Predicting Treatment Response of Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer Using Amide Proton Transfer MRI Combined With Diffusion-Weighted Imaging

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.

Chemical Shift-Encoded Sequence (IDEAL-IQ) and Amide Proton Transfer (APT) MRI for Prediction of Histopathological Factors of Rectal Cancer

To investigate whether parameters from IDEAL-IQ/amide proton transfer MRI (APTWI) could help predict histopathological factors of rectal cancer. Preoperative IDEAL-IQ and APTWI sequences of 67 patients with rectal cancer were retrospectively analyzed. The intra-tumoral proton density fat fraction (PDFF), R2* and magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)) were measured according to the histopathological factors of rectal cancer. The relationship between MR parameters and histopathological factors were analyzed, along with diagnostic performance of MR parameters. PDFF, R2* and MTRasym (3.5 ppm) were statistically different between T1+T2/T3+T4 stages, non-metastatic/metastatic lymph nodes, lower/higher tumor grade and negative/positive status of MRF and EMVI (p < 0.001 for PDFF, p = 0.000-0.015 for R2* and p = 0.000-0.006 for MTRasym (3.5 ppm)). There were positive correlations between the above parameters and the histopathological features of rectal cancer (r = 0.464-0.723 for PDFF (p < 0.001), 0.299-0.651 for R2* (p = 0.000-0.014), and 0.337-0.667 for MTRasym (3.5 ppm) (p = 0.000-0.005)). MTRasym (3.5 ppm) correlated moderately and mildly with PDFF (r = 0.563, p < 0.001) and R2* (r = 0.335, p = 0.006), respectively. PDFF provided a significantly higher diagnostic ability than MTRasym (3.5 ppm) for distinguishing metastatic from non-metastatic lymph nodes (z = 2.407, p = 0.0161). No significant differences were found in MR parameters for distinguishing other histopathological features (p > 0.05). IDEAL-IQ and APTWI were associated with histopathological factors of rectal cancer, and might serve as non-invasive biomarkers for characterizing rectal cancer.

A positive feedback loop between ID3 and PPARγ via DNA damage repair regulates the efficacy of radiotherapy for rectal cancer

OBJECTIVE

To study the effect of inhibitor of differentiation 3 (ID3) on radiotherapy in patients with rectal cancer and to explore its primary mechanism.

METHODS

Cell proliferation and clonogenic assays were used to study the relationship between ID3 and radiosensitivity. Co-immunoprecipitation and immunofluorescence were performed to analyze the possible mechanism of ID3 in the radiosensitivity of colorectal cancer. At the same time, a xenograft tumor model of HCT116 cells in nude mice was established to study the effect of irradiation on the tumorigenesis of ID3 knockdown colorectal cancer cells in vivo. Immunohistochemistry was performed to analyze the relationship between ID3 expression and the efficacy of radiotherapy in 46 patients with rectal cancer.

RESULTS

Proliferation and clonogenic assays revealed that the radiosensitivity of colorectal cancer cells decreased with ID3 depletion through p53-independent pathway. With the decrease in ID3 expression, MDC1 was downregulated. Furthermore, the expression of ID3, MDC1, and γH2AX increased and formed foci after irradiation. ID3 interacted with PPARγ and form a positive feedback loop to enhance the effect of ID3 on the radiosensitivity of colorectal cancer. Irradiation tests in nude mice also confirmed that HCT116 cells with ID3 knockdown were more affected by irradiation. Immunohistochemical study showed that rectal cancer patients with low expression of ID3 had better radiotherapy efficacy.

CONCLUSIONS

ID3 and PPARγ influence the radiosensitivity of colorectal cancer cells by interacting with MDC1 to form a positive feedback loop that promotes DNA damage repair. Patients with low expression of ID3 who received neoadjuvant chemoradiotherapy can obtain a better curative effect.

MRI-based pre-Radiomics and delta-Radiomics models accurately predict the post-treatment response of rectal adenocarcinoma to neoadjuvant chemoradiotherapy

Objectives

To develop and validate magnetic resonance imaging (MRI)-based pre-Radiomics and delta-Radiomics models for predicting the treatment response of local advanced rectal cancer (LARC) to neoadjuvant chemoradiotherapy (NCRT).

Methods

Between October 2017 and August 2022, 105 LARC NCRT-naïve patients were enrolled in this study. After careful evaluation, data for 84 patients that met the inclusion criteria were used to develop and validate the NCRT response models. All patients received NCRT, and the post-treatment response was evaluated by pathological assessment. We manual segmented the volume of tumors and 105 radiomics features were extracted from three-dimensional MRIs. Then, the eXtreme Gradient Boosting algorithm was implemented for evaluating and incorporating important tumor features. The predictive performance of MRI sequences and Synthetic Minority Oversampling Technique (SMOTE) for NCRT response were compared. Finally, the optimal pre-Radiomics and delta-Radiomics models were established respectively. The predictive performance of the radionics model was confirmed using 5-fold cross-validation, 10-fold cross-validation, leave-one-out validation, and independent validation. The predictive accuracy of the model was based on the area under the receiver operator characteristic (ROC) curve (AUC).

Results

There was no significant difference in clinical factors between patients with good and poor reactions. Integrating different MRI modes and the SMOTE method improved the performance of the radiomics model. The pre-Radiomics model (train AUC: 0.93 ± 0.06; test AUC: 0.79) and delta-Radiomcis model (train AUC: 0.96 ± 0.03; test AUC: 0.83) all have high NCRT response prediction performance by LARC. Overall, the delta-Radiomics model was superior to the pre-Radiomics model.

Conclusion

MRI-based pre-Radiomics model and delta-Radiomics model all have good potential to predict the post-treatment response of LARC to NCRT. Delta-Radiomics analysis has a huge potential for clinical application in facilitating the provision of personalized therapy.

Amide proton transfer weighted imaging combined with dynamic contrast-enhanced MRI in predicting lymphovascular space invasion and deep stromal invasion of IB1-IIA1 cervical cancer

Objectives

To investigate the value of amide proton transfer weighted (APTw) imaging combined with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in predicting intermediate-risk factors of deep stromal invasion (DSI) and lymphovascular vascular space invasion (LVSI) in cervical cancer.

Methods

Seventy patients with cervical cancer who underwent MRI before operation from July 2019 to February 2022 were retrospectively included in this study. Clinical information including age, histologic subtype etc. were recorded for patients. ATPw imaging parameter APT_mean and DCE-MRI parameters K^trans, K_ep and V_e were measured and analyzed. The independent-sample t-test, Mann-Whitney U test, or Chi-square test was used to compare the differences of parameters between DSI/LVSI positive and negative groups. Logistic analysis was used to develop a combined predictive model. The receiver operating characteristic curve was for predictive performance. ANOVA and Kruskal-Wallis test were used to compare the differences of consecutive parameters among multiple groups.

Results

K^trans and SCC-Ag were independent factors in predicting DSI; K^trans+SCC-Ag had the highest AUC 0.819 with sensitivity and specificity of 71.74% and 91.67%, respectively. APT_mean and K^trans were independent factors in predicting LVSI; APT_mean+K^trans had the highest AUC 0.874 with sensitivity and specificity of 92.86% and 75.00%, respectively. K^trans and Ve could discriminate coexistence of DSI and LVSI from presence of single one, APT_mean could discriminate the presence of DSI or LVSI from no risk factor presence.

Conclusion

The combination of APTw and DCE-MRI is valuable in predicting intermediate-risk factors of DSI and LVSI in cervical cancer.

Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer

BACKGROUND

Whole-tumor apparent diffusion coefficient (ADC) histogram analysis is relevant to predicting the neoadjuvant chemoradiation therapy (nCRT) response in patients with locally advanced rectal cancer (LARC).

AIM

To evaluate the performance of ADC histogram-derived parameters for predicting the outcomes of patients with LARC.

METHODS

This is a single-center, retrospective study, which included 48 patients with LARC. All patients underwent a pre-treatment magnetic resonance imaging (MRI) scan for primary tumor staging and a second restaging MRI for response evaluation. The sample was distributed as follows: 18 responder patients (R) and 30 non-responders (non-R). Eight parameters derived from the whole-lesion histogram analysis (ADCmean, skewness, kurtosis, and ADC10^th, 25^th, 50^th, 75^th, 90^th percentiles), as well as the ADCmean from the hot spot region of interest (ROI), were calculated for each patient before and after treatment. Then all data were compared between R and non-R using the Mann-Whitney U test. Two measures of diagnostic accuracy were applied: the receiver operating characteristic curve and the diagnostic odds ratio (DOR). We also reported intra- and interobserver variability by calculating the intraclass correlation coefficient (ICC).

RESULTS

Post-nCRT kurtosis, as well as post-nCRT skewness, were significantly lower in R than in non-R (both P < 0.001, respectively). We also found that, after treatment, R had a larger loss of both kurtosis and skewness than non-R (∆%kurtosis and ∆skewness, P < 0.001). Other parameters that demonstrated changes between groups were post-nCRT ADC10^th, ∆%ADC10^th, ∆%ADCmean, and ROI ∆%ADCmean. However, the best diagnostic performance was achieved by ∆%kurtosis at a threshold of 11.85% (Area under the receiver operating characteristic curve [AUC] = 0.991, DOR = 376), followed by post-nCRT kurtosis = 0.78 × 10^-3 mm²/s (AUC = 0.985, DOR = 375.3), ∆skewness = 0.16 (AUC = 0.885, DOR = 192.2) and post-nCRT skewness = 1.59 × 10^-3 mm²/s (AUC = 0.815, DOR = 168.6). Finally, intraclass correlation coefficient analysis showed excellent intraobserver and interobserver agreement, ensuring the implementation of histogram analysis into routine clinical practice.

CONCLUSION

Whole-tumor ADC histogram parameters, particularly kurtosis and skewness, are relevant biomarkers for predicting the nCRT response in LARC. Both parameters appear to be more reliable than ADCmean from one-slice ROI.

MRI Evaluation of Complete and Near-Complete Response after Neoadjuvant Therapy in Patients with Locally Advanced Rectal Cancer

Purpose To evaluate MRI performance in restaging locally advanced rectal cancers (LARC) after neoadjuvant chemoradiotherapy (nCRT) and interobserver agreement in identifying complete response (CR) and near-complete response (nCR). Methods 40 patients with CR and nCR on restaging MRI, surgery and/or endoscopy were enrolled. Two radiologists independently scored the restaging MRI and reported the presence of split scar sign (SSS) and MRI tumor regression grade (mrTRG). Diagnostic accuracy and ROC curves were calculated for single and combined sequences, with inter-reader agreement. Results Diagnostic performance was good for detecting CR and weaker for nCR. T2WI had the highest AUCs among individual sequences. There was a significant positive correlation between SSS and CR, with high Sp (89.5%/73.7%) and PPV (90%/79.2%) for both Readers. Similar accuracy rates were observed for the combination of sequences, with AUCs of 0.828–0.847 for CR and 0.690–0.762 for nCR. Interobserver agreement was strong for SSS, moderate for T2WI, weak for the combination of sequences. Conclusions Restaging MRI had good diagnostic performance in identifying CR and nCR. SSS had high Sp and PPV in diagnosing CR, with a strong level of interobserver agreement. T2WI with DWI was the optimal combination of sequences for selecting good responders.

Predicting Neoadjuvant Chemoradiotherapy Response in Locally Advanced Rectal Cancer Using Tumor-Infiltrating Lymphocytes Density

PURPOSE

Accumulating evidence revealed the predictive value of tumor-infiltrating lymphocytes (TILs) for neoadjuvant chemoradiotherapy (nCRT) response in solid tumors. This study quantified TILs density using hematoxylin and eosin (H&E) stained whole-slide images (WSIs) and investigated the predictive value of TILs density on nCRT response in locally advanced rectal cancer (LARC) patients.

PATIENTS AND METHODS

Two hundred and ten patients diagnosed with LARC were enrolled in this study. The density of TILs in the stroma region was quantified by a semi-automatic method in WSIs. Patients were stratified into low-TILs and high-TILs groups using the median value as the threshold. The tumor regression grade (TRG) was used to assess the response to nCRT in tumor resected specimens. Based on TRG, patients were classified into major-responder (TRG 0-1) and non-responder (TRG 2-3) groups.

RESULTS

The TILs density was significantly correlated with the nCRT response. Specifically, patients with high-TILs tend to have a higher major-responder rate than the low-TILs group (63.8% vs 47.6%, P = 0.026). Univariate analysis showed the TILs density was a predictor for the nCRT response (high vs low, odds ratio [OR] =1.94, 95% confidence interval 1.12-3.37, P = 0.019), and multivariate analysis further confirmed the correlation (adjusted odds ratio [AOR] = 2.41, 1.28-4.56, P = 0.007).

CONCLUSION

Patients with a high-TIL density have a higher major-responder rate than the low-TILs group, indicating patients with a strong immune response benefit more from nCRT. This semi-automatic method can facilitate the individualized preoperative prediction of the TRG for LARC patients before nCRT.

A Brief History and Future Prospects of CEST MRI in Clinical Non-Brain Tumor Imaging

Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging tool which allows the specific detection of metabolites that contain exchangeable amide, amine, and hydroxyl protons. Decades of development have progressed CEST imaging from an initial concept to a clinical imaging tool that is used to assess tumor metabolism. The first translation efforts involved brain imaging, but this has now progressed to imaging other body tissues. In this review, we summarize studies using CEST MRI to image a range of tumor types, including breast cancer, pelvic tumors, digestive tumors, and lung cancer. Approximately two thirds of the published studies involved breast or pelvic tumors which are sites that are less affected by body motion. Most studies conclude that CEST shows good potential for the differentiation of malignant from benign lesions with a number of reports now extending to compare different histological classifications along with the effects of anti-cancer treatments. Despite CEST being a unique 'label-free' approach with a higher sensitivity than MR spectroscopy, there are still some obstacles for implementing its clinical use. Future research is now focused on overcoming these challenges. Vigorous ongoing development and further clinical trials are expected to see CEST technology become more widely implemented as a mainstream imaging technology.