Correlation analysis of apparent diffusion coefficient value and P53 and Ki-67 expression in esophageal squamous cell carcinoma

Correlation of dynamic contrast-enhanced ultrasonography and the Ki-67 labelling index in pancreatic ductal adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) is a highly malignant and aggressive tumor, and high Ki-67 expression indicates poor histological differentiation and prognosis. Therefore, one of the challenges in diagnosing preoperatively patients with PDAC is predicting the degree of malignancy. Dynamic contrast-enhanced ultrasonography (DCE-US) plays a crucial role in abdominal tumor diagnosis, and can adequately show the microvascular composition within the tumors. However, the relationship between DCE-US and the Ki-67 labelling index remains unclear at the present time.

AIM

To predict the correlation between Ki-67 expression and the parameters of DCE-US.

METHODS

Patients with PDAC who underwent DCE-US were retrospectively analyzed. Patients who had received any treatment (radiotherapy or chemotherapy) prior to DCE-US; had incomplete clinical, imaging, or pathologic information; and had poor-quality image analysis were excluded. Correlations between Ki-67 expression and the parameters of DCE-US in patients with PDAC were assessed using Spearman's rank correlation analysis. The diagnostic performances of these parameters in high Ki-67 expression group were evaluated according to receiver operating characteristic curve.

RESULTS

Based on the Ki-67 labelling index, 30 patients were divided into two groups, i.e., the high expression group and the low expression group. Among the relative quantitative parameters between the two groups, relative half-decrease time (rHDT), relative peak enhancement, relative wash-in perfusion index and relative wash-in rate were significantly different between two groups (P = 0.018, P = 0.025, P = 0.028, P = 0.035, respectively). The DCE-US parameter rHDT was moderately correlated with Ki-67 expression, and rHDT ≥ 1.07 was more helpful in accurately diagnosing high Ki-67 expression, exhibiting a sensitivity and specificity of 53.8% and 94.1%, respectively.

CONCLUSION

One parameter of DCE-US, rHDT, correlates with high Ki-67 expression. It demonstrates that parameters obtained noninvasively by DCE-US could better predict Ki-67 expression in PDAC preoperatively.

Preoperative CT histogram analysis to predict the expression of Ki-67 in solid pseudopapillary tumours of the pancreas

AIM

To explore the value of preoperative computed tomography (CT) histogram features in predicting the expression status of Ki-67 in patients with solid pseudopapillary pancreatic tumours (SPTP).

MATERIALS AND METHODS

This retrospective study analysed venous phase CT images of 39 patients with SPTP confirmed at surgery and histopathology and measured using the Ki-67 proliferation index from November 2015 to February 2022. According to the Ki-67 proliferation index, they were divided into high expression (Ki-67 ≥ 4%) and low expression (Ki-67 < 4%) groups. The histogram features of quantitative parameters were extracted using MaZda software, and the quantitative parameters of CT histograms were compared between groups. The receiver operating characteristic (ROC) curves of the patients were plotted according to the parameters, with statistically significant differences. The area under the curve (AUC), sensitivity, and specificity were calculated, and the effectiveness of the histogram parameters in predicting Ki-67 expression was analysed and evaluated.

RESULTS

In total, 27 SPTP patients were enrolled, including 11 with high expression of Ki-67 and 16 with low expression. Comparative analysis of the Ki-67 high- and low-expression groups revealed a statistically significant in necrosis and variance (p<0.05). ROC curve analysis showed that the AUC of necrosis and variance predicting Ki-67 expression status were 0.753 and 0.841, the sensitivities were 81.8% and 81.3%, and the specificities were 68.7% and 81.8%, respectively.

CONCLUSION

Preoperative CT histogram features help predict Ki-67 expression status in patients with SPTP.

Quantitative dynamic contrast-enhanced parameters and intravoxel incoherent motion facilitate the prediction of TP53 status and risk stratification of early-stage endometrial carcinoma

BACKGROUND

The aim of the study was to investigate the value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and intravoxel incoherent motion (IVIM) in differentiating TP53-mutant from wild type, low-risk from non-low-risk early-stage endometrial carcinoma (EC).

PATIENTS AND METHODS

A total of 74 EC patients underwent pelvic MRI. Parameters volume transfer constant (K^trans), rate transfer constant (K_ep), the volume of extravascular extracellular space per unit volume of tissue (V_e), true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and microvascular volume fraction (f) were compared. The combination of parameters was investigated by logistic regression and evaluated by bootstrap (1000 samples), receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

RESULTS

In the TP53-mutant group, K^trans and K_ep were higher and D was lower than in the TP53-wild group; K^trans, V_e, f, and D were lower in the non-low-risk group than in the low-risk group (all P < 0.05). In the identification of TP53-mutant and TP53-wild early-stage EC, K^trans and D were independent predictors, and the combination of them had an optimal diagnostic efficacy (AUC, 0.867; sensitivity, 92.00%; specificity, 80.95%), which was significantly better than D (Z = 2.169, P = 0.030) and K^trans (Z = 2.572, P = 0.010). In the identification of low-risk and non-low-risk early-stage EC, K^trans, V_e, and f were independent predictors, and the combination of them had an optimal diagnostic efficacy (AUC, 0.947; sensitivity, 83.33%; specificity, 93.18%), which was significantly better than D (Z = 3.113, P = 0.002), f (Z = 4.317, P < 0.001), K^trans (Z = 2.713, P = 0.007), and V_e (Z = 3.175, P = 0.002). The calibration curves showed that the above two combinations of independent predictors, both have good consistency, and DCA showed that these combinations were reliable clinical prediction tools.

CONCLUSIONS

Both DCE-MRI and IVIM facilitate the prediction of TP53 status and risk stratification in early-stage EC. Compare with each single parameter, the combination of independent predictors provided better predictive power and may serve as a superior imaging marker.

Correlations between DKI and DWI with Ki-67 in gastric adenocarcinoma

BACKGROUND

Diffusion kurtosis imaging (DKI) has been applied for gastric adenocarcinoma. Correlations between its parameters and Ki-67 are unclear.

PURPOSE

To investigate the correlation between DKI and diffusion-weighted imaging (DWI) parameters with the Ki-67 index in gastric adenocarcinoma.

MATERIAL AND METHODS

A total of 54 patients with gastric adenocarcinoma were enrolled in the study and underwent DWI and DKI at 3.0-T MRI before surgery. Based on the settings of the regions of interest, the DWI and DKI parameters (including apparent diffusion coefficient [ADC], diffusion kurtosis [K], and diffusion coefficient [DK]) of each patient's gastric adenocarcinoma were measured and calculated. The participants were divided into two groups (low Ki-67 group and high Ki-67 groups). The intraclass correlation coefficient (ICC) and independent-sample t-test were used to compare differences in each parameter between two groups. Spearman's correlation coefficient was calculated to determine the correlation between Ki-67 and the parameters. Each parameter was compared using the area under the receiver operating characteristic curve. All parameters were included in the multivariate logistic regression analysis to explore the relationship between each parameter and high Ki-67 index.

RESULTS

ADC and DK were negatively relevant with Ki-67 and K was positively relevant with Ki-67 in gastric adenocarcinoma. ADC, DK, and K had diagnostic efficiency in differentiating the low Ki-67 group from the high Ki-67 group. A higher K value independently predicted a high Ki-67 status.

CONCLUSION

DWI and DKI reflected the proliferative characteristics of gastric adenocarcinoma. K was the strongest independent factor for predicting high Ki-67 status.

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

OBJECTIVE

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

PATIENTS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

The potential application of MR-derived ADCmin values from 68Ga-DOTATATE and 18F-FDG dual tracer PET/MR as replacements for FDG PET in assessment of grade and stage of pancreatic neuroendocrine tumors

BACKGROUND

To evaluate the utility of ⁶⁸Ga-DOTATATE and ¹⁸F-FDG PET/MR for prediction of grade and stage of pancreatic neuroendocrine tumors (PNETs), and to examine the correlation between parameters obtained from FDG PET and diffusion-weighted imaging (DWI) MR parameters.

METHODS

A retrospective study using ⁶⁸Ga-DOTATATE and ¹⁸F-FDG PET/MR imaging was performed between April 2020 and May 2022 on 46 individuals with histologically confirmed PNETs. Metabolic tumor volume (MTV), maximum standardized uptake value (FSUVmax), and tumor lesion glycolysis (TLG) for FDG; somatostatin receptor density (SRD), maximum standardized uptake value (GSUVmax), and total lesion somatostatin receptor density (TLSRD) for DOTATATE; and minimum and mean apparent diffusion coefficient (ADCmin and ADCmean) values for MRI, respectively. We performed Spearman's correlation analysis to examine the links between these variables and primary tumor stage and grading.

RESULTS

Higher PNET grading was associated with higher FSUVmax, MTV, and TLG values (P < 0.05). TLG, SRD, ADCmin, and ADCmean values were correlated with N staging, while SRD, MTV, ADCmin, TLG, and ADCmean were associated with M staging. Notably, ADCmin was a negative correlation between FSUVmax (r =  - 0.52; P < 0.001), MTV (r =  - 0.50; P < 0.001), and TLG (r =  - 0.56; P < 0.001).

CONCLUSIONS

This study highlights significant correlative relationships between FDG PET-derived parameters and ADCmin. ADCmin may offer utility as a tool for PNET staging and grading in lieu of FDG PET. ⁶⁸Ga-DOTATATE PET/MR alone may be a sufficient alternative to dual tracer PET/MR when conducting grading and staging of primary PNETs.

Correlation of Apparent Diffusion Coefficient With Proliferation and Apoptotic Indexes in a Murine Model of Fibrosarcoma: Comparison of Four Methods for MRI Region of Interest Positioning

BACKGROUND

Diffusion-weighted imaging (DWI) has demonstrated great potential in predicting the expression of tumor cell proliferation and apoptosis indexes.

PURPOSE

To evaluate the impact of four region of interest (ROI) methods on interobserver variability and apparent diffusion coefficient (ADC) values and to examine the correlation of ADC values with Ki-67, Bcl-2, and P53 labeling indexes (LIs) in a murine model of fibrosarcoma.

STUDY TYPE

Prospective, animal model.

ANIMAL MODEL

A total of 22 female BALB/c mice bearing intramuscular fibrosarcoma xenografts.

FIELD STRENGTH/SEQUENCE

A 3.0 T/T1-weighted fast spin-echo (FSE), T2-weighted fast relaxation fast spin-echo, and DWI PROPELLER FSE sequences.

ASSESSMENT

Four radiologists measured ADC values using four ROI methods (oval, freehand, small-sample, and whole-volume). Immunohistochemical assessment of Ki-67, Bcl-2, and P53 LIs was performed.

STATISTICAL TESTS

Interclass correlation coefficient (ICC), one-way analysis of variance followed by LSD-t post hoc analysis, and Pearson correlation test were performed. The statistical threshold was defined as a P-value of <0.05.

RESULTS

All ROI methods for ADC measurements showed excellent interobserver agreement (ICC range, 0.832-0.986). The ADC values demonstrated significant differences among the four ROI methods. The ADC values for oval, freehand, small-sample, and whole-volume ROI methods showed a moderately negative correlation with Ki-67 (r = -0.623; r = -0.629; r = -0.642, and r = -0.431) and Bcl-2 (r = -0.590; r = -0.597; r = -0.659, and r = -0.425) LIs, but no correlation with P53 LI (r = 0.364, P = 0.104; r = 0.350, P = 0.120; r = 0.379, P = 0.091; r = 0.390, P = 0.080).

DATA CONCLUSION

The ADC value can be used to evaluate cell proliferation and apoptosis indexes in a murine model of fibrosarcoma, employing the small-sample ROI as a reliable method.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 3.

A Multiparametric Method Based on Clinical and CT-Based Radiomics to Predict the Expression of p53 and VEGF in Patients With Spinal Giant Cell Tumor of Bone

Purpose

This project aimed to assess the significance of vascular endothelial growth factor (VEGF) and p53 for predicting progression-free survival (PFS) in patients with spinal giant cell tumor of bone (GCTB) and to construct models for predicting these two biomarkers based on clinical and computer tomography (CT) radiomics to identify high-risk patients for improving treatment.

Material and Methods

A retrospective study was performed from April 2009 to January 2019. A total of 80 patients with spinal GCTB who underwent surgery in our institution were identified. VEGF and p53 expression and clinical and general imaging information were collected. Multivariate Cox regression models were used to verify the prognostic factors. The radiomics features were extracted from the regions of interest (ROIs) in preoperative CT, and then important features were selected by the SVM to build classification models, evaluated by 10-fold crossvalidation. The clinical variables were processed using the same method to build a conventional model for comparison.

Results

The immunohistochemistry of 80 patients was obtained: 49 with high-VEGF and 31 with low-VEGF, 68 with wild-type p53, and 12 with mutant p53. p53 and VEGF were independent prognostic factors affecting PFS found in multivariate Cox regression analysis. For VEGF, the Spinal Instability Neoplastic Score (SINS) was greater in the high than low groups, p &lt; 0.001. For p53, SINS (p = 0.030) and Enneking stage (p = 0.017) were higher in mutant than wild-type groups. The VEGF radiomics model built using 3 features achieved an area under the curve (AUC) of 0.88, and the p53 radiomics model built using 4 features had an AUC of 0.79. The conventional model built using SINS, and the Enneking stage had a slightly lower AUC of 0.81 for VEGF and 0.72 for p53.

Conclusion

p53 and VEGF are associated with prognosis in patients with spinal GCTB, and the radiomics analysis based on preoperative CT provides a feasible method for the evaluation of these two biomarkers, which may aid in choosing better management strategies.

The Feasibility of Combining ADC Value With Texture Analysis of T2WI, DWI and CE-T1WI to Preoperatively Predict the Expression Levels of Ki-67 and p53 of Endometrial Carcinoma

PURPOSE

To evaluate the feasibility of apparent diffusion coefficient (ADC) value combined with texture analysis (TA) in preoperatively predicting the expression levels of Ki-67 and p53 in endometrial carcinoma (EC) patients.

METHODS

Clinical, pathological and MRI findings of 110 EC patients were analyzed retrospectively. The expression levels of Ki-67 and p53 in EC tissues were detected by immunohistochemistry. ADC value was calculated, and three-dimensional (3D) texture features were measured on T₂-weighted images (T₂WI), diffusion-weighted images (DWI), and contrast-enhanced T₁-weighted images (CE-T₁WI). The univariate and multivariate logistic regression and cross-validations were used for the selection of texture features. The receiver operating characteristic (ROC) curve was performed to estimate the diagnostic efficiency of prediction model by the area under the curve (AUC) in the training and validation cohorts.

RESULTS

Significant differences of the ADC values were found in predicting Ki-67 and p53 (P=0.039, P=0.007). The AUC of the ADC value in predicting the expression levels of Ki-67 and p53 were 0.698, 0.853 and 0.626, 0.702 in the training and validation cohorts. The AUC of the TA model based on T₂WI, DWI, CE-T₁WI, and ADC value combined with T₂WI + DWI + CE-T₁WI in the training and validation cohorts for predicting the expression of Ki-67 were 0.741, 0.765, 0.733, 0.922 and 0.688, 0.691, 0.651, 0.938, respectively, and for predicting the expression of p53 were 0.763, 0.805, 0.781, 0.901 and 0.796, 0.713, 0.657, 0.922, respectively.

CONCLUSION

ADC values combined with TA are beneficial for predicting the expression levels of Ki-67 and p53 in EC patients before surgery, and they provide higher auxiliary diagnostic values for clinical application.

Apparent Diffusion Coefficient Histogram Analysis for the Preoperative Evaluation of Ki-67 Expression in Pituitary Macroadenoma

PURPOSE

To explore the value of an apparent diffusion coefficient (ADC) histogram in predicting the Ki-67 proliferation index in pituitary macroadenomas.

MATERIAL AND METHODS

This retrospective study analyzed the pathological and imaging data of 102 patients with pathologically confirmed pituitary macroadenoma. Immunohistochemistry staining was used to assess Ki-67 expression in tumor tissue samples, and a high Ki-67 labeling index was defined as 3%. The ADC images of the maximum slice of tumors were selected and the region of interest (ROI) of each slice was delineated using the MaZda software (version 4.7, Technical University of Lodz, Institute of Electronics, Łódź, Poland) and analyzed by ADC histogram. Histogram characteristic parameters were compared between the high Ki-67 group (n = 42) and the low Ki-67 group (n = 60). The important parameters were further analyzed by receiver operating characteristic (ROC).

RESULTS

The mean value, and the 1st, 10th, 50th, 90th, and 99th percentiles were found to be negatively correlated with Ki-67 expression (all P < 0.05), with correlation coefficients of -0.292, -0.352, -0.344, -0.289, -0.253 and -0.267, respectively. The mean ADC and the 1st, 10th, 50th, 90th, and 99th quantiles extracted from the histogram were significantly lower in the high Ki-67 group than in the low Ki-67 group (all P < 0.05). The area under the ROC curve was 0.699-0.720; however, there were no significant between-group differences in variance, skewness and kurtosis (all P > 0.05).

CONCLUSION

An ADC histogram can be a reliable tool to predict the Ki-67 proliferation status in patients with pituitary macroadenomas.

The Impact of Entrepreneurial Optimism and Labor Law on Business Performance of New Ventures

The purpose is to study the internal relationship between entrepreneurial optimism and business performance of new ventures, and the impact of entrepreneurial optimism on the business performance of new ventures. Based on the literature review, the hypotheses that entrepreneurial optimism has a positive impact on the business performance of new ventures and that labor law plays a mediating role in the impact are put forward. Then, the questionnaire is designed according to the maturity scale, and 200 questionnaires are collected. Finally, the descriptive statistical analysis, reliability analysis, exploratory factor analysis, confirmatory factor analysis, correlation analysis, and regression analysis of the theoretical model and hypothesis are carried out by using the statistical analysis software spsss22.0. The results show that each dimension of entrepreneurial optimism has a significant positive impact on the business performance of new ventures, and labor law plays a mediating role between them. This study provides a new idea for the establishment of the performance impact mechanism of new ventures and helps new entrepreneurs realize the importance of maintaining an optimistic attitude, improving the business performance of new ventures.

Apparent Diffusion Coefficient to Evaluate Adult Intracranial Ependymomas: Relationship to Ki-67 Proliferation Index

BACKGROUND AND PURPOSE

There are important differences in the treatment and prognosis of adult intracranial low-grade ependymomas (grade II) versus anaplastic ependymomas (grade III). We evaluated the value of the apparent diffusion coefficient (ADC) for differentiating these two tumors and further investigated the relationship between ADC values and the Ki-67 proliferation index.

METHODS

Clinical and preoperative magnetic resonance imaging data of 35 cases of adult intracranial ependymomas were retrospectively analyzed, including 20 low-grade ependymomas and 15 anaplastic ependymomas. The minimum ADC (ADCmin), average ADC (ADCmean), and normalized ADC (nADC) were compared between the two groups. Receiver operating characteristic curves were drawn to evaluate the differentiating accuracy of ADC values. The Ki-67 proliferation index of the solid tumor components was also measured to explore its relationship with ADC values.

RESULTS

The ADCmin (.89 ± .17 vs. .66 ± .09 × 10^-3  mm² /second), ADCmean (.98 ± .21 vs. .72 ± .11 × 10^-3 mm² /second), and nADC (1.38 ± .31 vs. 1.02 ± .18 × 10^-3  mm² /second) were significantly higher in adult intracranial low-grade ependymomas than anaplastic ependymomas cases (all P < .05). ADCmean best distinguished the two groups, with an area under the curve value of .900. Using .716 × 10^-3  mm² /second as the optimal threshold, the sensitivity, specificity, accuracy, positive predictive value, and negative predictive value of the two groups were 66.7%, 100%, 85.7%, 100%, and 80%, respectively. ADCmin (r = -.490), ADCmean (r = -.449), and nADC (r = -.425) showed significant negative correlations with the Ki-67 proliferation index (all P < .05).

CONCLUSIONS

ADC values can differentiate adult intracranial low-grade ependymomas and anaplastic ependymomas, which could improve the preoperative diagnostic accuracy of these two tumors and guide their treatment.

Comparative Analysis of Amide Proton Transfer MRI and Diffusion-Weighted Imaging in Assessing p53 and Ki-67 Expression of Rectal Adenocarcinoma

BACKGROUND

The evaluation of prognostic factors in rectal carcinoma patients has important clinical significance. P53 status and the Ki-67 index have served as prognostic factors in rectal carcinoma. Amide proton transfer (APT) imaging has shown great potential in tumor diagnosis. However, few studies reported the value of APT imaging in evaluating p53 and Ki-67 status of rectal carcinoma.

PURPOSE

To investigate the feasibility of amide proton transfer MRI in assessing p53 and Ki-67 expression of rectal adenocarcinoma, and compare it with conventional diffusion-weighted imaging (DWI).

STUDY TYPE

Retrospective.

POPULATION

Forty-three patients with rectal adenocarcinoma (age: 34-85 years).

FIELD STRENGTH/SEQUENCE

3T/APT imaging using a 3D turbo spin echo (TSE)-Dixon pulse sequence with chemical shift-selective fat suppression, 2D DWI, and 2D T₂ -weighted TSE.

ASSESSMENT

Mean tumor APT signal intensity (SI_mean ) and apparent diffusion coefficient (ADC_mean ) were measured. Traditional tumor pathological analysis included WHO grades, pT (pathologic tumor) stages, and pN (pathologic node) stages. Expression levels of p53 and Ki-67 were determined by immunohistochemical assay.

STATISTICAL TESTS

One-way analysis of variance (ANOVA); Student's t-test; Spearman's correlation coefficient; receiver operating characteristic (ROC) curve analysis.

RESULTS

High-grade tumors, more advanced stage tumors, and tumors with lymph node involvement had higher APT SI_mean values: high grade (n = 15) vs. low-grade (n = 28), P < 0.001; pT2 (n = 10) vs. pT3 (n = 20) vs. pT4 (N = 13), P = 0.021; pN0 (n = 24) vs. pN1-2 (n = 19), P = 0.019. ADC_mean differences were found in tumors with different pT stage: pT2 (n = 10) vs. pT3 (n = 20) vs. pT4 (N = 13), P = 0.013, but not in tumors with different histologic grade: high grade (n = 15) vs. low-grade (n = 28), P = 0.3536; or pN stage: pN0 (n = 24) vs. pN1-2 (n = 19), P = 0.624. Tumor with p53 positive status had higher APT SI_mean than tumor with negative p53 status (2.363 ± 0.457 vs. 2.0150 ± 0.3552, P = 0.014). There was no difference in ADC_mean with p53 status (1.058 ± 0.1163 10^-3  mm² /s vs. 1.055 ± 0.128 10^-3  mm² /s, P = 0.935). APT SI_mean and ADC_mean were significantly different in tumors with low and high Ki-67 status (1.7882 ± 0.11386 vs. 2.3975 ± 0.41586, P < 0.001; 1.1741 ± 0.093 10^-3  mm² /s vs. 1.0157 ± 0.10459 10^-3  mm² /s, P < 0.001, respectively). APT SI_mean exhibited a positive correlation with p53 labeling index and Ki-67 labeling index (r = 0.3741, P = 0.0135; r = 0.7048; P < 0.001, respectively). ADC_mean showed no correlation with p53 labeling index, but a negative correlation with Ki-67 labeling index (r = -0.5543, P < 0.0001). ROC curves demonstrated that APT SI_mean had significantly higher diagnostic ability for differentiation of high Ki-67 expression of rectal adenocarcinoma than ADC_mean (81.2% vs. 78.12%, 90.91% vs. 63.64; P < 0.001 vs. P = 0.017), while no difference was found in predicting p53 status (92.86% vs. 71.4%, 53.33% vs. 66.7%; P < 0.001 vs. P = 0.0471).

DATA CONCLUSION

APT SI_mean was related to p53 and Ki-67 expression levels in rectal adenocarcinoma. APT imaging may serve as a noninvasive biomarker for assessing genetic prognostic factors of rectal adenocarcinoma.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.