Preliminary exploration of amide proton transfer weighted imaging in differentiation between benign and malignant bone tumors.

Purpose: To explore the value of 3D amide proton transfer weighted imaging (APTWI) in the differential diagnosis between benign and malignant bone tumors, and to compare the diagnostic performance of APTWI with traditional diffusion-weighted imaging (DWI). Materials and methods: Patients with bone tumors located in the pelvis or lower limbs confirmed by puncture or surgical pathology were collected from January 2021 to July 2023 in the First Affiliated Hospital of Zhengzhou University. All patients underwent APTWI and DWI examinations. The magnetization transfer ratio with asymmetric analysis at the frequency offset of 3.5 ppm [MTRasym(3.5 ppm)] derived by APTWI and the apparent diffusion coefficient (ADC) derived by DWI for the tumors were measured. The Kolmogorou-Smirnou and Levene normality test was used to confirm the normal distribution of imaging parameters; and the independent sample t test was used to compare the differences in MTRasym(3.5 ppm) and ADC between benign and malignant bone tumors. In addition, the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of different imaging parameters in differentiation between benign and malignant bone tumors. P<0.05 means statistically significant. Results: Among 85 bone tumor patients, 33 were benign and 52 were malignant. The MTRasym(3.5 ppm) values of malignant bone tumors were significantly higher than those of benign tumors, while the ADC values were significantly lower in benign tumors. ROC analysis shows that MTRasym(3.5 ppm) and ADC values perform well in the differential diagnosis of benign and malignant bone tumors, with the area under the ROC curve (AUC) of 0.798 and 0.780, respectively. Combination of MTRasym(3.5 ppm) and ADC values can further improve the diagnostic performance with the AUC of 0.849 (sensitivity = 84.9% and specificity = 73.1%). Conclusion: MTRasym(3.5 ppm) of malignant bone tumors was significantly higher than that of benign bone tumors, reflecting the abnormal increase of protein synthesis in malignant tumors. APTWI combined with DWI can achieve a high diagnostic efficacy in differentiation between benign and malignant bone tumors.

Spiral time-of-flight magnetic resonance angiography for intracranial vascular imaging: performance compared to conventional Cartesian angiogram.

Background: Computed tomography angiography (CTA) and digital subtraction angiography (DSA) usually raise the risk of potential malignancies with cumulative radiation doses. Current time-of-flight magnetic resonance angiography (TOF-MRA) (dubbed as cTOF), which is based on Cartesian sampling mode, may show limited diagnostic conspicuity at sinuous or branching regions. It is also prone to relatively high false positive diagnoses and undesirable display of distal intracranial vessels. This study aimed to use spiral TOF-MRA (sTOF) as a noninvasive alternative to explore possible improvement, such that the application of magnetic resonance angiography (MRA) can be extended to facilitate clinical examination or cerebrovascular disease diagnosis and follow-up studies. Methods: Initially, 37 patients with symptoms of dizziness or transient ischemic attack were consecutively recruited for suspected intracranial vascular disease examination from Zhongshan Hospital of Xiamen University between July 2020 and April 2021 in this cross-sectional prospective study. After excluding 1 patient with severe scanning artifacts, 1 patient whose scanning scope did not meet the requirement, and 1 patient with confounding tumor lesions, a total of 34 participants were included according to the inclusion and exclusion criteria. Each participant underwent intracranial vascular imaging with both sTOF and cTOF sequences on a 3.0 T MR scanner with a conventional head-neck coil of 16 channels. Contrast CTA or DSA was also performed for 15 patients showing pathology. Qualitative comparisons in terms of image quality and diagnostic efficacy ratings, quantitative comparisons in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), vessel length, and sharpness were evaluated. Pair-wise Wilcoxon test was performed to evaluate the imaging quality derived from cTOF and sTOF acquisitions and weighted Cohen's Kappa was conducted to assess the rating consistency between different physicians. Results: Compared to cTOF, sTOF showed better performance with fewer artifacts. It can effectively alleviate false positives of normal vessels being misdiagnosed as aneurysm or stenosis. Improved conspicuity was observed in cerebral distal regions with more clearly identifiable vasculature at finer scales. Quantitative comparisons in selected regions revealed significant improvement of sTOF in SNR (P<0.01 or P<0.001), CNR (P<0.001), vessel length (P<0.001), and sharpness (P<0.001) as compared to cTOF. Besides, sTOF can depict details of M1 and M2 segments of middle cerebral artery (MCA) at metallic implant region, showing its resistance to magnetic susceptibility. Conclusions: The sTOF shows higher imaging quality and lesion detectability with reduced artifacts and false positives, representing a potentially feasible surrogate in intracranial vascular imaging for future clinic routines.

Early prediction of pathological response to neoadjuvant chemotherapy of breast tumors: a comparative study using amide proton transfer-weighted, diffusion weighted and dynamic contrast enhanced MRI.

Objective: To examine amide proton transfer-weighted (APTw) combined with diffusion weighed (DWI) and dynamic contrast enhanced (DCE) MRI for early prediction of pathological response to neoadjuvant chemotherapy in invasive breast cancer. Materials: In this prospective study, 50 female breast cancer patients (49.58 ± 10.62 years old) administered neoadjuvant chemotherapy (NAC) were enrolled with MRI carried out both before NAC (T0) and at the end of the second cycle of NAC (T1). The patients were divided into 2 groups based on tumor response according to the Miller-Payne Grading (MPG) system. Group 1 included patients with a greater degree of decrease in major histologic responder (MHR, Miller-Payne G4-5), while group 2 included non-MHR cases (Miller-Payne G1-3). Traditional imaging protocols (T1 weighted, T2 weighted, diffusion weighted, and DCE-MRI) and APTw imaging were scanned for each subject before and after treatment. APTw value (APTw0 and APTw1), Dmax (maximum diameter, Dmax0 and Dmax1), V (3D tumor volume, V0 and V1), and ADC (apparent diffusion coefficient, ADC0 and ADC1) before and after treatment, as well as changes between the two times points (ΔAPT, ΔDmax, ΔV, ΔADC) for breast tumors were compared between the two groups. Results: APT0 and APT1 values significantly differed between the two groups (p = 0.034 and 0.01). ΔAPTw values were significantly lower in non-MHR tumors compared with MHR tumors (p = 0.015). ΔDmax values were significantly higher in MHR tumors compared with non-MHR tumors (p = 0.005). ADC0 and ADC1 values were significantly higher in MHR tumors than in non-MHR tumors (p = 0.038 and 0.035). AUC (Dmax+DWI + APTw) = AUC (Dmax+APTw) > AUC (APTw) > AUC (Dmax+DWI) > AUC (Dmax). Conclusion: APTw imaging along with change of tumor size showed a significant potential in early prediction of MHR for NAC treatment in breast cancer, which might allow timely regimen refinement before definitive surgical treatment.

T1 Mapping and Amide Proton Transfer Weighted Imaging for Predicting Lymph Node Metastasis in Patients with Rectal Cancer.

BACKGROUND: Accurate preoperative judgment of lymph node (LN) metastasis is a critical step in creating a treatment strategy and evaluating prognosis in rectal cancer (RC) patients. OBJECTIVE: This study aimed to explore the value of T1 mapping and amide proton transfer weighted (APTw) imaging in predicting LN metastasis in patients with rectal cancer. METHODS: In a retrospective study, twenty-three patients with pathologically confirmed rectal adenocarcinoma who underwent MRI and surgery from August 2019 to August 2021 were selected. Then, 3.0T/MR sequences included conventional sequences (T1WI, T2WI, and DWI), APTw imaging, and T1 mapping. Patients were divided into LN metastasis (group A) and non-LN metastasis groups (group B). The intra-group correlation coefficient (ICC) was used to test the inter-observer consistency. Mann-Whitney U test was used to compare the differences between the two groups. Spearman correlation analysis was performed to evaluate the correlation between T1 and APT values. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter and their combination. The difference between AUCs was compared using the DeLong test. RESULTS: The APT value in patients with LN metastasis was significantly higher than in those without LN metastasis group (P=0.020). Also, similar results were observed for the T1 values (P=0.001). The area under the ROC curve of the APT value in the prediction of LN metastasis was 0.794; when the cutoff value was 1.73%, the sensitivity and specificity were 71.4% and 88.9%, respectively. The area under the ROC curve of the T1 value was 0.913; when the cutoff value was 1367.36 ms, the sensitivity and specificity were 78.6% and 100.0%, respectively. The area under the ROC curve of T1+APT was 0.929, with a sensitivity of 78.6% and specificity of 100.0%. CONCLUSION: APT and T1 values show great diagnostic efficiency in predicting LN metastasis in rectal cancer.

T1 mapping in evaluation of clinicopathologic factors for rectal adenocarcinoma.

OBJECTIVE: T1 mapping has been increasingly applied in the study of tumor. The purpose of this study was to evaluate the value of T1 mapping in evaluating clinicopathologic factors for rectal adenocarcinoma. MATERIALS AND METHODS: Eighty-six patients with rectal adenocarcinoma confirmed by surgical pathology who underwent preoperative pelvic MRI were retrospectively analyzed. High-resolution T2-weighted imaging (T2WI), T1 mapping, and diffusion-weighted imaging (DWI) were performed. T1 and apparent diffusion coefficient (ADC) parameters were compared among different associated tumor markers, tumor grades, stages, and structure invasion statuses. A receiver operating characteristic (ROC) analysis was estimated. RESULTS: T1 value showed significant difference between high- and low-grade tumors ([1531.5 ± 84.7 ms] vs. [1437.1 ± 80.3 ms], P < 0.001). T1 value was significant higher in positive than in negative perineural invasion ([1495.7 ± 89.2 ms] vs. [1449.4 ± 88.8 ms], P < 0.05). No significant difference of T1 or ADC was observed in different CEA, CA199, T stage, N stage, lymphovascular invasions, extramural vascular invasion (EMVI), and circumferential resection margin (CRM) (P > 0.05). The AUC under ROC curve of T1 value were 0.796 in distinguishing high- from low-grade rectal adenocarcinoma. The AUC of T1 value in distinguishing perineural invasion was 0.637. CONCLUSION: T1 value was helpful in assessing pathologic grade and perineural invasion correlated with rectal cancer.

Amide proton transfer weighted combined with diffusion kurtosis imaging for predicting lymph node metastasis in cervical cancer.

OBJECTIVE: To investigate the value of amide proton transfer weighted (APTw) combined with diffusion kurtosis imaging (DKI) in quantitative prediction of lymph node metastasis (LNM) in cervical carcinoma (CC). METHODS: Data of 19 LNM(+) and 50 LNM(-) patients with CC were retrospectively analyzed. 3.0 T MRI scan was performed before the operation, including APTw and DKI. After post-processing, quantitative magnetization transfer ratio asymmetric at 3.5 ppm [MTRasym (3.5 ppm)], mean kurtosis (MK), and mean diffusivity (MD) maps were obtained. The MTRasym(3.5 ppm), MK, and MD values were respectively measured by two observers, and intra-class correlation coefficients (ICC) were used to test the consistency of the results. The independent samples t-test or Mann-Whitney U test was used to compare the differences in the values of each parameter. The ROC curve was used to analyze the predictive performance of parameters with significant differences and their combination parameter. RESULTS: The two observers had good agreement in the measurement of each data (ICC > 0.75). The MTRasym(3.5 ppm) and MK values of the LNM(+) group(3.260 ± 0.538% and 0.531 ± 0.202) were higher than those of the LNM(-) group(2.698 ± 0.597% and 0.401 ± 0.148) (P < 0.05), while there was no significant difference in MD values between the two groups(P > 0.05). The area under the curves (AUCs) of MTRasym(3.5 ppm), MK value, and MTRasym(3.5 ppm) + MK value were 0.763, 0.716, and 0.813, respectively, when predicting LNM status of CC. CONCLUSION: APTw and DKI can quantitatively predict LNM status of CC, which is of importance in clinical diagnosis and treatment.

Added-value of 3D amide proton transfer MRI in assessing prognostic factors of cervical cancer: a comparative study with multiple model diffusion-weighted imaging.

Background: Amide proton transfer (APT) imaging has been gradually applied to cervical cancer, yet the relationships between APT and multiple model diffusion-weighted imaging (DWI) have yet to be investigated. This study attempted to evaluate the added value of 3-dimensional (3D) APT imaging to multiple model DWI for assessing prognostic factors of cervical cancer. Methods: This prospective diagnostic study was conducted in The First Affiliated Hospital of Zhengzhou University. A total of 88 consecutive patients with cervical cancer underwent APT imaging and DWI with 11 b-values (0-2,000 s/mm2). The apparent diffusion coefficient (ADC), pure molecular diffusion (D), perfusion fraction (f), pseudo-diffusion (D*), mean kurtosis (MK), and mean diffusivity (MD) were calculated based on mono-exponential, bi-exponential, and kurtosis models. The mean, minimum, and maximum values of APT signal intensity (APT SI) and DWI-derived metrics were compared based on tumor stages, subtypes, grades, and lymphovascular space invasion status by Student's t-test or Mann-Whitney U test. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the parameters. Results: APT SImax, APT SImin, MKmean, and MKmax showed significant differences between adenocarcinoma (AC) and squamous cell carcinoma (SCC) (all P<0.05). APT SImean, APT SImax, and MKmax were higher and ADCmin, Dmean, Dmin, and MDmin were lower in the high-grade tumor than in low-grade tumor (all P<0.05). For distinguishing lymphovascular space invasion, only MKmean showed significant difference (P=0.010). APT SImax [odds ratio (OR) =2.347, P=0.029], APT SImin (OR =0.352; P=0.024), and MKmean (OR =6.523; P=0.001) were the independent predictors for tumor subtype, and APT SImax (OR =2.885; P=0.044), MDmin (OR =0.155, P=0.012) were the independent predictors for histological grade of cervical cancer. When APT SImin and APT SImax was combined with MKmean and MKmax, the diagnostic performance was significantly improved for differentiating AC and AC [area under the curve (AUC): 0.908, sensitivity: 87.5%; specificity: 83.3%; P<0.001]. The combination of APT SImean, APT SImax, ADCmin, MKmax, and MDmin demonstrated the highest diagnostic performance for predicting tumor grade (AUC: 0.903, sensitivity: 78.6%; specificity: 88.9%; P<0.001). Conclusions: Addition of APT to DWI may improve the ability to noninvasively predict poor prognostic factors of cervical cancer.

Multimodal MRI for Estimating Her-2 Gene Expression in Endometrial Cancer.

PURPOSE: To assess the value of multimodal MRI, including amide proton transfer-weighted imaging (APT), diffusion kurtosis imaging (DKI), and T2 mapping sequences for estimating human epidermal growth factor receptor-2 (Her-2) expression in patients with endometrial cancer (EC). METHODS: A total of 54 patients with EC who underwent multimodal pelvic MRI followed by biopsy were retrospectively selected and divided into the Her-2 positive (n = 24) and Her-2 negative (n = 30) groups. Her-2 expression was confirmed by immunohistochemistry (IHC). Two observers measured APT, mean kurtosis (MK), mean diffusivity (MD), and T2 values for EC lesions. RESULTS: The Her-2 (+) group showed higher APT values and lower MD and T2 values than the Her-2 (-) group (all p < 0.05); there was no significant difference in MK values (p > 0.05). The area under the receiver operating characteristic curve (AUC) of APT, MD, T2, APT + T2, APT + MD, T2 + MD, and APT + MD + T2 models to identify the two groups of cases were 0.824, 0.695, 0.721, 0.824, 0.858, 0.782, and 0.860, respectively, and the diagnostic efficacy after combined APT + MD + T2 value was significantly higher than those of MD and T2 values individually (p = 0.018, 0.028); the diagnostic efficacy of the combination of APT + T2 values was significantly higher than that of T2 values separately (p = 0.028). Weak negative correlations were observed between APT and T2 values (r = -0.365, p = 0.007), moderate negative correlations between APT and MD values (r = -0.560, p < 0.001), and weak positive correlations between MD and T2 values (r = 0.336, p = 0.013). The APT values were independent predictors for assessing Her-2 expression in EC patients. CONCLUSION: The APT, DKI, and T2 mapping sequences can be used to preoperatively assess the Her-2 expression in EC, which can contribute to more precise treatment for clinical preoperative.

Changes in aspartate metabolism in the medial-prefrontal cortex of nicotine addicts based on J-edited magnetic resonance spectroscopy.

This study aims to explore the changes of the aspartate (Asp) level in the medial-prefrontal cortex (mPFC) of subjects with nicotine addiction (nicotine addicts [NAs]) using the J-edited 1 H MR spectroscopy (MRS), which may provide a positive imaging evidence for intervention of NA. From March to August 2022, 45 males aged 40-60 years old were recruited from Henan Province, including 21 in NA and 24 in nonsmoker groups. All subjects underwent routine magnetic resonance imaging (MRI) and J-edited MRS scans on a 3.0 T MRI scanner. The Asp level in mPFC was quantified with reference to the total creatine (Asp/Cr) and water (Aspwater-corr , with correction of the brain tissue composition) signals, respectively. Two-tailed independent samples t-test was used to analyze the differences in levels of Asp and other coquantified metabolites (including total N-acetylaspartate [tNAA], total cholinine [tCho], total creatine [tCr], and myo-Inositol [mI]) between the two groups. Finally, the correlations of the Asp level with clinical characteristic assessment scales were performed using the Spearman criteria. Compared with the control group (n = 22), NAs (n = 18) had higher levels of Asp (Asp/Cr: p = .005; Aspwater-corr : p = .004) in the mPFC, and the level of Asp was positively correlated with the daily smoking amount (Asp/Cr: p < .001; Aspwater-corr : p = .004). No significant correlation was found between the level of Asp and the years of nicotine use, Fagerstrom Nicotine Dependence (FTND), Russell Reason for Smoking Questionnaire (RRSQ), or Barratt Impulsivity Scale (BIS-11) score. The elevated Asp level was observed in mPFC of NAs in contrast to nonsmokers, and the Asp level was positively correlated with the amount of daily smoking, which suggests that nicotine addiction may result in elevated Asp metabolism in the human brain.

Quantitative Analysis of Whole-Body MRI for Accessing the Degree of Diffuse Infiltration Patterns and Identifying High Risk Cases of Newly Diagnosed Multiple Myeloma.

BACKGROUND: Accurate identification of high-risk multiple myeloma (HRMM) is important for prognostication. The degree of diffuse infiltration patterns on magnetic resonance imaging (MRI) is associated with patient prognosis in multiple myeloma. However, objective indexes to determine the degree of diffuse infiltration patterns are unavailable. PURPOSE: To investigate whether qualitative and quantitative evaluations of diffuse infiltration patterns on MRI could identify HRMM. STUDY TYPE: Retrospective. SUBJECTS: Totally, 180 patients (79 HRMM and 101 standard-risk MM) were assessed. The presence of del(17p), t(4;14), t(14;16), t(14;20), gain 1q, and/or p53 mutations was considered to indicate HRMM. FIELD STRENGTH/SEQUENCE: 3.0 T/diffusion-weighted whole-body imaging with background body signal suppression (DWIBS), modified Dixon chemical-shift imaging Quant (mDIXON Quant), and short TI inversion recovery (STIR). ASSESSMENT: Qualitative analysis involved assessing the degree of diffuse marrow infiltration (mild, moderate, or severe), and quantitative analysis involved evaluating apparent diffusion coefficient (ADC), fat fraction (FF), and T2* values. Clinical data such as sex, age, hemoglobin, serum albumin, serum calcium, serum creatinine, serum lactate dehydrogenase, ß2-microglobulin, and bone marrow plasma cells (BMPCs) were also included. STATISTICAL TESTS: Univariate and multivariate analyses, receiver operating characteristic (ROC) curve. P < 0.05 was considered statistically significant. RESULTS: The high-risk group had significantly higher ADC and T2* and lower FF compared with the standard-risk group. Multivariate analysis indicated BMPCs as a significant independent risk factor for HRMM (odds ratio (OR) = 1.019, 95% CI 1.004-1.033), while FF was a significant independent protective factor associated with HRMM (OR = 0.972, 95% CI 0.946-0.999). The combination of BMPCs and FF achieved the highest areas under the curve (AUC) of 0.732, with sensitivity and specificity of 70.9% and 68.3%, respectively. DATA CONCLUSION: Compared with qualitative analysis, FF value was independently associated with HRMM. The quantitative features of diffuse marrow infiltration on MRI scans are more effective in detecting HRMM. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Amide proton transfer-weighted magnetic resonance imaging for the differentiation of parotid gland tumors.

Purpose: To assess the usefulness of amide proton transfer-weighted (APTw) imaging in the differentiation of parotid gland tumors. Materials and methods: Patients with parotid gland tumors who underwent APTw imaging were retrospectively enrolled and divided into groups according to pathology. Two radiologists evaluated the APTw image quality independently, and APTw images with quality score ≥3 were enrolled. The maximum and average values of APTw imaging for tumor lesions (APTmax and APTmean) were measured. The differences in APTmax and APTmean were compared between malignant tumors (MTs) and benign tumors (BTs), as well as between MTs and pleomorphic adenomas (PAs) and between MTs and Warthin tumors (WTs). Independent-samples t-test, Kruskal-Wallis H test, and receiver operating characteristic (ROC) curve analyses were used for statistical analysis. Results: Seventy-three patients were included for image quality evaluation. In this study, 32/73 and 29/73 parotid tumors were scored as 4 and 3, respectively. After excluding lesions with quality score ≤2 (12/73), the APTmean and APTmax of MTs were 4.15% ± 1.33% and 7.43% ± 1.61%, higher than those of BTs 2.74% ± 1.04% and 5.25% ± 1.54%, respectively (p < 0.05). The areas under the ROC curve (AUCs) of the APTmean and APTmax for differentiation between MTs and BTs were 0.819 and 0.821, respectively. MTs indicated significantly higher APTmean and APTmax values than those of PAs (p < 0.05) and WTs (p < 0.05). The AUCs of the APTmean and APTmax for differentiation between MTs and PAs were 0.830 and 0.815 and between MTs and WTs were 0.847 and 0.920, respectively. Conclusion: Most APTw images for parotid tumors had acceptable image quality for APTw value evaluation. Both APTmax and APTmean can be used to differentiate MTs from BTs and to differentiate MTs from subtype parotid gland tumors.

T1 mapping and multimodel diffusion-weighted imaging in the assessment of cervical cancer: a preliminary study.

OBJECTIVE: To evaluate the clinical feasibility of T1 mapping and multimodel diffusion-weighted imaging (DWI) for assessing the histological type, grade, and lymphovascular space invasion (LVSI) of cervical cancer. METHODS: Eighty patients with cervical cancer and 43 patients with a normal cervix underwent T1 mapping and DWI with 11 b-values (0-2000 s/mm2). Monoexponential, biexponential, and kurtosis models were fitted to calculate the apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion (D*), perfusion fraction (f), mean diffusivity (MD), and mean kurtosis (MK). Native T1 and DWI-derived parameters (ADCmean, ADCmin, Dmean, Dmin, D*, f, MDmean, MDmin, MKmean, and MKmax) were compared based on histological type, grade, and LVSI status. RESULTS: Native T1 and DWI-derived parameters differed significantly between cervical cancer and normal cervix (all p < 0.05), except D* (p = 0.637). Native T1 and MKmean varied significantly between squamous cell carcinoma (SCC) and adenocarcinoma (both p < 0.05). ADCmin, Dmin, and MDmin were significantly lower while MKmax was significantly higher in the high-grade SCC group than in the low-grade SCC group (all p < 0.05). LVSI-positive SCC had a significantly higher MKmean than LVSI-negative SCC (p < 0.05). CONCLUSION: Both T1 mapping and multimodel DWI can effectively differentiate cervical cancer from a normal cervix and cervical adenocarcinoma from SCC. Furthermore, multimodel DWI may provide quantitative metrics for non-invasively predicting histological grade and LVSI status in SCC patients. ADVANCES IN KNOWLEDGE: Combined use of T1 mapping and multimodel DWI may provide more comprehensive information for non-invasive pre-operative evaluation of cervical cancer.

Improved differentiation between stage I-II endometrial carcinoma and endometrial polyp with combination of APTw and IVIM MR imaging.

PURPOSE: To assess the value of amide proton transfer weighted (APTw) combined with intra-voxel incoherent motion (IVIM) imaging in differential diagnosis of stage I-II endometrial carcinoma (EC) and endometrial polyp (EP). METHODS: A total of 53 female patients (37 cases with EC and 16 cases with EP) confirmed by surgical resection or biopsy from June 2019 to Jan. 2022 were retrospectively reviewed. All patients underwent 3.0 T magnetic resonance imaging (MRI) examination including diffusion weighted imaging (DWI), APTw and IVIM scans. The pure diffusion coefficient (D), pseudo-diffusion coefficient (D⁎), perfusion fraction (f), apparent diffusion coefficient (ADC) and APT values were independently measured by two observers. Intra-class correlation coefficients (ICC) were used to test the consistency of measurements by the two observers. Mann-Whitney U test was performed to analyze the difference of each parameter between EC and EP groups. Receiver operator characteristic (ROC) analysis was performed, and the Delong test was used for ROC curve comparison. Pearson's correlation analysis was used to assess the correlation between APTw and IVIM parameters. RESULTS: There was no significant difference in clinical manifestations between the two groups (P > 0.05). APT and D⁎ values of the EC group were significantly higher than those of the EP group [APT: 2.64 ± 0.50% vs. 2.05 ± 0.58%; and D⁎: (54.06 ± 36.06) × 10-3 mm2/s vs. (30.54 ± 16.67) × 10-3 mm2/s]. D, f and ADC values of EC group were significantly lower than those of EP group [D: 0.62(0.53,0.76) × 10-3 mm2/s vs. (1.45 ± 0.48) × 10-3 mm2/s; f: 22.18 ± 8.08% vs. 30.80 ± 8.92%; and ADC: (0.88 ± 0.16) × 10-3 mm2/s vs. (1.57 ± 0.43) × 10-3 mm2/s]. The area under ROC curves were observed as: AUC (IVIM+APT) > AUC (D) > AUC (ADC) > AUC (APT) > AUC (f) > AUC (D⁎). Delong test suggested statistical significance between AUC by APT and D, D and D⁎, D and f, D⁎ and ADC, APT and com(IVIM+APT), D⁎ and com(IVIM+APT), as well as f and com(IVIM+APT). No significant correlation between the APT and IVIM parameters was observed in either EC or EP group. CONCLUSION: Both APT and IVIM parameters showed statistical differences between EC and EP. With combination of APT and IVIM parameters, the diagnostic accuracy between EC and EP can be significantly improved.

APTw combined with mDixon-Quant imaging to distinguish the differentiation degree of cervical squamous carcinoma.

Background: To investigate the value of amide proton transfer weighted (APTw) imaging combined with modified Dixon fat quantification (mDixon-Quant) imaging in determining the degree of differentiation of cervical squamous carcinoma (CSC) against histopathologic. Methods: Magnetic resonance imaging (MRI) data were collected from 52 CSC patients. According to histopathologic results, patients were divided into the poorly differentiated group (37 cases) and the well/moderately differentiated group (15 cases). The APTw value by APTw imaging and the fat fraction (FF) and transverse relaxation rate R 2 * values by mDixon-Quant were independently measured by two radiologists. Intra-class correlation coefficients (ICCs) were used to test the consistency of APTw, FF, and R 2 * values measured by the two observers. The Mann-Whitney U test was used to analyze the difference in each parameter between the two groups. Logistic regression analysis was used to assess the association between the degree of differentiation on histopathology and imaging parameters by APTw and mDixon Quant. The ROC curve was used to evaluate the diagnostic efficacy of various parameters and their combination in distinguishing the degree of CSC differentiation on histopathology. The DeLong test was used to access the differences among the area under the ROC curves (AUCs). The Pearson correlation coefficient was used to evaluate the correlation between APTw and mDixon-Quant imaging parameters. Results: The APTw means were 2.95 ± 0.78% and 2.05 (1.85, 2.65)% in the poorly and well/moderately differentiated groups, respectively. The R 2 * values were 26.62 (21.99, 33.31)/s and 22.93 ± 6.09/s in the poorly and well/moderately differentiated groups, respectively (P < 0.05). The AUCs of APTw, R 2 * , and their combination were 0.762, 0.686, and 0.843, respectively. The Delong test suggested statistical significance between R 2 * and the combination of APTw and R 2 * . R 2 * values showed a significant correlation with APTw values in the poorly differentiated group. Conclusions: APTw combined with mDixon-Quant can be used to efficiently distinguish the differention degrees of CSC diagnosed on histopathology.

The combined application of amide proton transfer imaging and diffusion kurtosis imaging for differentiating stage Ia endometrial carcinoma and endometrial polyps.

OBJECTIVE: This study aims to explore the diagnostic performance of amide proton transfer (APT) imaging combined with diffusion kurtosis imaging (DKI) in differentiating stage Ia endometrial carcinoma (EC) and endometrial polyps (EP). METHODS: All patients were scanned with APT and DKI sequences with 3.0 T MRI before surgery. The MRI data of 32 patients with histopathologically confirmed stage Ia EC and 17 patients with EP were retrospectively analyzed. Amide proton transfer, mean kurtosis (MK) and mean diffusivity (MD) values were measured. ROC curves were employed to evaluate the efficiency of differentiating and diagnosing stage Ia EC and EP, followed by the Delong test to compare the differences between the areas under the curve (AUCs) of each parameter. Additionally, the Pearson correlation analysis was performed to assess the correlation between APT values and MK and MD. RESULTS: The measured APT, MK, and MD values of the patients with stage Ia EC were 2.609 ± 0.504%,0.641 ± 0.113 and 0.904(0.816, 1.108) µm2/ms, while those of patients with EP were1.909 ± 0.418%, 0.495 ± 0.069, and 1.650 (1.458, 1.815) µm2/ms. The AUCs of APT, MK, MD, MK + MD, and APT + MK + MD in differentiating stage Ia EC and EP were.850, 0.879, 0.893, 0.930 and 0.976, respectively. The AUCs of APT + MK + MD were significantly higher than the AUCs of APT or MK (P < 0.05). The APT value was weakly and positively correlated with the MK value (r = 0.299, P = 0.037), while the APT value was moderately and negatively correlated with the MD value (r = -0.520, P < 0.001). CONCLUSION: Both APT and DKI effectively differentiated stage Ia EC and EP; however, when combined, APT and DKI improved the ability to differentiate these diseases, boosting the value of using a combination of these modalities in clinical applications.

Amide Proton Transfer-Weighted Imaging Combined With Intravoxel Incoherent Motion for Evaluating Microsatellite Instability in Endometrial Cancer.

BACKGROUND: Microsatellite instability (MSI), caused by mismatch repair (MMR) protein defects that lead to uncorrectable mismatch bases, results in the accumulation of gene mutations and ultimately to tumors. Preoperative prediction of MSI can provide a basis for personalized and precise treatment of endometrial cancer (EC) patients. PURPOSE: To investigate amide proton transfer weighting (APTw) imaging combined with intravoxel incoherent motion (IVIM) in the assessment of MSI in EC. STUDY TYPE: Retrospective. POPULATION: A total of 71 patients with EC (12 classified as the MSI group and 22 as the microsatellite stabilization [MSS] group after entering and leaving the group standard). FIELD STRENGTH/SEQUENCE: A 3.0 T/IVIM, diffusion-weighted imaging (DWI) and APTw. ASSESSMENT: Amide proton transfer (APT) value, apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo diffusion coefficient (D*), and perfusion fraction (f) were calculated and compared between MSI and MSS groups. STATISTICAL TESTS: The Kendall's W test; Mann-Whitney U-test; Chi-square test or Fisher's exact test; logistic regression analysis; Area under the receiver operating characteristic (ROC) curve (AUC); The Delong test; Pearson or Spearman correlation coefficients. The significance threshold was set at P < 0.05. RESULTS: APT and D* values of the MSI group were significantly higher than those of the MSS group. While ADC, D, and f values in the MSI group were significantly lower than those in the MSS group. The multivariate analysis revealed that only APT and D* values were independent predictors to evaluate the MSI status. And the ROC curves indicated that the combination of APT and D* values could distinguish the MSI status of EC with the highest diagnostic efficacy (AUC = 0.973), even without significant difference to those by APT (AUC = 0.894) or D* (AUC = 0.920) value separately (P = 0.149 and 0.078, respectively). CONCLUSION: Combination of APTw and IVIM imaging may serve as an effective noninvasive method for clinical assessment of MSI in EC. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

Three-dimensional amide proton transfer-weighted and intravoxel incoherent motion imaging for predicting bone metastasis in patients with prostate cancer: A pilot study.

PURPOSE: To explore the value of 3-dimensional amide proton transfer-weighted (APTw) and intravoxel incoherent motion (IVIM) imaging in predicting bone metastasis (BM) of prostate cancer (PCa) in addition to routine diffusion-weighted imaging (DWI). METHODS: The clinical and imaging data of 39 PCa patients who were pathologically confirmed in our hospital from March 2019 to February 2022 were retrospectively analyzed, and they were divided into BM-negative (27 patients) and BM-positive (12 patients) groups. MR examination included APTw, DWI and IVIM imaging. The IVIM data was fitted by single-exponential IVIM model (IVIMmono) and double-exponential IVIM model (IVIMbi), respectively. The APTw, ADC, IVIMmono (Dmono, D*mono, and fmono), and IVIMbi (Dbi, D*bi, and fbi) parameters were independently measured by two radiologists. The synthetic minority oversampling technique (SMOTE) was conducted to balance the minority group. Mann-Whitney U test or Student's t-test was used to compare above values between the BM-negative and BM-positive groups. The diagnostic performance was evaluated with receiver operating characteristic (ROC) analysis of each parameter and their combination. The Delong test was used for ROC curve comparison.The relationship between APTw and IVIM was explored through Spearman's rank correlation analysis. RESULTS: The APTw and D*mono values were higher, and the ADC, fmono, and fbi values were lower in the BM-positive group than in the BM-negative group (all P < 0.05). Among the individual parameters, the AUC of fmono was the highest (AUC = 0.865), and AUC (fmono) was significantly higher than AUC (fbi), AUC (D*mono), and AUC (ADC) (all P < 0.05). The AUC (IVIMmono) was higher than the AUC (IVIMbi) (P = 0.0068). The combination of APTw and IVIMmono further improved diagnostic capability, and the AUC of APTw+IVIMmono was significantly higher than those of APTw and DWI (all P < 0.05). No correlation was found between IVIM-derived parameters and APTw value. CONCLUSION: Both 3D APTw and IVIM imaging could predict BM of PCa. IVIM showed better performance than APTw and DWI, and the single-exponential IVIM model was superior to the double-exponential IVIM model. The combination of APTw and IVIM could further improve diagnostic performance.

IMPULSED model based cytological feature estimation with U-Net: Application to human brain tumor at 3T.

PURPOSE: This work introduces and validates a deep-learning-based fitting method, which can rapidly provide accurate and robust estimation of cytological features of brain tumor based on the IMPULSED (imaging microstructural parameters using limited spectrally edited diffusion) model fitting with diffusion-weighted MRI data. METHODS: The U-Net was applied to rapidly quantify extracellular diffusion coefficient (Dex ), cell size (d), and intracellular volume fraction (vin ) of brain tumor. At the training stage, the image-based training data, synthesized by randomizing quantifiable microstructural parameters within specific ranges, was used to train U-Net. At the test stage, the pre-trained U-Net was applied to estimate the microstructural parameters from simulated data and the in vivo data acquired on patients at 3T. The U-Net was compared with conventional non-linear least-squares (NLLS) fitting in simulations in terms of estimation accuracy and precision. RESULTS: Our results confirm that the proposed method yields better fidelity in simulations and is more robust to noise than the NLLS fitting. For in vivo data, the U-Net yields obvious quality improvement in parameter maps, and the estimations of all parameters are in good agreement with the NLLS fitting. Moreover, our method is several orders of magnitude faster than the NLLS fitting (from about 5 min to <1 s). CONCLUSION: The image-based training scheme proposed herein helps to improve the quality of the estimated parameters. Our deep-learning-based fitting method can estimate the cell microstructural parameters fast and accurately.

Multi-parametric MRI-based radiomics for preoperative prediction of multiple biological characteristics in endometrial cancer.

Purpose: To develop and validate multi-parametric MRI (MP-MRI)-based radiomics models for the prediction of biological characteristics in endometrial cancer (EC). Methods: A total of 292 patients with EC were divided into LVSI (n = 208), DMI (n = 292), MSI (n = 95), and Her-2 (n = 198) subsets. Total 2316 radiomics features were extracted from MP-MRI (T2WI, DWI, and ADC) images, and clinical factors (age, FIGO stage, differentiation degree, pathological type, menopausal state, and irregular vaginal bleeding) were included. Intra-class correlation coefficient (ICC), spearman's rank correlation test, univariate logistic regression, and least absolute shrinkage and selection operator (LASSO) were used to select radiomics features; univariate and multivariate logistic regression were used to identify clinical independent risk factors. Five classifiers were applied (logistic regression, random forest, decision tree, K-nearest neighbor, and Bayes) to construct radiomics models for predicting biological characteristics. The clinical model was built based on the clinical independent risk factors. The combined model incorporating the radiomics score (radscore) and the clinical independent risk factors was constructed. The model was evaluated by ROC curve, calibration curve (H-L test), and decision curve analysis (DCA). Results: In the training cohort, the RF radiomics model performed best among the five classifiers for the three subsets (MSI, LVSI, and DMI) according to AUC values (AUCMSI: 0.844; AUCLVSI: 0.952; AUCDMI: 0.840) except for Her-2 subset (Decision tree: AUC=0.714), and the combined model had higher AUC than the clinical model in each subset (MSI: AUCcombined =0.907, AUCclinical =0.755; LVSI: AUCcombined =0.959, AUCclinical =0.835; DMI: AUCcombined = 0.883, AUCclinical =0.796; Her-2: AUCcombined =0.812, AUCclinical =0.717; all P<0.05). Nevertheless, in the validation cohort, significant differences between the two models (combined vs. clinical model) were found only in the DMI and LVSI subsets (DMI: AUCcombined =0.803, AUCclinical =0.698; LVSI: AUCcombined =0.926, AUCclinical =0.796; all P<0.05). Conclusion: The radiomics analysis based on MP-MRI and clinical independent risk factors can potentially predict multiple biological features of EC, including DMI, LVSI, MSI, and Her-2, and provide valuable guidance for clinical decision-making.