Diagnostic accuracy and reliability of CT-based Node-RADS for colon cancer.

OBJECTIVE: The Node-RADS classification was recently published as a classification system to better characterize lymph nodes in oncological imaging. The present analysis investigated the diagnostic benefit of the Node-RADS classification of staging computed tomography (CT) images to categorize and stage lymph nodes in patients with colon cancer. MATERIALS AND METHODS: All patients were surgically resected and the lymph nodes were histopathological analyzed. All investigated lymph nodes were scored in accordance to the Node-RADS classification by two experienced radiologists. Interreader variability was assessed with Cohen's kappa analysis, discrimination analysis was performed with Mann-Whitney-U test and diagnostic accuracy was assessed with receiver-operating characteristics (ROC) curve analysis. RESULTS: Overall, 108 patients (n = 49 females, 45.3%) with a mean age of 70.08 ± 14.34 years were included. In discrimination analysis, the total Node-RADS score showed statistically significant differences between N- and N + stage (for reader 1: mean 1.89 ± 1.09 score for N- versus 2.93 ± 1.62 score for N+, for reader 2: 1.33 ± 0.48 score for N- versus 3.65 ± 0.94 score for N+, p = 0.001, respectively). ROC curve analysis for lymph node discrimination showed an area under the curve of 0.68. A threshold value of 2 resulted in a sensitivity of 0.62 and a specificity of 0.71. CONCLUSION: Node-RADS score derived from staging CT shows only limited diagnostic accuracy to correctly predict nodal positivity in colon cancer. The interreader variability seems to be high and should question the clinical translation for this tumour entity.

Impact of quantitative CT texture analysis on the outcome of CT-guided bone biopsy.

Texture analysis can provide new imaging-based biomarkers. Texture analysis derived from computed tomography (CT) might be able to better characterize patients undergoing CT-guided percutaneous bone biopsy. The present study evaluated this and correlated texture features with bioptic outcome in patients undergoing CT-guided bone biopsy. Overall, 123 patients (89 female patients, 72.4 %) were included into the present study. All patients underwent CT-guided percutaneous bone biopsy with an 11 Gauge coaxial needle. Clinical parameters and quantitative imaging features were investigated. Random forest classifier was used to predict a positive biopsy result. Overall, 69 patients had osteolytic metastasis (56.1 %) and 54 had osteoblastic metastasis (43.9 %). The overall positive biopsy rate was 72 %. The developed radiomics model demonstrated a prediction accuracy of a positive biopsy result with an AUC of 0.75 [95 %CI 0.65 - 0.85]. In a subgroup of breast cancer patients, the model achieved an AUC of 0.85 [95 %CI 0.73 - 0.96]. In the subgroup of non-breast cancer patients, the signature achieved an AUC of 0.80 [95 %CI 0.60 - 0.99]. Quantitative CT imaging findings comprised of conventional and texture features can aid to predict the bioptic result of CT-guided bone biopsies. The developed radiomics signature aids in clinical decision-making, and could identify patients at risk for a negative biopsy.

Impact of CT texture analysis on complication rate in CT-guided liver biopsies.

Aim of the study: Texture analysis derived from computed tomography (CT) involves quantitative imaging parameters characterizing possible valuable associations with clinical purposes. Their prognostic capability in patients undergoing percutaneous CT-guided liver biopsy to identify associations with postinterventional bleeding complications and biopsy success is not sufficiently explored. Material and methods: Three hundred fifteen patients (124 female, 39%) with a mean age of 62.5 ±10.2 years underwent percutaneous CT-guided liver biopsy and were analyzed regarding clinical, procedure-related, and CT texture features. Results: Thirty patients (9.5%) presented with bleeding after biopsy (including two requiring interventional treatment), whereas 46 patients (14.6%) had negative biopsy successes. Distance of lesion from liver capsule was statistically significantly different in patients with and without bleeding (p = 0.015). Several texture features were statistically significantly different between the groups, S(0,1)SumAverg having the highest significance (p = 0.004). Regarding unsuccessful biopsy results, liver fibrosis was the only clinical feature with statistical significance (p = 0.049). Only two texture features (S(4,-4)InvDfMom and Teta3) were statistically different between the groups according to the biopsy result. Conclusions: Several CT texture features of the target lesion and the length from the capsule to the lesion were associated with bleeding complications after CT-guided percutaneous liver biopsy. This could be used to identify patients at risk at the beginning of the procedure.

MRI Texture Analysis of Inguinal Lymph Node Metastasis in Vulvar Cancer - Associations With Histopathology.

BACKGROUND/AIM: Texture analysis is a quantitative imaging technique that provides novel biomarkers beyond conventional image reading. This study aimed to investigate the correlation between texture parameters and histopathological features of lymph nodes in patients with vulvar cancer. PATIENTS AND METHODS: Overall, nine female patients (mean age 70.1±13.4 years, range=39-87 years) were included in the analysis. All patients had squamous cell carcinomas and underwent upfront surgery with inguinal lymph node resection. Immunohistochemical assessment was performed using several markers of the epithelial-mesenchymal transition. The presurgical magnetic resonance imaging (MRI) was analyzed with the MaZda package. RESULTS: In discrimination analysis, several parameters derived from T1-weighted images showed statistically significant differences between non-metastatic and metastatic lymph nodes. The highest statistical significance was reached by the texture feature "S(0,3)InvDfMom" (p=0.016). In correlation analysis, significant associations were found between MRI texture parameters derived from both T1-weighted and T2-weighted images and the investigated histopathological features. Notably, S(0,3)InvDfMom derived from T1-weighted images highly correlated with the Vimentin-score (r=0.908, p=0.001). CONCLUSION: Several associations between MRI texture analysis and immunohistochemical parameters were identified in metastasized lymph nodes of cases with vulvar cancer.

CT texture analysis and node-RADS CT score of mediastinal lymph nodes - diagnostic performance in lung cancer patients.

BACKGROUND: Texture analysis derived from computed tomography (CT) can provide clinically relevant imaging biomarkers. Node-RADS is a recently proposed classification to categorize lymph nodes in radiological images. The present study sought to investigate the diagnostic abilities of CT texture analysis and Node-RADS to discriminate benign from malignant mediastinal lymph nodes in patients with lung cancer. METHODS: Ninety-one patients (n = 32 females, 35%) with a mean age of 64.8 ± 10.8 years were included in this retrospective study. Texture analysis was performed using the free available Mazda software. All lymph nodes were scored accordingly to the Node-RADS classification. All primary tumors and all investigated mediastinal lymph nodes were histopathologically confirmed during clinical workup. RESULTS: In discrimination analysis, Node-RADS score showed statistically significant differences between N0 and N1-3 (p < 0.001). Multiple texture features were different between benign and malignant lymph nodes: S(1,0)AngScMom, S(1,0)SumEntrp, S(1,0)Entropy, S(0,1)SumAverg. Correlation analysis revealed positive associations between the texture features with Node-RADS score: S(4,0)Entropy (r = 0.72, p < 0.001), S(3,0) Entropy (r = 0.72, p < 0.001), S(2,2)Entropy (r = 0.72, p < 0.001). CONCLUSIONS: Several texture features and Node-RADS derived from CT were associated with the malignancy of mediastinal lymph nodes and might therefore be helpful for discrimination purposes. Both of the two quantitative assessments could be translated and used in clinical routine.

Associations between tumor and edema volumes with tumor infiltrating lymphocytes in brain metastasis - A preliminary study.

OBJECTIVE: Perifocal edema of brain tumors is associated with survival and neurological symptoms. The present study sought to elucidate the association between edema volume and tumor infiltrating lymphocytes (TIL) in brain metastasis. METHODS: 25 patients with brain metastasis were included into the retrospective study. TILs expressing CD45 was analyzed with leucocyte common antigen staining. MRI was used to semiautomatically estimate tumor and edema volumes. RESULTS: No correlation between tumor volume and edema volume was identified. A positive correlation was identified between tumor volume and TILs expressing CD45 of the stromal compartment (r = 0.46, p = 0.02). No correlations were identified between TILs expressing CD45 and edema volume. CONCLUSIONS: The present study identified correlations between TILs expressing CD45 and volume of BM. The tumor growth of BM might lead to a recruitment of TIL, which could be assessed by MRI.

Associations Between ADC Texture Analysis and Tumor Infiltrating Lymphocytes in Brain Metastasis - A Preliminary Study.

BACKGROUND/AIM: Tumor infiltrating lymphocytes (TILs) are an important prognostic factor in brain metastasis (BM). This study elucidated associations between apparent diffusion coefficient (ADC) texture analysis and TIL in BM. PATIENTS AND METHODS: Eleven patients with BM were retrospectively included into the study. TIL levels were analyzed with Leucocyte-common antigen staining. Clinical routine magnetic resonance imaging was used to calculate the texture features. RESULTS: ADC GrayLevelNonUniformity correlated with TILs of the stromal compartment (r=0.67, p=0.02). ADC HighGrayLevelRunEmphasis and ADC Coarseness showed associations with TILs of the tumoral compartment (r=-0.60, p=0.04 and r=0.68, p=0.02, respectively). CONCLUSION: ADC texture features correlated with TIL levels in BM. ADC texture features could aid in reflecting the complex tumor-micromilieu in a non-invasive manner.

Perifocal edema volume is not associated with immunohistochemical features reflecting proliferation potential, microvessel density, neoangiogenesis and invasiveness in brain metastasis.

OBJECTIVE: Perifocal edema of brain tumors is associated with survival and neurological symptoms. Our aim was to analyze associations between perifocal edema and immunohistochemical features including proliferation potential, microvessel density, neoangiogenesis and invasiveness in brain metastasis (BM). METHODS: 35 patients with BM were included into the retrospective study. The tumors were localized supratentorial in 25 lesions (71.4%) and infratentorial in 10 lesions (28.6%). The following immunohistochemical features were calculated on histopathological specimens: microvessel density, proliferation index Ki 67, matrix-metallopeptidase 9 (MMP9) extracellular matrix metalloproteinase inducer (EMMPRIN) and vascular endothelial growth factor (VEGF) expression. Tumor and edema volumes were estimated semiautomatically on magnetic resonance images. RESULTS: There were no correlations between tumor volume and edema volume. Moreover, no correlation was identified between the investigated immunohistochemical features and tumor/edema volume. In the non-small cell lung cancer subgroup, a positive correlation between tumor volume and VEGF expression was observed (r = 0.52, P = 0.02) and edema volume correlated inversely with MMP9 expression (r = -0.53, P = 0.02). CONCLUSION: In BM, no linear associations exist between tumor volumes, edema volumes and immunohistochemical features reflecting proliferation potential, neoangiogenesis, microvessel density and MMP9 expression. However, in the subgroup of non-small cell lung cancer, there might be associations between MMP9 expression and edema volume as well as between tumor volume and angiogenesis.

18F-FDG-PET Can Predict Microvessel Density in Head and Neck Squamous Cell Carcinoma.

Aim: Positron emission tomography (PET) with 18F-fluordeoxyglucose (18F-FDG) plays an essential role in the staging and tumor monitoring of head and neck squamous cell carcinoma (HNSCC). Microvessel density (MVD) is one of the clinically important histopathological features in HNSCC. The purpose of this study was to analyze possible associations between 18F-FDG-PET findings and MVD parameters in HNSCC. Materials and Methods: Overall, 22 patients with a mean age of 55.2 ± 11.0 and with different HNSCC were acquired. In all cases, whole-body 18F-FDG-PET was performed. For each tumor, the maximum and mean standardized uptake values (SUVmax; SUVmean) were determined. The MVD, including stained vessel area and total number of vessels, was estimated on CD105 stained specimens. All specimens were digitalized and analyzed by using ImageJ software 1.48v. Spearman's correlation coefficient (r) was used to analyze associations between investigated parameters. p-values of <0.05 were taken to indicate statistical significance. Results: SUVmax correlated with vessel area (r = 0.532, p = 0.011) and vessel count (r = 0.434, p = 0.043). Receiver operating characteristic analysis identified a threshold SUVmax of 15 to predict tumors with high MVD with a sensitivity of 72.7% and specificity of 81.8%, with an area under the curve of 82.6%. Conclusion: 8F-FDG-PET parameters correlate statistically significantly with MVD in HNSCC. SUVmax may be used for discrimination of tumors with high tumor-related MVD.

Associations Between [18F]FDG-PET and Complex Histopathological Parameters Including Tumor Cell Count and Expression of KI 67, EGFR, VEGF, HIF-1α, and p53 in Head and Neck Squamous Cell Carcinoma.

PURPOSE: Head and neck squamous cell carcinoma (HNSCC) is one of common cancers worldwide. Positron emission tomography (PET) with 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) is increasingly used for diagnosing and staging, as well as for monitoring of treatment of HNSCC. PET parameters like maximum and mean standard uptake values (SUVmax, SUVmean) can predict the behavior of HNSCC. The purpose of this study was to analyze possible associations between these PET parameters and clinically relevant histopathological features in patients with HNSCC. PROCEDURES: Overall, 22 patients, mean age, 55.2 ± 11.0 years, with different HNSCC were acquired. Low grade (G1/2) tumors were diagnosed in 10 cases (45 %) and high grade (G3) tumor in 12 (55 %) patients. In all cases, whole body PET was performed. For this study, the following specimen stainings were performed: MIB-1 staining (KI 67 expression), epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF), tumor suppressor protein p53, hypoxia-inducible factor (HIF)-1α, and human papilloma virus (p16 expression). All stained specimens were digitalized and analyzed by using the ImageJ software 1.48v. Spearman's correlation coefficient (ρ) was used to analyze associations between investigated parameters. P values <0.05 were taken to indicate statistical significance. RESULTS: P16-negative tumors showed statistically significant higher SUVmax (ρ = 0.006) and SUVmean values (ρ = 0.002) in comparison to p16-positive carcinomas. No significant differences were identified in the analyzed parameters between poorly and moderately/well-differentiated tumors. In overall sample, there were no statistically significant correlations between the [18F]FDG-PET and histopathological parameters. Also, in G1/2 tumors, no significant correlations were identified. In G3 carcinomas, cell count correlated statistical significant with SUVmax (p = 0.580, P = 0.048) and SUVmean (ρ = 0.587, P = 0.045). CONCLUSION: Associations between [18F]FDG-PET parameters and different histopathological features in HNSCC depend significantly on tumor grading. In G1/2 carcinomas, there were no significant correlations between [18F]FDG-PET parameters and histopathology. In G3 lesions, SUVmax and SUVmean reflect tumor cellularity.

Metabolo-volumetric parameters of 18F-FDG-PET can predict expression of EGFR and HIF 1alpha in uterine cervical cancer.

BACKGROUND: The aim of our study was to investigate possible relationships between 18F-FDG-PET parameters and clinically relevant histopathological findings in patients with cervical cancer (CC). METHODS: Eighteen female patients (mean age 55.4 years) with histologically confirmed squamous cell CC were involved into the study. In all cases, 18F-FDG-PET CT was performed. Mean and maximum standardized uptake values (SUVmean and SUVmax), total lesion glycolysis (TLG) and metabolic tumor volume (MTV) were determined on PET-images. For every tumor the following specimen stainings were performed: epidermal growth factor receptor (EGFR), vascular endothelial growth factor (VEGF), tumor suppressor protein p53, hypoxia-inducible factor (HIF)-1α, and histone 3. All stained specimens were digitalized and analyzed by using the ImageJ software 1.48v. Spearman's correlation coefficient (p) was used to analyze associations between investigated parameters. p-values < 0.05 were taken to indicate statistical significance. RESULTS: TLG and MTV correlated well with expression of EGFR (p= 0.601, P= 0.008 and p= 0.586, P= 0.011, respectively). SUVmedian correlated inversely with expression of HIF 1alpha (p=-0.509, P= 0.031). SUVmean tended to correlate with expression of EGFR and HIF 1alpha. None of the PET parameters correlated with expression of Histone 3, p53 and VEGF. CONCLUSION: TLG and MTV can reflect expression of EGFR and SUVmedian correlated significantly with expression of HIF-1α. None of the PET parameters can predict expression of Histone 3, p53 and VEGF.

Histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging can predict histopathological findings including proliferation potential, cellularity, and nucleic areas in head and neck squamous cell carcinoma.

Our purpose was to analyze possible associations between histogram analysis parameters of dynamic contrast-enhanced magnetic resonance imaging DCE MRI and histopathological findings like proliferation index, cell count and nucleic areas in head and neck squamous cell carcinoma (HNSCC). 30 patients (mean age 57.0 years) with primary HNSCC were included in the study. In every case, histogram analysis parameters of Ktrans, Ve, and Kep were estimated using a mathlab based software. Tumor proliferation index, cell count, and nucleic areas were estimated on Ki 67 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters. KI 67 correlated with Ktrans min (p = -0.386, P = 0.043) and s Ktrans skewness (p = 0.382, P = 0.045), Ve min (p = -0.473, P = 0.011), Ve entropy (p = 0.424, P = 0.025), and Kep entropy (p = 0.464, P = 0.013). Cell count correlated with Ktrans kurtosis (p = 0.40, P = 0.034), Ve entropy (p = 0.475, P = 0.011). Total nucleic area correlated with Ve max (p = 0.386, P = 0.042) and Ve entropy (p = 0.411, P = 0.030). In G1/2 tumors, only Ktrans entropy correlated well with total (P =0.78, P =0.013) and average nucleic areas (p = 0.655, P = 0.006). In G3 tumors, KI 67 correlated with Ve min (p = -0.552, P = 0.022) and Ve entropy (p = 0.524, P = 0.031). Ve max correlated with total nucleic area (p = 0.483, P = 0.049). Kep max correlated with total area (p = -0.51, P = 0.037), and Kep entropy with KI 67 (p = 0.567, P = 0.018). We concluded that histogram-based parameters skewness, kurtosis and entropy of Ktrans, Ve, and Kep can be used as markers for proliferation activity, cellularity and nucleic content in HNSCC. Tumor grading influences significantly associations between perfusion and histopathological parameters.

Histogram analysis of ADC in rectal cancer: associations with different histopathological findings including expression of EGFR, Hif1-alpha, VEGF, p53, PD1, and KI 67. A preliminary study.

Functional imaging modalities like Diffusion-weighted imaging are increasingly used to predict tumor behavior like cellularity and vascularity in different tumors. Histogram analysis is an emergent imaging analysis, in which every voxel is used to obtain a histogram and therefore statistically information about tumors can be provided. The purpose of this study was to elucidate possible associations between ADC histogram parameters and several immunhistochemical features in rectal cancer. Overall, 11 patients with histologically proven rectal cancer were included into the study. There were 2 (18.18%) females and 9 males with a mean age of 67.1 years. KI 67-index, expression of p53, EGFR, VEGF, and Hif1-alpha were semiautomatically estimated. The tumors were divided into PD1-positive and PD1-negative lesions. ADC histogram analysis was performed as a whole lesion measurement using an in-house matlab application. Spearman's correlation analysis revealed a strong correlation between EGFR expression and ADCmax (p=0.72, P=0.02). None of the vascular parameters (VEGF, Hif1-alpha) correlated with ADC parameters. Kurtosis and skewness correlated inversely with p53 expression (p=-0.64, P=0.03 and p=-0.81, P=0.002, respectively). ADCmedian and ADCmode correlated with Ki67 (p=-0.62, P=0.04 and p=-0.65, P=0.03, respectively). PD1-positive tumors showed statistically significant lower ADCmax values in comparison to PD1-negative tumors, 1.93 ± 0.36 vs 2.32 ± 0.47×10-3mm2/s, p=0.04. Several associations were identified between histogram parameter derived from ADC maps and EGFR, KI 67 and p53 expression in rectal cancer. Furthermore, ADCmax was different between PD1 positive and PD1 negative tumors indicating an important role of ADC parameters for possible future treatment prediction.

Correlations between intravoxel incoherent motion (IVIM) parameters and histological findings in rectal cancer: preliminary results.

Our purpose was to correlate different intravoxel incoherent motion (IVIM), histopathological and clinical parameters in rectal cancer. 17 patients with histologically proven rectal cancer investigated on a 3.T device were included into the study. DWI was performed using a multi-slice single-shot echo-planar imaging sequence with b values of 0, 50, 200, 500 and 1000 s/mm.2 A polygonal region of interest was drawn within the tumors on every b image. The following parameters were retrieved from IVIM: apparent diffusion coefficient (ADC), true diffusion (D), pseudo diffusion coefficient (D*), perfusion factor (f), and relative perfusion f·D*. In every case, cell count, nucleic areas, proliferation index KI 67, and microvessel density were estimated on histopathological specimens. Pearson's correlation coefficient was used to analyze the association between the parameters. ADC correlated well with KI 67 index and D tended to correlate with cell count and KI 67. ADC and D tended to correlate with total nucleic area. The perfusion factor f correlated well with stained vessel area, total vessel area, and vessel count. D* and fD* correlated with mean vessel diameter. Distant metastasized tumors had higher D* and fD* values. IVIM parameter reflected different clinical and histopathological features in rectal cancer.

Parameters of simultaneous 18F-FDG-PET/MRI predict tumor stage and several histopathological features in uterine cervical cancer.

The purpose of this study was to analyze associations between apparent diffusion coefficient (ADC) and standardized uptake values (SUV) values and different histopathological parameters in uterine cervical cancer. 21 patients with primary uterine cervical cancer were involved into the study. All patients underwent a whole body simultaneous18F-FDG PET/MRI. Mean and maximum SUV were noted (SUVmean and SUVmax). In all tumors minimal, mean, and maximal ADC values (ADCmin, ADCmean, and ADCmax) were estimated. Combined parameters were calculated: SUVmax/SUVmean, ADCmin/ ADCmean, SUVmax/ADCmin and SUVmax/ADCmean. In all cases the diagnosis was confirmed histopathologically by tumor biopsy. Histological slices were stained by hematoxilin and eosin, MIB 1 monoclonal antibody, and p16. All histopathological images were digitalized and analyzed by using a ImageJ software 1.48v. The following parameters were estimated: cell count, proliferation index KI 67, total and average nucleic areas, epithelial and stromal areas. Spearman's correlation coefficient was used to analyze associations between ADC and SUV values and histological parameters. P values ≤ 0.05 were considered as statistically significant. ADCmin and ADCmin/ ADCmean were statistically significant lower in N positive tumors. KI 67 correlated statistically significant with SUVmax (r = 0.59, p = 0.005), SUVmean (0.45, p = 0.04), ADCmin (r = -0.48, p = 0.03), SUVmax/ADCmin (r = 0.71, p = 0.001), SUVmax/ADCmean (0.75, p = 0.001). SUVmax correlated well with epithelial area (r = 0.71, p = 0.001) and stromal areas (r = -0.71, p = 0.001). SUV values, ADCmin, SUVmax/ADCmin and SUVmax/ADCmean correlated statistically significant with KI 67 and can be used to estimate the proliferation potential of tumors. SUV values correlated strong with epithelial area of tumor reflected metabolic active areas.

Correlations Between DCE MRI and Histopathological Parameters in Head and Neck Squamous Cell Carcinoma.

BACKGROUND: Dynamic contrast-enhanced magnetic resonance imaging (DCE MRI) can characterize perfusion and vascularization of tissues. DCE MRI parameters can differentiate between malignant and benign lesions and predict tumor grading. The purpose of this study was to correlate DCE MRI findings and various histopathological parameters in head and neck squamous cell carcinoma (HNSCC). PATIENTS AND METHODS: Sixteen patients with histologically proven HNSCC (11 cases primary tumors and in 5 patients with local tumor recurrence) were included in the study. DCE imaging was performed in all cases and the following parameters were estimated: Ktrans, Ve, Kep, and iAUC. The tumor proliferation index was estimated on Ki 67 antigen stained specimens. Microvessel density parameters (stained vessel area, total vessel area, number of vessels, and mean vessel diameter) were estimated on CD31 antigen stained specimens. Spearman's non-parametric rank sum correlation coefficients were calculated between DCE and different histopathological parameters. RESULTS: The mean values of DCE perfusion parameters were as follows: Ktrans 0.189 ± 0.056 min-1, Kep 0.390 ± 0.160 min-1, Ve 0.548 ± 0.119%, and iAUC 22.40 ± 12.57. Significant correlations were observed between Kep and stained vessel areas (r = 0.51, P = .041) and total vessel areas (r = 0.5118, P = .043); between Ve and mean vessel diameter (r = -0.59, P = .017). Cell count had a tendency to correlate with Ve (r = -0.48, P = .058). In an analysis of the primary HNSCC only, a significant inverse correlation between Ktrans and KI 67 was identified (r = -0.62, P = .041). Our analysis showed significant correlations between DCE parameters and histopathological findings in HNSCC.

Diffusion-Weighted Imaging Using a Readout-Segmented, Multishot EPI Sequence at 3 T Distinguishes between Morphologically Differentiated and Undifferentiated Subtypes of Thyroid Carcinoma-A Preliminary Study.

BACKGROUND: Thyroid carcinomas represent the most frequent endocrine malignancies. Recent studies were able to distinguish malignant from benign nodules of the thyroid gland with diffusion-weighted imaging (DWI). Although this differentiation is undoubtedly helpful, presurgical discrimination between well-differentiated and undifferentiated carcinomas would be crucial to define the optimal treatment algorithm. Therefore, the aim of this study was to investigate if readout-segmented multishot echo planar DWI is able to differentiate between differentiated and undifferentiated subtypes of thyroid carcinomas. PATIENTS AND METHODS: Fourteen patients with different types of thyroid carcinomas who received preoperative DWI were included in our study. In all lesions, apparent diffusion coefficient (ADC)min, ADCmean, ADCmax, and D were estimated on the basis of region of interest measurements after coregistration with T1-weighted, postcontrast images. All tumors were resected and analyzed histopathologically. Ki-67 index, p53 synthesis, cellularity, and total and average nucleic areas were estimated using ImageJ version 1.48. RESULTS: Analysis of variance revealed a statistically significant difference in ADCmean values between differentiated and undifferentiated thyroid carcinomas (P=.022). Spearman Rho calculation identified significant correlations between ADCmax and cell count (r=0.541, P=.046) as well as between ADCmax and total nuclei area (r=0.605, P=.022). CONCLUSION: DWI can distinguish between differentiated and undifferentiated thyroid carcinomas.

Simultaneous (18)F-FDG-PET/MRI: Associations between diffusion, glucose metabolism and histopathological parameters in patients with head and neck squamous cell carcinoma.

OBJECTIVES: To analyze possible associations between functional simultaneous (18)F-FDG-PET/MR imaging parameters and histopathological parameters in head and neck squamous cell carcinoma (HNSCC). MATERIAL AND METHODS: 11 patients (2 female, 9 male; mean age 56.0years) with biopsy-proven primary HNSCC underwent simultaneous (18)F-FDG-PET/MRI with a dedicated head and neck protocol including diffusion weighted imaging. For each tumor, glucose metabolism was estimated with standardized uptake values (SUV) and diffusion restriction was calculated using apparent diffusion coefficients (ADC). The tumor proliferation index was estimated on Ki 67 antigen stained specimens. Cell count, total nucleic area, and average nucleic area were estimated in each case. Pearson's correlation coefficient was used to analyze possible associations between the estimated parameters. RESULTS: The mean SUVmax value was 24.41±6.51, and SUVmean value 15.01±4.07. Mean values (×10(-3)mm(2)s(-1)) of ADC parameters were as follows: ADCmin: 0.65±0.20; ADCmean: 1.28±0.18; and ADCmax: 2.16±0.35. Histopathological analysis identified the following results: cell count 1069.82±388.66, total nucleic area 150771.09±61177.12µm(2), average nucleic area 142.90±57.27µm(2) and proliferation index 49.09±22.67%. ADCmean correlated with Ki 67 level (r=-0.728, p=0.011) and total nucleic area (r=-0.691, p=0.019) and tended to correlate with average nucleic area (r=-0.527, p=0.096). ADCmax correlated with Ki 67 level (r=-0.633, p=0.036). SUVmax also tended to correlate with average nucleic area (r=0.573, p=0.066). Combined parameter SUVmax/ADCmin correlated with average nucleic area (r=0.627, p=0.039). CONCLUSION: ADC and SUV values showed significant correlations with different histopathological parameters and can be used as biological markers in HNSCC.