Diagnostic Performance of MRI for Esophageal Carcinoma: A Systematic Review and Meta-Analysis

Advances in the Imaging of Esophageal and Gastroesophageal Junction Malignancies

Accurate imaging is key for the diagnosis and treatment of esophageal and gastroesophageal junction cancers . Current imaging modalities, such as computed tomography (CT) and 18F-FDG (2-deoxy-2-[18F]fluoro-D-glucose) positron emission tomography (PET)/CT, have limitations in accurately staging these cancers. MRI shows promise for T staging and residual disease assessment. Novel PET tracers, like FAPI, FLT, and hypoxia markers, offer potential improvements in diagnostic accuracy. 18F-FDG PET/MRI combines metabolic and anatomic information, enhancing disease evaluation. Radiomics and artificial intelligence hold promise for early detection, treatment planning, and response assessment. Theranostic nanoparticles and personalized medicine approaches offer new avenues for cancer therapy.

Esophageal cancer: Treatment advances and need for screening

ABSTRACT

Esophageal cancer is a challenging malignancy that often is diagnosed in advanced stages, resulting in a poor prognosis. This article provides a comprehensive review of the two main types of esophageal cancer, esophageal squamous cell carcinoma and esophageal adenocarcinoma, and reviews epidemiology, risk factors, pathogenesis, diagnostic modalities, staging systems, and established and emerging treatments. Recent advancements in treatment for resectable and unresectable esophageal cancer also are explored. These include immunotherapy, targeted therapy, sentinel lymph node mapping, radiogenomics, palliative measures, and screening measures.

Prospective evaluation of MR-TRG (Tumor Regression Grade) in esophageal cancer after neo-adjuvant therapy: Preliminary results

PURPOSE

To develop MRI-based criteria to assess tumor response to neoadjuvant therapies (NAT) of esophageal cancers (EC) and to evaluate its diagnostic performance in predicting the pathological Tumor Regression Grade (pTRG).

METHOD

From 2018 to 2022, patients with newly diagnosed locally advanced EC underwent MRI examinations for initial staging and restaging after NAT. Magnetic Resonance TRG (MR-TRG), equivalent to the Mandard and Becker classifications, were developed and independently assessed by two radiologists, blinded to pTRG, using T2W and DW-MR Images. All patients underwent surgery and benefited from a blinded pTRG evaluation by two pathologists. The agreement between readers and between MR-TRG and pTRG were assessed with Cohen's Kappa. The correlation of MR-TRG and pTRG was determined using Spearman's correlation.

RESULTS

28 patients were included. Interrater agreement was substantial between radiologists, improved when grouping grade 1 and 2 (κ = 0.78 rose to 0,84 for Mandard and 0.68 to 0,78 for Becker score). Agreement between pTRG and MR-TRG was moderate with a percentaged agreement (p) = 87.5 %, kappa (κ) = 0.54 and p = 83.3 %, κ = 0.49 for Mandard and Becker, respectively. Agreement was improved to substantial when grouping grades 1-2 for Mandard and 1a-1b for Becker with p = 89.3 %, κ = 0.65 and p = 85.2 %, κ = 0.65 respectively. Sensitivity and specificity of MR-TRG in predicting pTRG were 88.2 % and 72.7 % for Mandard system (scores 1-2 versus 3-5), and 83.3 % and 80 % for Becker system (scores 1a-1b versus 2-3).

CONCLUSION

A substantial agreement between MR-TRG and pTRG was achieved when grouping grade 1-2. Hence, MR-TRG could be used as a surrogate of complete and near-complete pTRG.

MR radiomics predicts pathological complete response of esophageal squamous cell carcinoma after neoadjuvant chemoradiotherapy: a multicenter study

BACKGROUND

More than 40% of patients with resectable esophageal squamous cell cancer (ESCC) achieve pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT), who have favorable prognosis and may benefit from an organ-preservation strategy. Our study aims to develop and validate a machine learning model based on MR radiomics to accurately predict the pCR of ESCC patients after nCRT.

METHODS

In this retrospective multicenter study, eligible patients with ESCC who underwent baseline MR (T2-weighted imaging) and nCRT plus surgery were enrolled between September 2014 and September 2022 at institution 1 (training set) and between December 2017 and August 2021 at institution 2 (testing set). Models were constructed using machine learning algorithms based on clinical factors and MR radiomics to predict pCR after nCRT. The area under the curve (AUC) and cutoff analysis were used to evaluate model performance.

RESULTS

A total of 155 patients were enrolled in this study, 82 in the training set and 73 in the testing set. The radiomics model was constructed based on two radiomics features, achieving AUCs of 0.968 (95%CI 0.933-0.992) in the training set and 0.885 (95%CI 0.800-0.958) in the testing set. The cutoff analysis resulted in an accuracy of 82.2% (95%CI 72.6-90.4%), a sensitivity of 75.0% (95%CI 58.3-91.7%), and a specificity of 85.7% (95%CI 75.5-96.0%) in the testing set.

CONCLUSION

A machine learning model based on MR radiomics was developed and validated to accurately predict pCR after nCRT in patients with ESCC.

Decoding tumor stage by peritumoral and intratumoral radiomics in resectable esophageal squamous cell carcinoma

PURPOSE

To evaluate the potential application of radiomics in predicting Tumor-Node-Metastasis (TNM) stage in patients with resectable esophageal squamous cell carcinoma (ESCC).

METHODS

This retrospective study included 122 consecutive patients (mean age, 57 years; 27 women). Corresponding tumor of interest was identified on axial arterial-phase CT images with manual annotation. Radiomics features were extracted from intra- and peritumoral regions. Features were pruned to train LASSO regression model with 93 patients to construct a radiomics signature, whose performance was validated in a test set of 29 patients. Prognostic value of radiomics-predicted TNM stage was estimated by survival analysis in the entire cohort.

RESULTS

The radiomics signature incorporating one intratumoral and four peritumoral features was significantly associated with TNM stage. This signature discriminated tumor stage with an area under curve (AUC) of 0.823 in the training set, with similar performance in the test set (AUC 0.813). Recurrence-free survival (RFS) was significantly different between different radiomics-predicted TNM stage groups (Low-risk vs high-risk, log-rank P = 0.004). Univariate and multivariate Cox regression analyses revealed that radiomics-predicted TNM stage was an independent preoperative factor for RFS.

CONCLUSIONS

The proposed radiomics signature combing intratumoral and peritumoral features was predictive of TNM stage and associated with prognostication in ESCC.

MR imaging characteristics of different pathologic subtypes of esophageal carcinoma

OBJECTIVES

To describe the specific MRI characteristics of different pathologic subtypes of esophageal carcinoma (EC) METHODS: This prospective study included EC patients who underwent esophageal MRI and esophagectomy between April 2015 and October 2021. Pathomorphological characteristics of EC such as localized type (LT), ulcerative type (UT), protruding type (PT), and infiltrative type (IT) were assessed by two radiologists relying on the imaging characteristics of tumor, especially the specific imaging findings on the continuity of the mucosa overlying the tumor, the opposing mucosa, mucosa linear thickening, and transmural growth pattern. Intraclass correlation coefficients (ICC) were calculated for the consistency between two readers. The associations of imaging characteristics with different pathologic subtypes were assessed using multilogistic regression model (MLR).

RESULTS

A total of 201 patients were identified on histopathology with a high inter-reader agreement (ICC = 0.991). LT showed intact mucosa overlying the tumor. IT showed transmural growth pattern extending from the mucosa to the adventitia and a "sandwich" appearance. The remaining normal mucosa on the opposing side was linear and nodular in UT. PT showed correlation with T1 staging and grade 1; IT showed correlation with T3 staging and grades 2-3. Four MLR models showed high predictive performance on the test set with AUCs of 0.94 (LT), 0.87 (PT), 0.96 (IT), and 0.97 (UT), respectively, and the predictors that contributed most to the models matched the four specific characteristics.

CONCLUSIONS

Different pathologic subtypes of EC displayed specific MR imaging characteristics, which could help predict T staging and the degree of pathological differentiation.

CLINICAL RELEVANCE STATEMENT

Different pathologic subtypes of esophageal carcinoma displayed specific MR imaging characteristics, which correspond to differences in the degree of differentiation, T staging, and sensitivity to radiotherapy, and could also be one of the predictive factors of cause-specific survival and local progression-free rates.

KEY POINTS

Different types of EC had different characteristics on MR images. A total of 91/95 (96%) LTEC showed intact mucosa over the tumor, while masses or nodules are specific to PTEC; 21/27 (78%) ITEC showed a "sandwich" sign; and 33/35 (60%) UTEC showed linear and nodular opposing mucosa. In the association of tumor type with degree of differentiation and T staging, PTEC was predominantly associated with T1 and grade 1, and ITEC was associated with T3 and grades 2-3, while LTEC and UECT were likewise primarily linked with T2-3 and grades 2-3.

Esophageal cancer T-staging on MRI: A preliminary study using cine and static MR sequences

OBJECTIVES

To evaluate the added value of cine MR in addition to static MRI for T-Staging assessment of esophageal cancer (EC).

MATERIALS AND METHODS

This prospective monocentric study included 54 patients (mean age 66.3 ± 9.4 years, 46 men) with histologically proven EC. They underwent MRI on a 3 T-scanner in addition to the standard workup. Acquisitions included static and cine sequences (steady-state-free-precession and real-time True-FISP during water ingestion). Three radiologists independently assessed T-staging and diagnosis confidence by reviewing (1) static sequences (S-MRI) and (2) adding cine sequences (SC-MRI). Inter-reader agreement was performed. MRI T-staging was correlated to reference standard T-staging (histopathology or consensus on endoscopic ultrasonography and imaging findings) and to clinical outcome by log-rank test.

RESULTS

Both S-MRI and SC-MRI T-staging showed a significant correlation with reference T-staging (rs = 0.667, P < 0.001). SC-MRI showed a slightly better performance in distinguishing T1-T3 from T4 with a sensitivity, specificity and AUC of 76.5% (95% CI: 50.1-93.2), 83.8% (68-93.8) and 0.801 (0.681-0.921) vs 70.6% (44-89.7), 83% (68-93.8) and 0.772 (0.645-0.899) for S-MRI. Compared to S-MRI, SC-MRI increased inter-reader agreement for T4a and T4b (κ = 0.403 and 0.498) and T-staging confidence.

CONCLUSION

MRI is accurate for T-staging of EC. The addition of cine sequences allows better differentiation between T1-T3 and T4 tumors with increased diagnostic confidence and inter-reader agreement.

A CT-Based Radiomics Nomogram Model for Differentiating Primary Malignant Melanoma of the Esophagus from Esophageal Squamous Cell Carcinoma

Objective

The diagnosis of primary malignant melanoma of the esophagus (PMME) before treatment is essential for clinical decision-making. However, PMME may be misdiagnosed as esophageal squamous cell carcinoma (ESCC) sometimes. This research is aimed at devising a radiomics nomogram model of CT for distinguishing PMME from ESCC.

Methods

In this retrospective analysis, 122 individuals with proven pathologically PMME (n = 28) and ESCC (n = 94) were registered from our hospital. PyRadiomics was applied to derive radiomics features from plain and enhanced CT images after resampling image into an isotropic resolution of 0.625 × 0.625 × 0.625 mm³. The diagnostic efficiency of the model was evaluated by an independent validation group.

Results

For the purpose of differentiation between PMME and ESCC, a radiomics model was constructed using 5 radiomics features obtained from nonenhanced CT and 4 radiomics features derived from enhanced CT. A radiomics model including multiple radiomics features showed excellent discrimination efficiency with AUCs of 0.975 and 0.906 in the primary and validation cohorts, respectively. Then, a radiomics nomogram model was developed. The decision curve analysis has shown remarkable performance of this nomogram model for distinguishing PMME from ESCC.

Conclusions

The proposed radiomics nomogram model based on CT could be used for distinguishing PMME from ESCC. Moreover, this model also contributed to helping clinicians determine an appropriate treatment strategy for esophageal neoplasms.

Aorta and tracheobronchial invasion in esophageal cancer: comparing diagnostic performance of 3.0-T MRI and CT

OBJECTIVES

To compare between the diagnostic performance of 3.0-T MRI and CT for aorta and tracheobronchial invasion in patients with esophageal cancer (EC).

METHODS

We prospectively included patients with pathologically confirmed EC from November 2018 to June 2021, who had baseline stage of T3-4N0-2M0 and restaging after neoadjuvant chemotherapy. All patients underwent contrast-enhanced CT and MRI of the thorax. Two independent blinded radiologists scored image quality and the presence of invasion. Agreements between the two readers were calculated using kappa test. The sensitivity, specificity, accuracy, positive predict value (PPV), and negative predict value (NPV) of MRI and CT in evaluating invasion were calculated. The net reclassification index (NRI) was used to evaluate the change in the number of patients correctly classified by MRI and CT.

RESULTS

A total of 70 patients (64.8 ± 9.0 years; 53 men) were enrolled. Inter-reader agreements of image quality scores and presence of invasion by MRI and CT between the two readers were almost perfect (kappa > 0.80). The accuracy of MRI in evaluating thoracic aorta invasion was significantly higher than that of CT (reader 1: 90.0% vs. 71.4%; reader 2: 92.9% vs. 70.0%, respectively), and the accuracy of MRI in evaluating tracheobronchial invasion also was significantly higher than that of CT (reader 1: 92.9% vs. 72.9%; reader 2: 95.7% vs. 70.0%, respectively). NRI values were positive in both the evaluation of aorta and tracheobronchial invasion.

CONCLUSIONS

The accuracy of 3-T MRI in determining thoracic aorta and tracheobronchial invasion is significantly higher than that of CT.

KEY POINTS

• 3.0-T MRI was significantly more accurate than CT in assessing invasion of the thoracic aorta in patients with esophageal cancer. • 3.0-T MRI was also significantly more accurate than CT in assessing tracheobronchial invasion in patients with esophageal cancer. • 3.0-T MRI has a higher diagnostic performance than CT in evaluating patients with suspected aortic or tracheobronchial invasion in esophageal cancer.

State-of-the-art imaging in oesophago-gastric cancer

Radiological investigations are essential in the management of oesophageal and gastro-oesophageal junction cancers. The current multimodal combination of CT, 18F-fluorodeoxyglucose positron emission tomography combined with CT (PET/CT) and endoscopic ultrasound (EUS) has limitations, which hinders the prognostic and predictive information that can be used to guide optimum treatment decisions. Therefore, the development of improved imaging techniques is vital to improve patient management. This review describes the current evidence for state-of-the-art imaging techniques in oesophago-gastric cancer including high resolution MRI, diffusion-weighted MRI, dynamic contrast-enhanced MRI, whole-body MRI, perfusion CT, novel PET tracers, and integrated PET/MRI. These novel imaging techniques may help clinicians improve the diagnosis, staging, treatment planning, and response assessment of oesophago-gastric cancer.

Quantitative RECIST derived from multiparametric MRI in evaluating response of esophageal squamous cell carcinoma to neoadjuvant therapy

OBJECTIVE

To develop a quantitative Response Evaluation Criteria in Solid Tumors (qRECIST) for evaluating response to neoadjuvant therapy (nT) in ESCCs relying on multiparametric (mp) MRI.

METHODS

Patients with cT2-T4a/N0-N3/M0 ESCC undergoing pre-nT and post-nT esophageal mpMRI before radical resection were prospectively included. Images were reviewed by two experienced radiologists. qRECIST was redefined using four methods including conventional criterion (cRECIST) and three model-dependent RECIST relying on quantitative MRI measurements at pre-nT, post-nT, and delta pre-post nT, respectively. Pathological tumor regression grades (TRGs) were used as a reference standard. The rates of agreement between four qRECIST methods and TRGs were determined with a Cronbach's alpha test, area under the curve (AUC), and a diagnostic odds ratio meta-analysis.

RESULTS

Ninety-one patients were enrolled. All four methods revealed high inter-reader agreements between the two radiologists, with a Kappa coefficient of 0.96, 0.87, 0.88, and 0.97 for cRECIST, pre-nT RECIST, post-nT RECIST, and delta RECIST, respectively. Among them, delta RECIST achieved the highest overall agreement rate (67.0% [61/91]) with TRGs, followed by post-nT RECIST (63.8% [58/91]), cRECIST (61.5% [56/91]), and pre-nT RECIST (36.3% [33/91]). Especially, delta RECIST achieved the highest accuracy (97.8% [89/91]) in distinguishing responders from non-responders, with 97.3% (34/35) for responders and 98.2% (55/56) for non-responders. Post-nT RECIST achieved the highest accuracy (93.4% [85/91]) in distinguishing complete responders from non-pCRs, with 77.8% (11/18) for pCRs and 94.5% (69/73) for non-pCRs.

CONCLUSION

The qRECIST with mpMRI can assess treatment-induced changes and may be used for early prediction of response to nT in ESCC patients.

KEY POINTS

• Quantitative mpMRI can reliably assess tumor response, and delta RECIST model had the best performance in evaluating response to nT in ESCCs, with an AUC of 0.98, 0.95, 0.80, and 0.82 for predicting TRG0, TRG1, TRG2, and TRG3, respectively. • In distinguishing responders from non-responders, the rate of agreement between delta RECIST and pathology was 97.3% (34/35) for responders and 98.2% (55/56) for non-responders, resulting in an overall agreement rate of 97.8% (89/91). • In distinguishing pCRs from non-pCR, the rate of agreement between MRI and pathology was 77.8% (11/18) for pCRs and 94.5% (69/73) for non- pCRs, resulting in an overall agreement rate of 91.2% (83/91).

Approach to Localized Squamous Cell Cancer of the Esophagus

OPINION STATEMENT

Esophageal cancer is a leading cause of cancer deaths worldwide, with an increasing incidence in recent decades. The majority of esophageal cancers are squamous cell carcinoma. The 5-year survival rate of esophageal squamous cell carcinoma (ESCC) is poor, and there remains globally a pressing need for novel treatments that improve patient outcomes and quality of life. In this review, we discuss management of localized ESCC with an update on relevant newly published literature, including targeted therapy and novel biomarkers. The standard treatment approach for locally advanced, resectable ESCC is currently chemoradiation with or without surgery. Here we discuss different approaches to endoscopic resection, surgery, and radiation therapy. Although the typical chemotherapy regimen is a combination of a platinum with a fluoropyrimidine or paclitaxel, different regimens are being evaluated. With the landscape of immunotherapy rapidly evolving, at the forefront of new treatments for ESCC is immunotherapy and other targeted agents. Ultimately, the treatment approach should be individualized to each patient.

Application Value of MRI Combined with MSCT in Diagnosis and Staging of Colon Carcinoma

Objective

To clarify the application value of magnetic resonance imaging (MRI) combined with multislice spiral computed tomography (MSCT) in the diagnosis and staging of colon carcinoma (CC).

Methods

A total of 103 patients with histopathologically diagnosed CC were enrolled. Patient clinical and imaging data were collected, and MRI and MSCT images were analyzed to assess the accuracy of MRI, MSCT, and their combination in diagnosing tumor (T) staging of CC.

Results

Among the 103 cases of histopathologically diagnosed CC, 26 cases (25.24) were in stage T1-2, 72 cases (69.90) were in stage T3, and 5 cases (4.85) were in stage T4. The accuracy of MRI in diagnosing stage T1-2, T3, and T4 was 80.77%, 88.89%, and 60.00%, respectively, with an average of 76.55%. The accuracy rates of MSCT in diagnosing T1-2, T3, and T4 stages were 73.08%, 90.27%, and 60.00%, respectively, with an average of 74.45%. The accuracy rates of MRI+MSCT in diagnosing T1-2, T3, and T4 were 88.46%, 95.83%, and 80.00%, respectively, with an average of 88.10%.

Conclusions

Compared with single use of MRI or MSCT, MRI+MSCT provides accurate imaging data with higher accuracy, which is more helpful for the T-staging evaluation of CC.

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.

Molecular Imaging-Guided Sonodynamic Therapy

Low-intensity ultrasound-triggered sonodynamic therapy (SDT) is a promising noninvasive therapeutic modality due to its strong tissue penetration ability. In recent years, with the development of nanotechnology, nanoparticle-based sonosensitizer-mediated SDT has been widely investigated. With the increasing demand for precise and personalized treatment, abundant novel sonosensitizers with imaging capabilities have been developed for determining the optimal therapeutic window, thus significantly enhancing treatment efficacy. In this review, we focus on the molecular imaging-guided SDT. The prevalent mechanisms of SDT are discussed, including ultrasonic cavitation, sonoluminescence, reactive oxygen species, and mechanical damage. In addition, we introduce the major molecular imaging techniques and the design principles based on nanoparticles to achieve efficient imaging. Furthermore, the imaging-guided SDT for the treatment of cancer, bacterial infections, and vascular diseases is summarized. The ultimate goal is to design more effective imaging-guided SDT modalities and provide novel ideas for clinical translation of SDT.