Predictive value of diffusion-weighted MR imaging in early response to chemoradiotherapy of esophageal cancer: a meta-analysis

Lesion Volume Divided by ADC Measures Is an Independent Prognostic Marker in Colorectal Liver Metastasis Treated by Y90-radioembolization

BACKGROUND/AIM

To assess the ability of apparent diffusion coefficient (ADC) at baseline in predicting overall survival in patients who undergo Y90-radioembolization (Y90-RE) for liver-dominant metastatic colorectal cancer (mCRC) in the salvage situation.

PATIENTS AND METHODS

A retrospective review of 411 lesions in 63 patients with refractory mCRC treated with Y90-RE was conducted. Manual region of interest (ROI) measurements were applied using a whole lesion and volume method. Minimum and mean ADC values were measured, and averages were calculated per patient. Ratios combining tumor volume and ADC were correlated with OS, and a receiver-operating characteristic (ROC) analysis defined a cut-off value. Cox regression analysis was performed, and the log-rank test confirmed prognostic cut-off levels for survival.

RESULTS

The median survival was 6.4 months. Multivariate Cox regression identified tumor volume divided by minimum ADC (ADCtumor volume, min) as an independent predictor of OS (HR=1.814, 95%CI=1.188-2.770, p=0.006). Neither ADCmin nor ADCmean were significantly associated with survival. Optimal prediction was identified with a ADCtumor volume, min cut-off of 0.3673 arbitrary units (AU) yielding 76.0% sensitivity and 70.3% specificity. Patients with ADCtumor volume min <0.3673 had a median OS of 10.4 months, compared to 4.7 months for those above the cut-off (p<0.001).

CONCLUSION

Tumor volume divided by minimum ADC at baseline (ADCtumor volume, min) was identified as an independent predictor of OS in mCRC scheduled for Y90-radioembolization in the salvage situation and may improve future patient selection.

Meta-Analysis of MRI in Predicting Early Response to Radiotherapy and Chemotherapy in Esophageal Cancer

RATIONALE AND OBJECTIVES

At present, the application of magnetic resonance imaging (MRI) in the prediction of response to neoadjuvant therapy and concurrent chemoradiotherapy for the treatment of esophageal cancer still needs to be further explored, and its early differential value remains controversial, thus we carried out this systematic review with a meta-analysis. In the application, different MRI sequences and corresponding parameters are used for the differential diagnosis of the response to neoadjuvant therapy and concurrent chemoradiotherapy.

METHODS

All relevant studies evaluated the efficacy and response to MRI in neoadjuvant therapy or concurrent chemoradiotherapy for esophageal cancer on Pubmed, Embase, Cohrane Library, and Web of Science databases published before October 10, 2023 (inclusive) were systematically searched. A revised tool was used to assess the quality of diagnostic accuracy studies (QUADAS-2) to assess the risk of bias in the included original studies. A subgroup analysis of MRI sequences diffusion weighted imaging (DWI), dynamic contrast enhanced (DCE) and their corresponding different parameters, as well as the acquisition timepoints (before and after treatment) for different parameters, was performed during the meta-analysis. The bivariate mixed-effects model was used for meta-analysis.

RESULTS

21 studies were finally included, involving 1128 patients with esophageal cancer. The sensitivity, specificity, and area under receiver operating characteristic curve (ROC curve) of DWI sequence for identifying response to concurrent chemoradiotherapy were 0.82 (95% CI: 0.74-0.87), 0.81 (95% CI: 0.72-0.87) and 0.88 (95% CI: 0.56-0.98), respectively. The sensitivity, specificity, and area under ROC curve of DCE sequence for identifying response to concurrent chemoradiotherapy were 0.78 (95% CI: 0.70-0.84), 0.65 (95% CI: 0.59-0.70) and 0.73 (95% CI: 0.50-0.88), respectively. In patients with esophageal cancer, the sensitivity, specificity, and area under the ROC curve of DWI sequences for identifying response to neoadjuvant therapy were 0.80 (95% CI: 0.69 - 0.88), 0.81 (95% CI: 0.69 - 0.89), and 0.88 (95% CI: 0.34 - 0.99), respectively; the sensitivity, specificity, and area under the ROC curve of DCE sequences for identifying response to neoadjuvant therapy were 0.84 (95% CI: 0.76 - 0.90), 0.61 (95% CI: 0.53 - 0.68), and 0.70 (95% CI: 0.27 - 0.94), respectively.

CONCLUSIONS

Based on the available evidence, MRI had a very good value in the early identification of response to neoadjuvant therapy and concurrent chemoradiotherapy for esophageal cancer, especially DWI. Apparent diffusion coefficient (ADC) value changes before and after treatment could be used as predictors of pathological response. Also, ADC value changes before and after treatment could be used as a tool to guide clinical decision-making.

Local ablation of hepatocellular carcinoma by interstitial brachytherapy: prediction of outcome by diffusion-weighted imaging

BACKGROUND

Interstitial brachytherapy (iBT) has become a viable treatment option in the therapy of early and intermediate stage hepatocellular carcinoma (HCC). Prognostic imaging tools to predict patient outcome are missing.

PURPOSE

To assess the predictive value of baseline diffusion-weighted imaging in HCC before iBT with regard to local tumor control and overall survival (OS).

MATERIAL AND METHODS

We retrospectively identified 107 patients who underwent iBT for HCC from 2011 to 2018 from our database. Apparent diffusion coefficient (ADC) values for each treated lesion were analyzed in region of interest measurements. Additionally, explorative combined ratios adjusting total measured lesion area and mean measured lesion area per patient by ADC values were calculated. Measurements underwent a univariate and multivariate Cox regression analysis. The log rank test was then used to verify prognostic cutoff levels for median survival time.

RESULTS

A total of 189 lesions in 81 patients were measured. Median survival of patients was 46.0 months. Neither ADC parameter was indicative of local tumor control. Lesion size >5 cm was associated with lower local tumor control (hazard ratio [HR]=4.292, 95% confidence interval [CI]=1.285-14.331; P = 0.018). Average measured lesion area divided by ADC_min (ADC_{area mean, min}) was identified to independently predict OS (HR=1.994, 95% CI=1.172-3.392; P = 0.011). A cutoff based on the variable's median (0.29 × 10-4 AU) identified patients with poor outcome (OS 36 vs. 61 months) for lower ADC_{area mean, min} values as verified by the log-rank test (P = 0.040).

CONCLUSION

Pre-treatment ADC_{area mean, min} may serve as an independent predictor of OS in patients with HCC undergoing iBT.

Apparent Diffusion Coefficient Can Predict Therapy Response of Hepatocellular Carcinoma to Transcatheter Arterial Chemoembolization

AIM

The goal of this meta-analysis was to assess the apparent diffusion coefficient (ADC) as a pre- and posttreatment (ADC value changes [ΔADC]) predictive imaging biomarker of response to transcatheter arterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC).

METHODS

Scopus database, Embase database, and MEDLINE library were scanned for connections between pre- and posttreatment ADC values of HCC and response to TACE. Six studies qualified for inclusion. The following parameters were collected: authors, publication year, study design, number of patients, drugs for TACE, mean ADC value, standard deviation, measure method, b values, and Tesla strength. The Quality Assessment of Diagnostic Studies 2 instrument was employed to check the methodological quality of each study. The meta-analysis was performed by utilizing RevMan 5.3 software. DerSimonian and Laird random-effects models with inverse-variance were used to regard heterogeneity. The mean ADC values and 95% confidence intervals were computed.

RESULTS

Six studies (n = 271 patients with 293 HCC nodules) were included. The pretreatment mean ADC in the responder group was 1.20 × 10-3 mm2/s (0.98, 1.42) and 1.14 × 10-3 mm2/s (0.89, 1.39) in the nonresponder group. The analysis of post-TACE ΔADC revealed a threshold of ≥20% to identify treatment responders. No suitable pretreatment ADC threshold to predict therapy response or discriminate between responders and nonresponders before therapy could be discovered.

CONCLUSION

ΔADC can facilitate early objective response evaluation through post-therapeutic ADC alterations ≥20%. Pretreatment ADC cannot predict response to TACE.

Predicting Grade of Esophageal Squamous Carcinoma: Can Stretched Exponential Model-Based DWI Perform Better Than Bi-Exponential and Mono-Exponential Model?

Background

To evaluate and compare the potential performance of various diffusion parameters obtained from mono-exponential model (MEM)-, bi-exponential model (BEM)-, and stretched exponential model (SEM)-based diffusion-weighted imaging (DWI) in grading of esophageal squamous carcinoma (ESC).

Methods

Eighty-two patients with pathologically confirmed ESC without treatment underwent multi-b-value DWI scan with 13 b values (0~12,00 s/mm²). The apparent diffusion coefficient (ADC) deriving from the MEM; the pure molecular diffusion (ADC_slow), pseudo-diffusion coefficient (ADC_fast), perfusion, and fraction (f) deriving from the BEM; and the distributed diffusion coefficient (DDC) and water molecular diffusion heterogeneity index (α) deriving from the SEM were calculated and compared between poorly differentiated and well/moderately differentiated ESC, respectively. The prediction parameters and diagnostic efficiency were compared by drawing receiver operating characteristic (ROC) curves.

Results

The ADC, ADC_slow, ADC_fast, and DDC in poorly ESC were significantly lower than those in well/moderately differentiated ones. By using only one parameter, ADC_slow, DDC had the moderate diagnostic efficiency and the areas under the curve (AUC) were 0.758 and 0.813 in differentiating ESC. The DDC had the maximum AUC with sensitivity (88.00%) and specificity (68.42%). Combining ADC with ADC_fast, ADC_slow, and DDC and combining ADC_slow with ADC_fast can provide a higher diagnostic accuracy with AUC ranging from 0.756, 0.771, 0.816, and 0.793, respectively.

Conclusion

Various parameters derived from different DWI models including MEM, BEM, and SEM were potentially helpful in grading ESC. DDC obtained from SEM was the most promising diffusion parameter for predicting the grade of ESC.

The Role of Magnetic Resonance Imaging in the Management of Esophageal Cancer

Esophageal cancer (EC) is the eighth more frequent cancer worldwide, with a poor prognosis. Initial staging is critical to decide on the best individual treatment approach. Current modalities for the assessment of EC are irradiating techniques, such as computed tomography (CT) and positron emission tomography/CT, or invasive techniques, such as digestive endoscopy and endoscopic ultrasound. Magnetic resonance imaging (MRI) is a non-invasive and non-irradiating imaging technique that provides high degrees of soft tissue contrast, with good depiction of the esophageal wall and the esophagogastric junction. Various sequences of MRI have shown good performance in initial tumor and lymph node staging in EC. Diffusion-weighted MRI has also demonstrated capabilities in the evaluation of tumor response to chemoradiotherapy. To date, there is not enough data to consider whole body MRI as a routine investigation for the detection of initial metastases or for prediction of distant recurrence. This narrative review summarizes the current knowledge on MRI for the management of EC.

Intravoxel Incoherent Motion Model in Differentiating the Pathological Grades of Esophageal Carcinoma: Comparison of Mono-Exponential and Bi-Exponential Fit Model

PURPOSE

To compare the diagnostic efficiency of the mono-exponential model and bi-exponential model deriving from intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in differentiating the pathological grade of esophageal squamous cell carcinoma (ESCC).

METHODS

Fifty-four patients with ESCC were divided into three groups of poorly-differentiated (PD), moderately-differentiated (MD), and well-differentiated (WD), and underwent the IVIM-DWI scan. Mono-exponential (Dmono, D*mono, and fmono) and bi-exponential fit parameters (Dbi, D*bi, and fbi) were calculated using the IVIM data for the tumors. Mean parameter values of three groups were compared using a one-way ANOVA followed by post hoc tests. The receiver operating characteristic curve was drawn for differentiating pathological grade of ESCC. Correlations between pathological grades and IVIM parameters were analyzed.

RESULTS

There were significant differences in fmono and fbi among the PD, MD and WD ESCC groups (all p<0.05). The fmono were 0.32 ± 0.07, 0.23 ± 0.08, and 0.16 ± 0.05, respectively, and the fbi were 0.35 ± 0.08, 0.26 ± 0.10, and 0.18 ± 0.07, respectively. There was a significant difference in the Dmono between the WD and the PD group (1.48 ± 0.51* 10-3 mm2/s versus 1.05 ± 0.44*10-3 mm2/s, p<0.05), but there was no significant difference between the WD and MD groups, MD and PD groups (all p>0.05). The D*mono, Dbi, and D*bi showed no significant difference among the three groups (all p>0.05). The area under the curve (AUC) of Dmono, fmono and fbi in differentiating WD from PD ESCC were 0.764, 0.961 and 0.932, and the sensitivity and specificity were 92.9% and 60%, 92.9% and 90%, 85.7% and 100%, respectively. The AUC of fmono and fbi in differentiating MD from PD ESCC were 0.839 and 0.757, and the sensitivity and specificity were 78.6% and 80%, 85.7% and 70%, respectively. The AUC of fmono and fbi in differentiating MD from WD ESCC were 0.746 and 0.740, and the sensitivity and specificity were 65% and 85%, 80% and 60%, respectively. The pathologically differentiated grade was correlated with all IVIM parameters (all p<0.05).

CONCLUSIONS

The mono-exponential IVIM model is superior to the bi-exponential IVIM model in differentiating pathological grades of ESCC, which may be a promising imaging method to predict pathological grades of ESCC.

Optimal timing for prediction of pathologic complete response to neoadjuvant chemoradiotherapy with diffusion-weighted MRI in patients with esophageal cancer

OBJECTIVE

This study was conducted in order to determine the optimal timing of diffusion-weighted magnetic resonance imaging (DW-MRI) for prediction of pathologic complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) for esophageal cancer.

METHODS

Patients with esophageal adenocarcinoma or squamous cell carcinoma who planned to undergo nCRT followed by surgery were enrolled in this prospective study. Patients underwent six DW-MRI scans: one baseline scan before the start of nCRT and weekly scans during 5 weeks of nCRT. Relative changes in mean apparent diffusion coefficient (ADC) values between the baseline scans and the scans during nCRT (ΔADC(%)) were compared between pathologic complete responders (pCR) and non-pCR (tumor regression grades 2-5). The discriminative ability of ΔADC(%) was determined based on the c-statistic.

RESULTS

A total of 24 patients with 142 DW-MRI scans were included. pCR was observed in seven patients (29%). ΔADC(%) from baseline to week 2 was significantly higher in patients with pCR versus non-pCR (median [IQR], 36% [30%, 41%] for pCR versus 16% [14%, 29%] for non-pCR, p = 0.004). The ΔADC(%) of the second week in combination with histology resulted in the highest c-statistic for the prediction of pCR versus non-pCR (0.87). The c-statistic of this model increased to 0.97 after additional exclusion of patients with a small tumor volume (< 7 mL, n = 3) and tumor histology of the resection specimen other than adenocarcinoma or squamous cell carcinoma (n = 1).

CONCLUSION

The relative change in tumor ADC (ΔADC(%)) during the first 2 weeks of nCRT is the most predictive for pathologic complete response to nCRT in esophageal cancer patients.

KEY POINTS

• DW-MRI during the second week of neoadjuvant chemoradiotherapy is most predictive for pathologic complete response in esophageal cancer. • A model including ΔADCweek 2was able to discriminate between pathologic complete responders and non-pathologic complete responders in 87%. • Improvements in future MRI studies for esophageal cancer may be obtained by incorporating motion management techniques.

Prognostic value of 18F-FDG PET/MR imaging biomarkers in oesophageal squamous cell carcinoma

PURPOSE

To correlate the clinical stage and prognosis of oesophageal squamous cell carcinoma (SCC) using the imaging biomarkers from integrated positron emission tomography (PET)/magnetic resonance imaging (MRI).

METHODS

In total, 54 consecutive patients with oesophageal SCC who receive PET/MRI scan were recruited before treatment. The imaging biomarkers used were the mean and minimal apparent diffusion coefficients (ADC_mean and ADC_min), standardized uptake value (SUV), metabolic tumour volume (MTV), and total lesion glycolysis (TLG) of tumours. The correlation between each imaging biomarker and survival was investigated using the Cox proportional hazards model.

RESULTS

ADC_mean was negatively correlated with SUV_max (r = -0.414, P =  0.025). ADC_min was negatively correlated with SUV_max (r = -0.423, P =  0.001) and SUV_peak (r = -0.402, P =  0.003), and was significantly lower in M1 than in M0 tumours (829.6 vs. 1069.8, P = 0.005). MTV was significantly higher in T3 + (P <  0.001), N1 + (P = 0.014) and TNM stage III + (P <  0.001) tumours. TLG was significantly higher in T3 + (P <  0.001), N1 + (P <  0.001), M1 (P =  0.045) and TNM stage III + (P <  0.001) tumours. The MTV/ADC_min ratio exhibited the highest area under the receiver operating characteristic curve (AUROC) for predicting M1 and advanced TNM stage tumours. Multivariate analysis for progression-free survival (PFS) and overall survival (OS) showed that a larger MTV/ADC_min was associated with a shorter PFS and OS (P = 0.024 and 0.046, respectively).

CONCLUSION

The imaging biomarkers in integrated PET/MRI may predict clinical stage and survival in patients with oesophageal SCC.

Volumetric histogram analysis of apparent diffusion coefficient for predicting pathological complete response and survival in esophageal cancer patients treated with chemoradiotherapy

BACKGROUND

The purpose of the study was to evaluate whether histogram analysis of apparent diffusion coefficient (ADC) can predict pathological complete response (pCR) and survival in patients with esophageal squamous cell carcinoma (ESCC) after chemoradiotherapy (CRT).

METHODS

We retrospectively identified 58 patients with ESCC who underwent surgery after CRT between 2007 and 2016. Associations of pretreatment histogram derived ADC parameters with pathological response and survival were analyzed.

RESULTS

Tumors achieved pCR (10 patients, 17.2%) showed significant lower ADC, higher kurtosis, and higher skewness than those of non-pCR (p = 0.005, 0.007, <0.001, respectively). Receiver operating characteristics analysis demonstrated skewness was the best predictor for pCR (AUC = 0.86), with a cut off value of 0.50 (accuracy, 86.2%). In Kaplan-Meier analysis, patients with higher skewness tumors (≥0.50) showed a significantly better recurrence free survival (p = 0.032, log-rank).

CONCLUSIONS

Histogram analysis of ADC can enable prediction of pCR and survival in ESCC patients treated with preoperative CRT.

A SHORT SUMMARY

ADC histogram analysis can be an imaging biomarker for esophageal cancer patients treated with CRT.

Imaging biomarkers for the treatment of esophageal cancer

Esophageal cancer is known as one of the malignant cancers with poor prognosis. To improve the outcome, combined multimodality treatment is attempted. On the other hand, advances in genomics and other “omic” technologies are paving way to the patient-oriented treatment called “personalized” or “precision” medicine. Recent advancements of imaging techniques such as functional imaging make it possible to use imaging features as biomarker for diagnosis, treatment response, and prognosis in cancer treatment. In this review, we will discuss how we can use imaging derived tumor features as biomarker for the treatment of esophageal cancer.

Imaging biomarkers in upper gastrointestinal cancers

In parallel with the increasingly widespread availability of high performance imaging platforms and recent progresses in pathobiological characterisation and treatment of gastrointestinal malignancies, imaging biomarkers have become a major research topic due to their potential to provide additional quantitative information to conventional imaging modalities that can improve accuracy at staging and follow-up, predict outcome, and guide treatment planning in an individualised manner. The aim of this review is to briefly examine the status of current knowledge about imaging biomarkers in the field of upper gastrointestinal cancers, highlighting their potential applications and future perspectives in patient management from diagnosis onwards.

High expression of uPA related to p38MAPK in esophageal cancer indicates poor prognosis

Background

The aim of the study was to investigate the relationship between urokinase-type plasminogen activator (uPA) and mitogen-activated protein kinase 38 (p38MAPK), and preliminarily analyze their relationship with clinical characteristics of esophageal cancer.

Materials and methods

Immunohistochemistry and Western blot were used to detect the expressions of uPA and p38MAPK in patients with esophageal cancer. The relationship between them and clinicopathological features was analyzed by chi-squared test and Spearman correlation. Prognosis was performed using Kaplan–Meier and Cox proportional hazard models analysis.

Results

The expressions of uPA and p38MAPK proteins were significantly higher in esophageal squamous cell carcinoma or adenocarcinoma than in normal esophageal mucosa tissue (both P<0.0001). The expression of uPA was significantly correlated with the depth of invasion of esophageal cancer (P=0.0067), tumor size (P=0.0364), and pathological stage (P<0.0001); p38MAPK expression vs esophageal cancer tissue type (P=0.0043), esophageal cancer infiltration depth (P=0.0097), tumor size (P=0.0015), and pathological stage (P<0.0001). Both were not significantly associated with lymph node staging, gender, age, and esophageal cancer histological type. There was a positive correlation between uPA and p38MAPK expressions (r=0.7301, P=0.0104). Kaplan–Meier analysis showed that the overall survival time of patients with positive expression of uPA or p38MAPK protein was significantly shorter, and the time of recurrence or metastasis of esophageal cancer was significantly earlier in patients with uPA-positive expression. Multivariate analysis of Cox model showed that uPA, p38MAPK, and pathological staging were independent factors influencing survival.

Conclusion

The expressions of uPA and p38MAPK may play an important role in the progression of esophageal cancer, and there is a close relationship between the two proteins, which may be one of the prognostic indicators.