular cell tumours, four (36%), three (27%), and two (18%) tumours were found in the submucosal layer, subcutaneous layer, and intramuscular area, respectively. On CT, all tumours exhibited homogeneous iso-attenuating enhancement compared with adjacent muscle, and nine out of the 11 tumours (81%) demonstrated well-defined margins. On T2-weighted imaging (T2WI), four out of five tumours (80%) demonstrated iso-signal intensity compared with adjacent muscles, and four tumours (80%) exhibited homogeneous signal intensity. The apparent diffusion coefficient (ADC) values ranged from 0.68-0.81 × 10-3 mm2/s. Histopathological examination revealed densely packed tumour cells with variable amounts of fibrous stroma.

CONCLUSION

Granular cell tumours were characterised by well-defined and iso-signals on T2WI and low mean ADC values, and were predominantly located in the submucosal, subcutaneous, or intramuscular areas in middle-aged women. The characteristic locations, demographic characteristics, and imaging findings can help to differentiate granular cell tumours from other soft-tissue tumours in the head and neck.

CT texture analysis of tonsil cancer: Discrimination from normal palatine tonsils

The purposes of the study were to determine whether there are differences in texture analysis parameters between tonsil cancers and normal tonsils, and to correlate texture analysis with 18F-FDG PET/CT to investigate the relationship between texture analysis and metabolic parameters. Sixty-four patients with squamous cell carcinoma of the palatine tonsil were included. A ROI was drawn, including all slices, to involve the entire tumor. The contralateral normal tonsil was used for comparison with the tumors. Texture analysis parameters, mean, standard deviation (SD), entropy, mean positive pixels, skewness, and kurtosis were obtained using commercially available software. Parameters were compared between the tumor and the normal palatine tonsils. Comparisons were also performed among early tonsil cancer, advanced tonsil cancer, and normal tonsils. An ROC curve analysis was performed to assess discrimination of tumor from normal tonsils. Correlation between texture analysis and 18F-FDG PET/CT was performed. Compared to normal tonsils, the tumors showed a significantly lower mean, higher SD, higher entropy, lower skewness, and higher kurtosis on most filters (p<0.001). On comparisons among normal tonsils, early cancers, and advanced tonsil cancers, SD and entropy showed significantly higher values on all filters (p<0.001) between early cancers and normal tonsils. The AUC from the ROC analysis was 0.91, obtained from the entropy. A mild correlation was shown between texture parameters and metabolic parameters. The texture analysis parameters, especially entropy, showed significant differences in contrast-enhanced CT results between tumor and normal tonsils, and between early tonsil cancers and normal tonsils. Texture analysis can be useful as an adjunctive tool for the diagnosis of tonsil cancers.

Histogram analysis of arterial spin labeling perfusion data to determine the human papillomavirus status of oropharyngeal squamous cell carcinomas

PURPOSE

To evaluate the correlation between histogram parameters derived from pseudo-continuous arterial spin labeling (PCASL) and human papillomavirus (HPV) status in patients with oropharyngeal squamous cell carcinoma (OPSCC).

METHODS

This study included a total of 58 patients (HPV-positive: n = 45; -negative: n = 13) from a prospective cohort of consecutive patients aged ≥ 18 years, who were newly diagnosed with oropharyngeal squamous cell carcinoma. All patients were required to have undergone pre-treatment MRI with PCASL to measure regional perfusion. The region of interest was drawn by two radiologists, encompassing the entire tumor volume on all corresponding slices. Differences in the histogram parameters derived from tumor blood flow (TBF) in ASL were assessed for HPV-positive and -negative patients. Receiver operating characteristic curve analysis was performed to determine the best differentiating parameters, and a leave-one-out cross-validation was used.

RESULTS

Patients with HPV-positive OPSCC showed a significantly lower overall standard deviation and 95th percentile value of tumor blood flow (P < .007). The standard deviation of TBF was the single best predictive parameter. Leave-one-out cross-validation tests revealed that the area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity were 0.745, 75.9%, 75.6%, and 76.9%, respectively.

CONCLUSION

PCASL revealed differences in perfusion parameters according to HPV status in patients with OPSCC, reflecting their distinct histopathology.

Technical feasibility of radiomics signature analyses for improving detection of occult tonsillar cancer

Diagnosis of occult palatine tonsil squamous cell carcinoma (SCC) using conventional magnetic resonance imaging (MRI) is difficult in patients with cervical nodal metastasis from an unknown primary site at presentation. We aimed to establish a radiomics approach based on MRI features extracted from the volume of interest in these patients. An Elastic Net model was developed to differentiate between normal palatine tonsils and occult palatine tonsil SCC. The diagnostic performances of the model with radiomics features extracted from T1-weighted image (WI), T2WI, contrast-enhanced T1WI, and an apparent diffusion coefficient (ADC) map had area under the receiver operating characteristic (AUROC) curve values of 0.831, 0.840, 0.781, and 0.807, respectively, for differential diagnosis. The model with features from the ADC alone showed the highest sensitivity of 90.0%, while the model with features from T1WI + T2WI + contrast-enhanced T1WI showed the highest AUROC of 0.853. The added sensitivity of the radiomics feature analysis were 34.6% over that of conventional MRI to detect occult palatine tonsil SCC. Therefore, we concluded that adding radiomics feature analysis to MRI may improve the detection sensitivity for occult palatine tonsil SCC in patients with a cervical nodal metastasis from cancer of an unknown primary site.

MRI Predictors of Malignant Transformation in Patients with Inverted Papilloma: A Decision Tree Analysis Using Conventional Imaging Features and Histogram Analysis of Apparent Diffusion Coefficients

OBJECTIVE

Preoperative differentiation between inverted papilloma (IP) and its malignant transformation to squamous cell carcinoma (IP-SCC) is critical for patient management. We aimed to determine the diagnostic accuracy of conventional imaging features and histogram parameters obtained from whole tumor apparent diffusion coefficient (ADC) values to predict IP-SCC in patients with IP, using decision tree analysis.

MATERIALS AND METHODS

In this retrospective study, we analyzed data generated from the records of 180 consecutive patients with histopathologically diagnosed IP or IP-SCC who underwent head and neck magnetic resonance imaging, including diffusion-weighted imaging and 62 patients were included in the study. To obtain whole tumor ADC values, the region of interest was placed to cover the entire volume of the tumor. Classification and regression tree analyses were performed to determine the most significant predictors of IP-SCC among multiple covariates. The final tree was selected by cross-validation pruning based on minimal error.

RESULTS

Of 62 patients with IP, 21 (34%) had IP-SCC. The decision tree analysis revealed that the loss of convoluted cerebriform pattern and the 20th percentile cutoff of ADC were the most significant predictors of IP-SCC. With these decision trees, the sensitivity, specificity, accuracy, and C-statistics were 86% (18 out of 21; 95% confidence interval [CI], 65-95%), 100% (41 out of 41; 95% CI, 91-100%), 95% (59 out of 61; 95% CI, 87-98%), and 0.966 (95% CI, 0.912-1.000), respectively.

CONCLUSION

Decision tree analysis using conventional imaging features and histogram analysis of whole volume ADC could predict IP-SCC in patients with IP with high diagnostic accuracy.

Differentiation of follicular carcinomas from adenomas using histogram obtained from diffusion-weighted MRI

AIM

To evaluate the role of histogram analysis of apparent diffusion coefficient (ADC) maps from diffusion-weighted imaging (DWI) in the differentiation of follicular thyroid carcinoma (FTC) from follicular adenoma (FA) in nodules indeterminate on ultrasound-guided core needle biopsy (USCNB).

MATERIALS AND METHODS

This study was performed with institutional review board approval. Seventeen patients who were planned to undergo diagnostic lobectomy for an indeterminate thyroid nodule (atypical of unknown significance/follicular lesion of undetermined significance [AUS/FLUS] or suspicious for follicular neoplasm/follicular neoplasm [SFN]) on USCNB were enrolled prospectively. All patients underwent DWI on the day before surgery. Histogram parameters were derived from ADC values obtained from the whole extent of the tumours. The parameters were compared with the final diagnosis based on histopathological examination after surgery. The accuracy of the parameters in differentiating FTC from FA was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

Twelve patients were confirmed as having FA and five patients as having FTC. Histogram parameters including the 10^th (ADC₁₀), 25^th (ADC₂₅), and 50^th (ADC₅₀) percentiles of the ADC values were significantly lower in FA than in FTC (p < 0.05, all). ROC curve analysis revealed that ADC₂₅ resulted in the highest AUC (0.867; confidence interval, 0.616-0.980), with a cut-off value of 0.352×10^-3 mm²/s.

CONCLUSION

Histogram parameters from ADC maps could differentiate FTC from FA effectively in indeterminate nodules on USCNB, with ADC₂₅ being the most promising parameter.

Feasibility study for evaluating lumbar intervertebral disc degeneration using histogram analysis of T2* values

PURPOSE

To evaluate the feasibility of histogram analysis of T2* value for the detection and grading of degenerative lumbar intervertebral discs (IVDs) and for the characterization of microstructural heterogeneity of discs.

METHODS

Two hundred fourteen lumbar IVDs of 44 subjects with chronic low back pain were examined using sagittal T2WI and axial T2* mapping. All IVDs were classified according to the Pfirrmann grade on T2WI. The correlations between histogram-derived parameters based on T2* values (T2*-HPs) of IVDs and Pfirrmann grade as well as between "red zone ratio" (area of "red zone" on T2* color maps over cross-sectional area of corresponding IVDs) and Pfirrmann grade were calculated.

RESULTS

The agreement for Pfirrmann grade of IVDs was excellent (κ = 0.808, P < 0.001). The consistency of the measured T2*-HPs was excellent, with ICCs ranging from 0.828-0.960. Each histogram-derived parameter had a statistically significant relationship with Pfirrmann grade (P < 0.001). The bright "red zone" on T2* color maps of IVDs displayed as a separated peak relative to the rest of voxels in histograms. The mean area ratio of "red zone" over the corresponding IVD was 9.234% ± 6.680 and ranged from 0.517% to 30.598%. The "red zone ratio" was highly related to Pfirrmann grade (r = - 0.732, P < 0.001).

CONCLUSION

Histogram analysis of T2* value is an effective tool for the detection and grading of degenerative IVDs. Identification of the "red zone" may provide new breakthroughs in the study of disc degeneration initiation and generate new hypotheses in anatomical and histological studies of IVDs.

CT and MRI Findings of Glomangiopericytoma in the Head and Neck: Case Series Study and Systematic Review

Glomangiopericytoma is a rare sinonasal mesenchymal tumor of borderline or low malignant potential. We reviewed the CT and MR imaging findings of head and neck glomangiopericytoma via a retrospective case series study and systematic review. Our study revealed that glomangiopericytoma is a well-defined lobulated avidly enhancing soft-tissue mass with erosive bony remodeling that is most commonly found in the sinonasal cavity. Typically, it is hyperintense on T2-weighted images with vascular signal voids, has a high mean ADC value, and a wash-in and washout pattern on dynamic contrast-enhanced MR imaging. Although the CT findings are nonspecific, typical MR imaging findings, including those on the ADC map and dynamic contrast-enhanced MR imaging, may be helpful for differentiating glomangiopericytomas from other hypervascular tumors in the head and neck.

Texture Analysis of Multi-Shot Echo-planar Diffusion-Weighted Imaging in Head and Neck Squamous Cell Carcinoma: The Diagnostic Value for Nodal Metastasis

Accurate assessment of nodal metastasis in head and neck squamous cell carcinoma (SCC) is important, and diffusion-weighted imaging (DWI) has emerged as a potential technique in differentiating benign from malignant lymph nodes (LNs). This study aims to evaluate the diagnostic performance of texture analysis using apparent diffusion coefficient (ADC) data of multi-shot echo-planar imaging-based DWI (msEPI-DWI) in predicting metastatic LNs of head and neck SCC. 36 patients with pathologically proven head and neck SCC were included in this study. A total of 204 MRI-detected LNs, including 176 subcentimeter-sized LNs, were assigned to metastatic or benign groups. Texture features of LNs were compared using independent t-test. Hierarchical cluster analysis was performed to exclude redundant features. Multivariate logistic regression and receiver operating characteristic analysis were performed to assess the diagnostic performance. The discriminative texture features for predicting metastatic LNs were complexity, energy and roundness. Areas under the curves (AUCs) for diagnosing metastasis in all/subcentimeter-sized LNs were 0.829/0.767 using complexity, 0.699/0.685 using energy and 0.671/0.638 using roundness, respectively. The combination of three features resulted in higher AUC values of 0.836/0.781. In conclusion, texture analysis of ADC data using msEPI-DWI could be a useful tool for nodal staging in head and neck SCC.

Prognostic role of diffusion weighted and dynamic contrast-enhanced MRI in loco-regionally advanced head and neck cancer treated with concomitant chemoradiotherapy

Background In the study, the value of pre-treatment dynamic contrast-enhanced (DCE) and diffusion weighted (DW) MRI-derived parameters as well as their changes early during treatment was evaluated for predicting disease-free survival (DFS) and overall survival (OS) in patients with locoregionally advanced head and neck squamous carcinoma (HNSCC) treated with concomitant chemoradiotherapy (cCRT) with cisplatin. Patients and methods MRI scans were performed in 20 patients with locoregionally advanced HNSCC at baseline and after 10 Grays (Gy) of cCRT. Tumour apparent diffusion coefficient (ADC) and DCE parameters (volume transfer constant [Ktrans], extracellular extravascular volume fraction [ve], and plasma volume fraction [Vp]) were measured. Relative changes in parameters from baseline to 10 Gy were calculated. Univariate and multivariate Cox regression analysis were conducted. Receiver operating characteristic (ROC) curve analysis was employed to identify parameters with the best diagnostic performance. Results None of the parameters was identified to predict for DFS. On univariate analysis of OS, lower pre-treatment ADC (p = 0.012), higher pre-treatment Ktrans (p = 0.026), and higher reduction in Ktrans (p = 0.014) from baseline to 10 Gy were identified as significant predictors. Multivariate analysis identified only higher pre-treatment Ktrans (p = 0.026; 95% CI: 0.000-0.132) as an independent predictor of OS. At ROC curve analysis, pre-treatment Ktrans yielded an excellent diagnostic accuracy (area under curve [AUC] = 0.95, sensitivity 93.3%; specificity 80 %). Conclusions In our group of HNSCC patients treated with cisplatin-based cCRT, pre-treatment Ktrans was found to be a good predictor of OS.

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.

Use of Diffusion-Weighted Imaging and 18F-Fluorodeoxyglucose Positron Emission Tomography Combined With Computed Tomography in the Response Assessment for (Chemo)radiotherapy in Head and Neck Squamous Cell Carcinoma

AIMS

Our purpose was to assess the diagnostic accuracy and prognostic value of diffusion-weighted imaging (DWI) and ¹⁸F-fluorodeoxyglucose positron emission tomography combined with computed tomography (¹⁸F-FDG-PET/CT) carried out 3-6 months after (chemo)radiotherapy in head and neck squamous cell carcinoma.

MATERIALS AND METHODS

For this retrospective cohort study we included 82 patients with advanced-stage head and neck squamous cell carcinoma treated between 2012 and 2015. Primary tumours and lymph nodes were assessed separately. DWI was analysed qualitatively and quantitatively. ¹⁸F-FDG-PET/CT was evaluated using the Hopkins criteria. Dichotomous qualitative analysis was carried out for both modalities. Cox regression analysis was used for univariate analysis of recurrence-free survival (RFS). Significant univariate parameters were included in multivariate analysis.

RESULTS

In 12 patients, locoregional recurrence occurred. With all imaging strategies, either single-modality or multi-modality, a high negative predictive value (NPV) was achieved (94.3-100%). In response evaluation of the primary site, the preferred strategy is ¹⁸F-FDG-PET/CT only, which resulted in a sensitivity of 85.7%, specificity of 86.5%, positive predictive value (PPV) of 37.5% and NPV of 98.5%. For response evaluation of the neck, the best results were obtained with a sequential approach only including the second modality in positive reads of the first modality. It did not matter which modality was assessed first. This strategy for lymph node assessment resulted in a sensitivity, specificity, PPV and NPV of 83.3%, 95.6%, 62.5%, and 98.5%, respectively. After correction for received treatment and human papillomavirus status, primary tumour (P = 0.009) or lymph node (P < 0.001) Hopkins score ≥4 on ¹⁸F-FDG-PET/CT remained significant predictors of RFS.

CONCLUSION

For response evaluation of the primary tumour ¹⁸F-FDG-PET/CT only is the preferred strategy, whereas for the neck a sequential approach including both DWI and ¹⁸F-FDG-PET/CT resulted in the best diagnostic accuracy for follow-up after (chemo)radiotherapy. Qualitative analysis of ¹⁸F-FDG-PET/CT is a stronger predictor of RFS than DWI analysis.

Diagnostic value of diffusion-weighted imaging and 18F-FDG-PET/CT for the detection of unknown primary head and neck cancer in patients presenting with cervical metastasis

BACKGROUND AND PURPOSE

Head and neck squamous cell carcinoma (HNSCC) may present with cervical metastases without an apparent primary tumor. Detecting the primary tumor results in more targeted treatment. Acquisition of DWI is improving with less artifacts and image distortion. We assessed the diagnostic value of DWI and ¹⁸F-FDG-PET/CT for detecting primary tumors in patients presenting with nodal metastasis of an unknown primary HNSCC.

MATERIALS AND METHODS

For this retrospective study we included 31 patients (male/female ratio = 23/8, median age = 66 years, age range = 40-80 years) who presented with a pathologically proven cervical nodal metastasis from HNSCC without overt primary tumor location between January 2013 and November 2016 and underwent both DWI and ¹⁸F-FDG-PET/CT. Both modalities were assessed qualitatively and quantitatively. With ROC analysis we determined the optimal cut-off for imaging parameters in separating occult malignancy from benign tissue.

RESULTS

Qualitative analysis of MRI including DWI resulted in a sensitivity of 81.3% (95%CI) = 53.7-95.0) and specificity of 73.3% (95%CI = 44.8-91.1). With qualitative scoring of ¹⁸F-FDG-PET/CT a sensitivity and specificity of 93.8% (95%CI = 67.8-99.7) and 73.3% (95%CI = 44.8-91.1) were found. With quantitative analysis sensitivity and specificity of SUV_max were 81.3% (95%CI = 53.6-95.0) and 93.3% (95%CI = 66.0-99.7), respectively. Combining DWI and ¹⁸F-FDG-PET/CT resulted in a sensitivity of 93.8% (95%CI = 67.7-99.7%) and specificity of 60.0% (95%CI = 32.9-82.5%).

CONCLUSION

In this study on HNSCC patients presenting with clinically UP lesions the diagnostic accuracy of qualitative analysis with DWI and ¹⁸F-FDG-PET/CT and quantitative analysis of ¹⁸F-FDG-PET/CT using SUV_max were high. Adding DWI did not improve the accuracy of ¹⁸F-FDG-PET/CT.

Histogram analysis of apparent diffusion coefficient maps for the differentiation between lymphoma and metastatic lymph nodes of squamous cell carcinoma in head and neck region

Background To clarify the nature of cervical malignant lymphadenopathy is highly important for the diagnosis and differential diagnosis of head and neck tumors. Purpose To investigate the role of first-order apparent diffusion coefficient (ADC) histogram analysis for differentiating lymphoma from metastatic lymph nodes of squamous cell carcinoma (SCC) in the head and neck region. Material and Methods Diffusion-weighted imaging (DWI) data of 67 patients (lymphoma, n = 20; SCC, n = 47) with malignant lymphadenopathy were retrospectively analyzed. The SCC group was divided into nasopharyngeal SCC and non-nasopharyngeal SCC groups. The ADC histogram features (ADC₁₀, ADC₂₅, ADC_mean, ADC_median, ADC₇₅, ADC₉₀, skewness, and kurtosis) were derived and then compared by independent-samples t-test and one-way analysis of variance test, respectively. Receiver operating characteristic curve analyses were employed to investigate diagnostic performance of the significant parameters. Results Lymphoma showed significantly lower ADC_mean, ADC_median, ADC₇₅, and ADC₉₀ than SCC (all P < 0.05). Setting ADC₉₀ = 0.719 × 10^-3mm²/s as the threshold value, optimal diagnostic performance was achieved (area under the curve [AUC] = 0.719, sensitivity = 95.7%, specificity = 50.0%). Subgroup analyses showed no significant difference between lymphoma and NPC (all P > 0.05). Lymphoma showed significantly lower ADC₂₅, ADC_mean, ADC_median, ADC₇₅, and ADC₉₀ than non-nasopharyngeal SCC (all P < 0.05). Optimal diagnostic performance (AUC = 0.847, sensitivity = 86.7%, specificity = 80.0%) could be achieved when setting ADC₉₀ = 0.943 × 10^-3mm²/s as the threshold value. Conclusion Given its limitations, our study has shown that first-order ADC histogram analysis is capable of differentiating lymphoma from metastatic lymph nodes of SCC, especially those of non-nasopharyngeal SCC.

Volumetric analysis of intravoxel incoherent motion imaging for assessment of solitary pulmonary lesions

Background Differentiating between malignant and benign solitary pulmonary lesions (SPLs) is challenging. Purpose To determine diagnostic performance of intravoxel incoherent motion-based diffusion-weighted imaging (DW-IVIM) in distinguishing malignant from benign SPLs, using histogram analysis derived whole-tumor and single-section region of interest (ROI). Material and Methods This retrospective study received institutional review board approval. A total of 129 patients with diagnosed SPLs underwent DW-IVIM and apparent diffusion coefficient (ADC). ADC, slow diffusion coefficient (D), fast diffusion coefficient (D*), and perfusion fraction (f) were calculated separately by outlining whole-tumor and single-section ROI. Inter-observer reliability was assessed by inter-class correlation coefficient (ICC). ADC and DW-IVIM parameters were analyzed using independent-sample T-test. Receiver operating characteristic (ROC) analysis was constructed to determine diagnostic performance. Multiple logistic regression was performed to identify independent factors associated with malignant SPLs. Results There were 48 benign SPLs found in 35 patients and 94 patients with lung cancer (LC). ICC for whole-tumor ROI (range, 0.89-0.95) was higher than that for single-section ROI (range, 0.61-0.71). Mean ADC and D were significantly lower in the malignant group. ADC and D 10th showed significantly higher AUC values than did mean ADC and D. D showed significantly higher diagnostic accuracy in mean, 10th, and 25th percentiles than ADC values (all Ps < 0.05). D 10th was found to be an independent factor in discriminating LCs with an odds ratio of -1.217. Conclusion Volumetric analysis had higher reproducibility and diagnostic accuracy than did single-section. Further, compared to ADC, D value differentiated benign SPLs from LCs more accurately.

Quantitative Assessment of Heterogeneity in Bladder Tumor MRI Diffusivity: Can Response be Predicted Prior to Neoadjuvant Chemotherapy?

Background:

It is a critical unmet need to predict chemosensitivity in muscle-invasive bladder cancer patients who receive neoadjuvant chemotherapy (NAC). Quantification of tumor heterogeneity has been shown to be useful in the assessment of therapeutic response. Apparent diffusion coefficient (ADC) is derived from diffusion weighted MRI (DWI) to quantify the water diffusivity which characterizes micro-cellularity in tumor tissues.

Objective:

The aim of this study is to assess if a quantitative measurement of ADC heterogeneity in bladder tumors can be a predictor of therapeutic response to NAC.

Materials and Methods:

Twenty patients with pT2 bladder cancer have been included in this study. Patient MRI was performed on a 3T system with DWI prior to NAC. Regions of interest (ROIs) were placed over the whole tumor volume on ADC maps to acquire a data matrix of voxel-wise ADC values for each patient. We performed histogram analysis on each ADC data matrix to calculate uniformity (U) and entropy (E). These quantities were subsequently correlated with the patient’s response to chemotherapy. Statistical significance was found with P < 0.05.

Results:

Fifteen patients were categorized as responders, and five as non-responders. The data showed that tumors of responders were significantly higher in U (P = 0.01) and lower in E (P < 0.01) than non-responders. This finding indicates that resistant tumors were more heterogeneous in their spatial distribution of ADC values. While this difference in ADC heterogeneity was not always visually recognizable, it could be quantified by the data analytics.

Conclusions:

This study demonstrates that the quantitative readout of tumor heterogeneity in micro-cellularity is associated with the patient’s defined response to chemotherapy. Quantification of tumor ADC heterogeneity may provide useful information to enable the prediction of chemotherapeutic response prior to the treatment to improve patient outcomes.

Whole-lesion histogram analysis of the apparent diffusion coefficient: Evaluation of the correlation with subtypes of mucinous breast carcinoma

PURPOSE

To evaluate the utility of the whole-lesion histogram apparent diffusion coefficient (ADC) for characterizing the heterogeneity of mucinous breast carcinoma (MBC) and to determine which ADC metrics may help to best differentiate subtypes of MBC.

MATERIALS AND METHODS

This retrospective study involved 52 MBC patients, including 37 pure MBC (PMBC) and 15 mixed MBC (MMBC). The PMBC patients were subtyped into PMBC-A (20 cases) and PMBC-B (17 cases) groups. All patients underwent preoperative diffusion-weighted imaging (DWI) at 1.5T and the whole-lesion ADC assessments were generated. Histogram-derived ADC parameters were compared between PMBC vs. MMBC and PMBC-A vs. PMBC-B, and receiver operating characteristic (ROC) curve analysis was used to determine optimal histogram parameters for differentiating these groups.

RESULTS

The PMBC group exhibited significantly higher ADC values for the mean (P = 0.004), 25^th (P = 0.004), 50^th (P = 0.004), 75^th (P = 0.006), and 90^th percentiles (P = 0.013) and skewness (P = 0.021) than did the MMBC group. The 25^th percentile of ADC values achieved the highest area under the curve (AUC) (0.792), with a cutoff value of 1.345 × 10^-3 mm² /s, in distinguishing PMBC and MMBC. The PMBC-A group showed significantly higher ADC values for the mean (P = 0.049), 25^th (P = 0.015), and 50^th (P = 0.026) percentiles and skewness (P = 0.004) than did the PMBC-B group. The 25^th percentile of the ADC cutoff value (1.476 × 10^-3 mm² /s) demonstrated the best AUC (0.837) among the ADC values for distinguishing PMBC-A and PMBC-B.

CONCLUSION

Whole-lesion ADC histogram analysis enables comprehensive evaluation of an MBC in its entirety and differentiating subtypes of MBC. Thus, it may be a helpful and supportive tool for conventional MRI.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:391-400.

Multiparametric MR diffusion-weighted imaging for monitoring the ultra-early treatment effect of sorafenib in human hepatocellular carcinoma xenografts

PURPOSE

To investigate the value of multiparametric magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) for monitoring the ultra-early (within 24 hours) treatment effect of sorafenib in human hepatocellular carcinoma (HCC) xenografts.

MATERIALS AND METHODS

With institutional Animal Care and Use Committee approval, 16 BALB/c nude mice bearing subcutaneous HCC xenografts underwent serial Gaussian and non-Gaussian DWI at baseline and 1, 3, 6, 12, and 24 hours posttreatment using a 1.5T whole-body MRI system. Gaussian-DWI-derived apparent diffusion coefficient (ADC), D, D*, and f, and non-Gaussian-DWI-derived MD, MK, DDC, and α were calculated and compared between the control (n = 6) and sorafenib-treated groups (n = 10) with respect to each timepoint using Mann-Whitney or Wilcoxon signed-rank test. Results were validated by pathology.

RESULTS

Compared to baseline, ADC and D at 1 hour posttreatment (P = 0.005 and P = 0.013, respectively) and MD and DDC at 3 hours posttreatment (P = 0.009 and P = 0.005, respectively) significantly decreased and remained lower through 12 hours of follow-up (P = 0.005-0.022), followed by recovery to baseline levels at 24 hours posttreatment (P = 0.139-0.646). MK significantly increased at 1 hour posttreatment (P = 0.013) and remained higher through 24 hours of follow-up (P = 0.009-0.028). No significant differences were found in D*, f, and α at different timepoints (P = 0.188-0.714). Light microscopy did not reveal abnormal findings until 3 hours posttreatment, when central patchy necrosis was observed; more prominent diffuse necrosis was observed at 24 hours. Electron microscopy revealed swollen mitochondria at 1 hour posttreatment and accumulation of intracellular autophagosomes from 3 to 24 hours posttreatment.

CONCLUSION

Multiparametric DWI might evaluate therapeutic effects of sorafenib in HCC, where metrics of ADC, D, and MK could potentially serve as imaging biomarkers for monitoring therapeutic effects as early as 1 hour after treatment. Level of Evidence 1 Technical Efficacy: Stage 4 J. MAGN. RESON. IMAGING 2017;46:248-256.

Differentiation between malignant and benign thyroid nodules and stratification of papillary thyroid cancer with aggressive histological features: Whole-lesion diffusion-weighted imaging histogram analysis

PURPOSE

To explore the usefulness of whole-lesion histogram analysis of apparent diffusion coefficient (ADC) derived from reduced field-of-view (r-FOV) diffusion-weighted imaging (DWI) in differentiating malignant and benign thyroid nodules and stratifying papillary thyroid cancer (PTC) with aggressive histological features.

MATERIALS AND METHODS

This Institutional Review Board-approved, retrospective study included 93 patients with 101 pathologically proven thyroid nodules. All patients underwent preoperative r-FOV DWI at 3T. The whole-lesion ADC assessments were performed for each patient. Histogram-derived ADC parameters between different subgroups (pathologic type, extrathyroidal extension, lymph node metastasis) were compared. Receiver operating characteristic curve analysis was used to determine optimal histogram parameters in differentiating benign and malignant nodules and predicting aggressiveness of PTC.

RESULTS

Mean ADC, median ADC, 5^th percentile ADC, 25^th percentile ADC, 75^th percentile ADC, 95^th percentile ADC (all P < 0.001), and kurtosis (P = 0.001) were significantly lower in malignant thyroid nodules, and mean ADC achieved the highest AUC (0.919) with a cutoff value of 1842.78 × 10^-6 mm² /s in differentiating malignant and benign nodules. Compared to the PTCs without extrathyroidal extension, PTCs with extrathyroidal extension showed significantly lower median ADC, 5^th percentile ADC, and 25^th percentile ADC. The 5^th percentile ADC achieved the highest AUC (0.757) with cutoff value of 911.5 × 10^-6 mm² /s for differentiating between PTCs with and without extrathyroidal extension.

CONCLUSION

Whole-lesion ADC histogram analysis might help to differentiate malignant nodules from benign ones and show the PTCs with extrathyroidal extension. J. Magn. Reson. Imaging 2016;44:1546-1555.