Next Article in Journal
Utility of Coronary Computed Tomography Angiography in Patients Undergoing Transcatheter Aortic Valve Implantation: A Meta-Analysis and Meta-Regression Based on Published Data from 7458 Patients
Next Article in Special Issue
VAC-Stent in the Treatment of Post-Esophagectomy Anastomotic Leaks: A New “Kid on the Block” Who Marries the Best of Old Techniques—A Review
Previous Article in Journal
Autophagy-Related Gene ATG7 Polymorphism Could Potentially Serve as a Biomarker of the Progression of Atrophic Gastritis
Previous Article in Special Issue
Skeletal Muscle Quality and Quantity Affect Prognosis after Neoadjuvant Chemotherapy with a Triple Regimen of Docetaxel/Cisplatin/5-FU in Patients with Esophageal Cancer
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
JCM
Volume 13
Issue 2
10.3390/jcm13020632
jcm-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Novel Advances in Qualitative Diagnostic Imaging for Decision Making in Multidisciplinary Treatment for Advanced Esophageal Cancer

by
Shinichi Okazumi
1,
Gaku Ohira
2,*,
Koichi Hayano
2,
Tomoyoshi Aoyagi
2,
Shunsuke Imanishi
2 and
Hisahiro Matsubara
2
1
Department of Surgery, Toho University Sakura Medical Center, Chiba 285-8741, Japan
2
Frontier Surgery, Graduate School of Medicine, Chiba University, Chiba 260-8670, Japan
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2024, 13(2), 632; https://doi.org/10.3390/jcm13020632
Submission received: 6 November 2023 / Revised: 18 January 2024 / Accepted: 18 January 2024 / Published: 22 January 2024
(This article belongs to the Special Issue Esophageal Cancer: Diagnosis and Treatment)
Browse Figures
Versions Notes

Abstract

:
Background: Recently, neoadjuvant therapy and the succeeding surgery for advanced esophageal cancer have been evaluated. In particular, the response to the therapy has been found to affect surgical outcomes, and thus a precise evaluation of treatment effect is important for this strategy. In this study, articles on qualitative diagnostic modalities to evaluate tumor activities were reviewed, and the diagnostic indices were examined. Methods: For prediction of the effect, perfusion CT and diffusion MRI were estimated. For the histological response evaluation, perfusion CT, diffusion-MRI, and FDG-PET were estimated. For downstaging evaluation of T4, tissue-selective image reconstruction using enhanced CT was estimated and diagnostic indices were reviewed. Results: The prediction of the effect using perfusion CT with ‘pre CRT blood flow’ and diffusion MRI with ‘pre CRT ADC value’; the estimation of the histological response using perfusion CT with ‘post CRT blood flow reduction, using diffusion MRI with ‘post CRT ADC increasing’, and using FDG-PET with ‘post CRT SUV reduction’; and the downstaging evaluation of T4 using CT image reconstruction with ‘fibrous changed layer’ were performed well, respectively. Conclusions: Qualitative imaging modalities for prediction or response evaluation of neoadjuvant therapy for progressive esophageal cancer were useful for the decision making of the treatment strategy of the multidisciplinary treatment.

1. Introduction

Recently, in the treatment of advanced esophageal cancer, evidence for combined-modality therapy has been obtained, and the usefulness of neoadjuvant therapy [1,2] and conversion surgery has been reported [3,4]. Neoadjuvant therapy is known to improve the results of surgery for advanced esophageal cancer. In particular, neoadjuvant chemoradiotherapy (NACRT) showed a better prognosis than chemotherapy [5,6,7,8]. When a histologically effective response is obtained, the presence of a good response has been shown to significantly affect the resection rate [9] and the long-term prognosis [10,11]; thus, precise evaluation has become more important for determining the treatment strategy.
On the other hand, if we could predict sensitivity before neoadjuvant therapy, the treatment plan could be made with higher certainty. Therefore, the diagnostic aims when considering the neoadjuvant strategy are predicting the response before initiating therapy, evaluating the response after therapy, and assessing R0 surgical resectability.
Given this background, a qualitative diagnostic method to evaluate tumor activity would be useful. Tumors show many physiological or biochemical activities, such as increased perfusion with angiogenesis [12,13], decreased diffusion and heterogeneity with cellularity, stroma or necrosis, and increased glucose metabolism with proliferative activity. In recent years, blood flow evaluation using perfusion CT or dynamic contrast-enhanced (DCE) MRI, diffusion evaluation using diffusion MRI, glucose metabolism evaluation using FDG-PET, and tissue-selective contrast-enhanced CT reconstruction have been developed and reported as qualitative evaluations and as biomarkers that can be used to predict and evaluate treatment response [14]. The diagnostic procedures are independent of tumor shape and changes in metrics.

2. Material and Methods

In this article, studies regarding these novel qualitative diagnostic procedures were reviewed. We searched papers on Pubmed with the key words ‘esophageal cancer’, ‘neoadjuvant chemoradiotherapy’, ‘diagnostic imaging’, and ‘response evaluation’ from 2006 to 2023, and we selected papers presenting results of comparisons between a diagnostic imaging evaluation method and histologic response investigated using surgical specimen after neoadjuvant treatment. And the future of qualitative diagnostic assessment for neo- adjuvant strategy was discussed according to the diagnostic aims, respectively. The criteria of ‘advanced cancer’ referred to tumor depth over T2, and that of ‘responder’ was of histological regression after neoadjuvant treatment over 50%. Our clinical images for the qualitative diagnosis of cases with advanced esophageal cancer during treatment are shown as examples in Figure 1, Figure 2 and Figure 3 and the methods of each imaging are described below.
Perfusion imaging: Using dynamic contrast-enhanced (DCE)-CT, the contrast medium (40 mL/body/8 s) was administrated and scanned using multi-detector CT (GE light speed ultra) continuously for 30 s at the tumor section and the tumor part perfusion was calculated with the apparatus.
Diffusion imaging: Tumor diffusion was evaluated using the index of ADC (apparent diffusion coefficient) of the tumor region obtained at b = 1000 using 1.5T-MRI (Philips Achiva, Phlips Japan, Tokyo, Japan).

3. Results

3.1. Response Prediction before Neoadjuvant Therapy

A highly detailed prediction of treatment outcome requires evaluation of the physiological or biochemical characteristics of the tumor, which must be considered when selecting the drug delivery system or irradiation conditions. Tumors show angiogenesis with increased VEGF, which can be seen through evaluation of perfusion status, or stromal changes, which can be seen through evaluation of diffusion status [15]. Therefore, qualitative imaging modalities such as perfusion-CT or diffusion-MRI can show the dynamics of blood flow or diffusion of the tumor and surrounding tissue, which are considered useful for the prediction [16,17]. Table 1 shows the reported modalities and their indices for the prediction of the treatment effect. Most of the reported subjects were cases with esophageal squamous cell carcinoma. The usefulness of each respective modality is discussed below.
Perfusion analysis: It was thought that the high blood flow presented advantages with respect to pharmacokinetics or oxygenation to obtain a good pathological response. Perfusion-CT is a method that shows tumor tissue hemodynamics [18,19] (Figure 1). The tumor blood flow after CRT and the ◿blood flow could be evaluated using this modality. And the predictive ability of this method has also been reported. The quantity of tumor blood flow before treatment reflects the degree of response. Hayano et al. [20], Makari [21], and Li [22] reported that higher tumor blood flow could be the index for predicting responders. On the other hand, DCE-MRI also provides perfusion images. In the analysis of DCE-MRI, the Ktrans value is used as an index that reflects tissue permeability and blood flow. Lei et al. [23] and Ye et al. [24] reported that the pre-treatment Ktrans value was significantly higher in complete responders and could be a response predictor [25].
Diffusion analysis: Tumors are considered to show trends in their diffusion status due to their microvessels and stromal characteristics [14]. Diffusion-MRI is a method to calculate the diffusion dynamics of tissue through imaging (Figure 2). According to the treatment effect, the apparent diffusion coefficient (ADC) is a quantitative measure of the state of diffusion. ADC value was reported to be inversely correlated to the tissue VEGF expression [14,26] or tumor stromal density [14]. Therefore, it could reflect the drug delivery or radiation circumstance and was expected to be a predictive marker of treatment response [26]. It has been reported in several articles that the diffusion of the tumor before treatment correlates with the degree of response to CRT [24,26,27,28]. Aoyagi et al. [27] described that the susceptibility to treatment could be predicted using this method, with ADC > 1.1 identifying responders, but no consensus was reached regarding the concept and index value for the prediction of response. Li et al. [29] speculated that tumors with high necrosis might have higher ADC values and that they would be associated with poor therapy outcomes. Hirata et al. reported that a high ADC value was related to a lower response [30].
Table 1. Articles on imaging biomarkers and their indices predicted the histological effect of neoadjuvant therapy before treatment for esophageal cancer.
Table 1. Articles on imaging biomarkers and their indices predicted the histological effect of neoadjuvant therapy before treatment for esophageal cancer.
AuthorYearModalityPatientsPathologyIndices
Hayano et al. [20]2007Perfusion-CT31SCChigh pre-CRT blood flow > 50 (mL/min/100 g)
Makari et al. [21]2007Perfusion-CT55SCChigh pre-CRT blood flow > 70 (mL/min/100 g)
Li [22]2015Perfusion-CT55SCChigh pre-CRT blood flow > 36.1 (mL/min/100 g)
Lei et al. [23]2015DCE-MRI25SCChigh pre-CRT Ktrans value
Ye et al. [24]2018DCE-MRI237AC, SCChigh pre-CRT Ktrans value
Aoyagi et al. [27]2011DW-MRI80SCChigh pre CRT ADC value > 1.1 (10−3 mm2/s)
Ye et al. [24]2018DW-MRI237AC, SCChigh pre-CRT ADC value
Guo et al. [28]2018DW-MRI78SCChigh pre-CRT ADC value
Cong et al. [26]2019DW-MRI52SCChigh pre-CRT ADC value
Hirata et al. [30]2020DW-MRI58SCClow pre-CRT ADC value
DCE: dynamic contrast-enhanced MRI; DW: diffusion-weighted; ADC: apparent diffusion coefficient; SCC: squamous cell carcinoma; AC: adenocarcinoma.

3.2. Response Evaluation Reflecting the Degree of Pathological Regression after Treatment

In neoadjuvant therapy, when a histologically effective response was obtained, the prognosis after surgery was significantly better [31,32]. Therefore, it becomes essential to assess the degree of response after treatment accurately to determine whether to proceed with surgical resection. Tumor perfusion, diffusion, glucose metabolism, and tissue heterogeneity and their relationships have been found to change according to the histologic response to therapy. Table 2 shows the reported modalities and their indices for the evaluation of the treatment effect. The reported subjects were cases with esophageal squamous cell carcinoma or adenocarcinoma. Usefulness of respective modality is discussed below.
Perfusion analysis: It has been reported that, on perfusion CT, the tumor part shows a significant blood flow decrease with treatment, and the images reflect the histologic response. Significant tumor blood flow decreases were seen in responders to neoadjuvant chemoradiotherapy compared with non-responders (Figure 1), and responders were diagnosed using this index of tumor blood flow decrease. Hayano et al. [33] reported an index of a 15% decrease in tumor blood flow after treatment, which reflected histological response, and Stefanovic et al. reported [34] a post-CRT blood flow < 30 (mL/min/100 g) as a response.
Diffusion analysis: A consensus was seen in several reports that tumor diffusion had been shown to have a tendency to increase after treatment according to the degree of the histologic response (Figure 3), and ◿ADC (pre–post) was a good marker which reflected histologic response [17,35,36,37,38]. In our results obtained via diffusion-weighted imaging with 1.5T-MRI for advanced esophageal cancer during the treatment of CRT, the responder group showed a significant earlier increase in the ADC value at the irradiation dose of 20 Gy than the non-responder group (Figure 3), and it seemed that an evaluation of the early treatment effect would be possible. Moreover, the possibility of its evaluation in the early treatment course was also recommended in several articles [35,37,39]. Imanishi et al. [35] reported that responders to CRT showed an ADC increase of 15% at 20 Gy and 40% at 40 Gy. Guo et al. [28], Vollenbrock et al. [40], and Borggreve [39] reported that the optimal timing for early prediction of the effect was 2 weeks after the beginning of treatment. Vollenbrock et al. [40] described that the ADC increase with treatment effect was due to the early effect of radiotherapy on the tumor microenvironment inducing tumor necrosis with a loss of cell membrane, resulting in an increase in the ADC.
Glucose metabolism analysis: FDG-PET is a technique for imaging the state of glucose metabolism, which reflects tumor proliferative activity, and the degree of glucose integration is assessed with the standardized uptake value (SUV) calculated from an image [41]. Evaluations of the mean uptake of the tumor and of total uptake are possible, and the histologic responses have been reported to correlate with the mean uptake [42,43]. As indices to identify responders, Higuchi et al. [44] reported post-treatment SUV < 2.5, and Swisher et al. [42] reported SUV < 3.1. Furthermore, through evaluation in the early treatment period, a prediction of the final effect was also considered possible. Otto et al. [45] assumed that a 35% decrease in accumulation two weeks after the start of chemotherapy for esophageal adenocarcinoma was a predictor of response. This occurred before the morphologic decrease in the tumor, which was thought to be due to decreased glucose metabolism prior to its morphologic decrease. In addition, the prognostic value of metastatic lymph node uptake after treatment, as well as the main tumor, was reported [46], and Yasuda et al. reported the prognostic value of residual lymph node uptake after treatment [47,48].
Heterogeneity analysis: Tumor heterogeneity has been reported to reflect malignancy or prognosis, and it has been studied through texture analysis using CT. It was reported that tumor texture showed a tendency to homogenize, decrease entropy, and increase uniformity after treatment [49,50,51,52]. When planning for conversion surgery, an evaluation of the heterogeneity of the effect on the tumor is needed to diagnose downstaging. If T4 status could be diagnosed as resolved, conversion surgery with R0 resection could be possible. For such a diagnostic aim, tissue-selective reconstruction of enhanced CT was applied to show the fibrous changes in the tumor due to treatment. In our study, contrast-enhanced CT (100 mL/body/30 s of contrast medium) was performed using multi-detector CT, and a depiction of the layer of connective tissue or adipose tissue between a tumor and adjacent organs was enabled through the contrast-enhanced CT image reconstruction method, which emphasizes the CT values of the tissue (Figure 4). It was found to be useful for the diagnosis of T4 cases. Furthermore, after treatment, the decrease in the CT level of the tumor has been found to correspond to the histologic response. In T4-diagnosed cases before treatment, the presence of a fibrotic change in the tumor and the emergence of a fibrous layer between the tumor and the adjacent organs after treatment have been reported to be evidence of downstaging that would permit conversion surgery with R0 resection [53].
Table 2. Articles of imaging biomarkers and their indices reflected the histological effect of neoadjuvant therapy after treatment for esophageal cancer.
Table 2. Articles of imaging biomarkers and their indices reflected the histological effect of neoadjuvant therapy after treatment for esophageal cancer.
AuthorYearModalityPatientsPathologyIndices
Evaluation after treatment
Hayano et al. [33]2014Perfusion-CT32SCCpre–post-CRT blood flow reduction > 15%
Stefanovic et al. [34]2015Perfusion-CT40SCCpost-CRT blood flow < 30 (ml/min/100 g)
Imanishi et al. [35]2013DW-MRI27SCC◿ADC (>40%)
Li et al. [38]2017DW-MRI28SCC◿ADC, post-CRT ADC
Cheng et al. [36]2018DW-MRI236AC, SCC◿ADC, post-CRT ADC
Heethuis et al. [37]2018DW-MRI45AC, SCC◿ADC (>75%)
Borggreve et al. [17]2019DW-MRI69AC, SCC◿ADC
Swisher et al. [42]2004FDG-PET103AC, SCCpost-CRT SUV (<3.1)
Higuchi et al. [44]2008FDG-PET50SCCpost-CRT SUV (<2.5)
Izumi et al. [46]2015FDG-PET73SCCpost-CRT SUVmax with T/N ratio
Boerggreve et al. [17]2019FDG-PET69AC, SCC◿SUV
Evaluation at the early treatment course
Imanishi et al. [35]2013DW-MRI27SCC◿ADC (>15%: 20Gy after beginning of CRT)
Guo et al. [28]2018DW-MRI78SCC, AC◿ADC (2 w after beginning of CRT)
Vollenblock et al. [40]2019DW-MRI 516AC, SCC◿ADC (2 w after beginning of CRT)
Borggreve et al. [39]2020DW-MRI24AC, SCC◿ADC (>36%: 2 w after beginning of CRT)
Ott et al. [45]2006FDG-PET65AC◿SUV (>35%: 2 W after beginning of CRT)
ADC: apparent diffusion coefficient; SUV: standardized uptake value; SCC: squamous cell carcinoma; AC: adenocarcinoma; CRT: chemoradiotherapy.

4. Discussions

The literature on the novel qualitative imaging modalities for the evaluation or prediction of histological effects after neoadjuvant therapy for progressive esophageal cancer, as well as downstaging evaluation for conversion surgery, was reviewed. Several investigations of the indices of the various modalities have been performed (Table 3). Perfusion CT and diffusion-MRI appear useful for prediction and effect evaluation during neoadjuvant treatment. Perfusion CT, diffusion-MRI, and FDG-PET reflect the histologic response and are useful for precise evaluation. Heterogeneity evaluation using tissue-selected image reconstruction with contrast-enhanced CT can help in the diagnosis of downstaging after chemoradiation, which supports decision making in conversion surgery.
These modalities with the indices were useful for decision making in multidisciplinary treatment at every treatment stage, not only to choose the most effective method but also to avoid invasive and non-effective ones. The limitation is that there were few choices for strategy decision making for the cases that show poor effect prediction. In the future, alternative neoadjuvant therapy for them besides chemo radiation should be found, and then qualitative imaging modalities would be more useful.

5. Conclusions

Qualitative imaging modalities using indices of the respective modalities for the prediction or evaluation of histological effects after neoadjuvant therapy for progressive esophageal cancer were novel and useful techniques for making decisions regarding the treatment strategy for advanced esophageal cancer at several stages of the multidisciplinary treatment. In the future, even in the cases that show poor effect prediction, an alternative neoadjuvant therapy besides chemoradiation should be found, and then the qualitative imaging modalities would be more useful.

Author Contributions

Conceptualization, S.O. and G.O.; methodology, S.O.; software, S.O.; validation, S.O., G.O. and H.M.; formal analysis, S.O.; investigation, K.H.; resources, T.A.; data curation, S.I.; writing—original draft preparation, S.O.; writing—review and editing, S.O.; visualization, S.O.; supervision, G.O.; project administration, H.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Ethical review and approval were waived for this study due to the review article.

Informed Consent Statement

Informed consent was obtained from all participants included in the study.

Data Availability Statement

The data used in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare that there are no conflicts of interest.

References

  1. Kumar, T.; Pai, E.; Singh, R.; Francis, N.J.; Pandey, M. Neoadjuvant strategies in resectable carcinoma esophagus: A meta-analysis of randomized trials. World J. Surg. Oncol. 2020, 18, 59. [Google Scholar] [CrossRef] [PubMed]
  2. Yang, H.; Liu, H.; Chen, Y.; Zhu, C.; Fang, W.; Yu, Z. Neoadjuvant Chemoradiotherapy Followed by Surgery Versus Surgery Alone for Locally Advanced Squamous Cell Carcinoma of the Esophagus (NEOCRTEC5010): A Phase III Multicenter, Randomized, Open-Label Clinical Trial. Clin. Oncol. 2018, 36, 2796–2803. [Google Scholar] [CrossRef]
  3. Terada, M.; Hara, H.; Daiko, H.; Mizusawa, J.; Kadota, T.; Hori, K. Phase III study of tri-modality combination therapy with induction docetaxel plus cisplatin and 5-fluorouracil versus definitive chemoradiotherapy for locally advanced unresectable squamous-cell carcinoma of the thoracic esophagus (JCOG1510, TRIANgLE). Jpn. J. Clin. Oncol. 2019, 49, 1055–1060. [Google Scholar] [CrossRef] [PubMed]
  4. Miyata, H.; Sugimura, K.; Motoori, M.; Omori, T.; Yamamoto, K.; Yanagimoto, Y. Clinical Implications of Conversion Surgery After Induction Therapy for T4b Thoracic Esophageal Squamous Cell Carcinoma. Ann. Surg. Oncol. 2019, 26, 4737–4743. [Google Scholar] [CrossRef]
  5. Von Döbeln, G.A.; Klevebro, F.; Jacobsen, B.; Johannessen, O.; Nielsen, H.; Johnsen, G. Neoadjuvant chemotherapy versus neoadjuvant chemoradiotherapy for cancer of the esophagus or gastroesophageal junction: Long-term results of a randomized clinical trial. Dis. Esophagus 2018, 32, doy078. [Google Scholar] [CrossRef]
  6. Sjoquist, K.M.; Burmeister, B.H.; Smithers, B.M.; Zalcberg, J.R.; Simes, R.J.; Barbour, A.; Australasian Gastro-Intestinal Trials Group. Survival after neoadjuvant chemotherapy or chemoradiotherapy for resectable oesophageal carcinoma: An updated meta-analysis. Lancet Oncol. 2011, 12, 681–692. [Google Scholar] [CrossRef] [PubMed]
  7. Eyck, B.M.; van Lanschot, J.J.B.; Hulshof, M.C.C.M.; van der Wilk, B.J.; Shapiro, J.; van Hagen, P. Ten-Year outcome of neoadjuvant chemoradiotherapy plus surgery for esophageal cancer: The Randomized controlled CROSS Trial. J. Clin. Oncol. 2021, 39, 1995–2004. [Google Scholar] [CrossRef]
  8. Tang, H.; Wang, H.; Fang, Y.; Zhu, J.Y.; Yin, J.; Shen, Y.X. Neoadjuvant chemoradiotherapy versus neoadjuvant chemotherapy followed by minimally invasive esophagectomy for locally advanced esophageal squamous cell carcinoma: A prospective multicenter randomized clinical trial. Ann. Oncol. 2023, 34, 163–172. [Google Scholar] [CrossRef]
  9. Nusrath, S.; Thammineedi, S.R.; Vijaya Narsimha Raju, K.V.; Patnaik, S.C.; Pawar, S.; Santa, A. Short-term Outcomes in Patients with Carcinoma of the Esophagus and Gastroesophageal Junction Receiving Neoadjuvant Chemotherapy or Chemoradiation before Surgery. A Prospective Study. Rambam Maimonides Med. J. 2019, 10, e0002. [Google Scholar] [CrossRef]
  10. Thomas, M.; Borggreve, A.S.; van Rossum, P.S.N.; Perneel, C.; Moons, J.; Van Daele, E.; van Hillegersberg, R. Radiation dose and pathological response in oesophageal cancer patients treated with neoadjuvant chemoradiotherapy followed by surgery: A multi-institutional analysis. Acta Oncol. 2019, 58, 1358–1365. [Google Scholar] [CrossRef]
  11. Andreollo, N.A.; Beraldo, G.C.; Alves, I.P.F.; Tercioti-Junior, V.; Ferrer, J.A.P.; Coelho-Neto, J.S. Pathologic complete response (YPT0 YPN0) after chemo therapy and radiotherapy neoadjuvant followed by esophagectomy in the squamous cell carcinoma of the esophagus. Arq. Bras. Cir. Dig. 2018, 31, e1405. [Google Scholar] [CrossRef] [PubMed]
  12. Jain, R.K.; Carmeliet, P. SnapShot: Tumor angiogenesis. Cell 2012, 149, 1408–1408.e1. [Google Scholar] [CrossRef] [PubMed]
  13. Carmeliet, P.; Jain, R.K. Angiogenesis in cancer and other diseases. Nature 2000, 407, 249–257. [Google Scholar] [CrossRef]
  14. Hayano, K.; Ohira, G.; Hirata, A.; Aoyagi, T.; Imanishi, S.; Tochigi, T. Imaging biomarkers for the treatment of esophageal cancer. World J. Gastroenterol. 2019, 25, 3021–3029. [Google Scholar] [CrossRef] [PubMed]
  15. Aoyagi, T.; Shuto, K.; Okazumi, O.; Hayano, K.; Satoh, A.; Saitoh, H. Apparent Diffusion Coefficient Correlation With Oesophageal Tumour Stroma and Angiogenesis. Eur. Radiol. 2012, 22, 1172–1177. [Google Scholar] [CrossRef] [PubMed]
  16. Tamandl, D.; Fueger, B.; Haug, A.; Schmid, R.; Stift, J.; Schoppmann, S.F. Diagnostic Algorithm That Combines Quantitative 18F-FDG PET Parameters and Contrast-Enhanced CT Improves Posttherapeutic Locoregional Restaging and Prognostication of Survival in Patients With Esophageal Cancer. Clin. Nucl. Med. 2019, 44, e13–e21. [Google Scholar] [CrossRef] [PubMed]
  17. Borggreve, A.S.; Goense, L.; van Rossum, P.S.N.; Heethuis, S.E.; van Hillegersberg, R.; Lagendijk, J.J.W. Preoperative Prediction of Pathologic Response to Neoadjuvant Chemoradiotherapy in Patients With Esophageal Cancer Using 18F-FDG PET/CT and DW-MRI: A Prospective Multicenter Study. Int. J. Radiat. Oncol. Biol. Phys. 2020, 106, 998–1009. [Google Scholar] [CrossRef] [PubMed]
  18. Miles, K.A.; Hayball, M.; Dixon, A.K. Colour perfusion imaging: A new application of computed tomography. Lancet 1991, 337, 643–645. [Google Scholar] [CrossRef]
  19. Chen, T.W.; Yang, Z.G.; Wang, Q.L.; Li, Y.; Qian, L.L.; Chen, H. Whole tumour quantitative measurement of first-pass perfusion of oesophageal squamous cell carcinoma using 64-row multidetector computed tomography: Correlation with microvessel density. J. Eur. J. Radiol. 2011, 79, 218–223. [Google Scholar] [CrossRef]
  20. Hayano, K.; Okazumi, S.; Shuto, K.; Matsubara, H.; Shimada, H.; Nabeya, Y. Perfusion CT can predict the response to chemoradiation therapy and survival in esophageal squamouscell carcinoma: Initial clinical results. Oncol. Rep. 2007, 18, 901–908. [Google Scholar]
  21. Makari, Y.; Yasuda, T.; Doki, Y.; Miyata, H.; Fujiwara, Y.; Takiguchi, S. Correlation between tumor blood flow assessed by perfusion CT and effect of neoadjuvant therapy in advanced esophageal cancers. Surg. Oncol. 2007, 96, 220–229. [Google Scholar] [CrossRef]
  22. Li, M.H.; Shang, D.P.; Chen, C.; Xu, L.; Huang, Y.; Kong, L. Perfusion computed tomography in predicting treatment response of advanced esophageal squamous cell carcinomas. Asian Pac. J. Cancer Prev. 2015, 16, 797–802. [Google Scholar] [CrossRef] [PubMed]
  23. Lei, J.; Han, Q.; Zhu, S.; Shi, D.; Dou, S.; Su, Z. Assessment of esophageal carcinoma undergoing concurrent chemoradiotherapy with quantitative dynamic contrast-enhanced magnetic resonance imaging. Oncol. Lett. 2015, 10, 3607–3612. [Google Scholar] [CrossRef] [PubMed]
  24. Ye, Z.M.; Dai, S.J.; Yan, F.Q.; Wang, L.; Fang, J.; Fu, Z.F. DCE-MRI-Derived Volume Transfer Constant (K(trans)) and DWI Apparent Diffusion Coefficient as Predictive Markers of Short- and Long-Term Efficacy of Chemoradiotherapy in Patients With Esophageal Cancer. Technol. Cancer Res. Treat. 2018, 17, 1533034618765254. [Google Scholar] [CrossRef]
  25. Sun, N.N.; Ge, X.L.; Liu, X.S.; Xu, L.L. Histogram analysis of DCE-MRI for chemoradiotherapy response evaluation in locally advanced esophageal squamous cell carcinoma. Radiol. Med. 2020, 125, 165–176. [Google Scholar] [CrossRef] [PubMed]
  26. Cong, Q.; Li, G.; Wang, Y.; Zhang, S.; Zhang, H. DW-MRI for esophageal squamous cell carcinoma, correlations between ADC values with histologic differentiation and VEGF expression: A retrospective study. Oncol. Lett. 2019, 17, 2770–2776. [Google Scholar] [CrossRef] [PubMed]
  27. Aoyagi, T.; Shuto, K.; Okazumi, S.; Shimada, H.; Kazama, T.; Matsubara, H. Apparent Diffusion Coefficient Values Measured by Diffusion-Weighted Imaging Predict Chemoradiotherapeutic Effect for Advanced Esophageal Cancer. Dig. Surg. 2011, 28, 252–257. [Google Scholar] [CrossRef] [PubMed]
  28. Guo, L.; Zhang, L.; Zhao, J. CT scan and magnetic resonance diffusion-weighted imaging in the diagnosis and treatment of esophageal cancer. Oncol. Lett. 2018, 16, 7117–7122. [Google Scholar] [CrossRef] [PubMed]
  29. Li, S.P.; Padhani, A.R. Tumor response assessments with diffusion and perfusion MRI. J. Magn. Reson. Imaging 2012, 35, 745–763. [Google Scholar] [CrossRef]
  30. Hirata, A.; Hayano, K.; Ohira, G.; Imanishi, S.; Hanaoka, T.; Murakami, K. Volumetric histogram analysis of apparent diffusion coefficient for predicting pathological complete response and survival in esophageal cancer patients treated with chemoradiotherapy. Am. J. Surg. 2020, 219, 1024–1029. [Google Scholar] [CrossRef]
  31. Chao, Y.K.; Chuang, W.Y.; Chang, H.K.; Tseng, C.K.; Yeh, C.J.; Liu, Y.H. Prognosis of patients with esophageal squamous cell carcinoma who achieve major histopathological response after neoadjuvant chemoradiotherapy. Eur. J. Surg. Oncol. 2017, 43, 234–239. [Google Scholar] [CrossRef] [PubMed]
  32. Noble, F.; Nolan, L.; Bateman, A.C.; Byrne, J.P.; Kelly, J.J.; Bailey, I.S. Refining pathological evaluation of neoadjuvant therapy for adenocarcinoma of the esophagus. World J. Gastroenterol. 2013, 19, 9282–9293. [Google Scholar] [CrossRef] [PubMed]
  33. Hayano, K.; Shuto, K.; Satoh, A.; Aoyagi, T.; Narushima, K.; Gunji, H. Tumor blood flow change measured by CT perfusion during chemoradiation therapy (CRT) for monitoring response and predicting survival in patients with esophageal cancer. Esophagus 2014, 11, 72–79. [Google Scholar] [CrossRef]
  34. Djuric-Stefanovic, A.; Micev, M.; Stojanovic-Rundic, S.; Pesko, P.; Saranovic, D. Absolute CT perfusion parameter values after the neoadjuvant chemoradiotherapy of the squamous cell esophageal carcinoma correlate with the histopathologic tumor regression grade. Eur. J. Radiol. 2015, 84, 2477–2484. [Google Scholar] [CrossRef] [PubMed]
  35. Imanishi, S.; Shuto, K.; Aoyagi, T.; Kono, T.; Saito, H.; Matsubara, H. Diffusion-weighted Magnetic Resonance Imaging for Predicting and Detecting the Early Response to Chemoradiotherapy of Advanced Esophageal Squamous Cell Carcinoma. Dig. Surg. 2013, 30, 240–248. [Google Scholar] [CrossRef] [PubMed]
  36. Cheng, B.; Yu, J. Predictive value of diffusion-weighted MR imaging in early response to chemoradiotherapy of esophageal cancer: A meta-analysis. Dis. Esophagus 2018, 32, doy065. [Google Scholar] [CrossRef]
  37. Heethuis, S.E.; Goense, L.; van Rossum, P.S.N.; Borggreve, A.S.; Mook, S.; Voncken, F.E.M. DW-MRI and DCE-MRI are of complementary value in predicting pathologic response to neoadjuvant chemoradiotherapy for esophageal cancer. Acta Oncol. 2018, 57, 1201–1208. [Google Scholar] [CrossRef]
  38. Li, Q.W.; Qiu, B.; Wang, B.; Wang, D.L.; Yin, S.H.; Yang, H. Prediction of pathologic responders to neoadjuvant chemoradiotherapy by diffusion-weighted magnetic resonance imaging in locally advanced esophageal squamous cell carcinoma: A prospective study. Dis. Esophagus 2017, 31, dox121. [Google Scholar] [CrossRef]
  39. Borggreve, A.S.; Heethuis, S.E.; Boekhoff, M.R.; Goense, L.; van Rossum, P.S.N.; Brosens, L.A.A. Optimal timing for prediction of pathologic complete response to neoadjuvant chemoradiotherapy with diffusion-weighted MRI in patients with esophageal cancer. J. Eur. Radiol. 2020, 30, 1896–1907. [Google Scholar] [CrossRef]
  40. Vollenbrock, S.E.; Voncken, F.E.M.; Bartels, L.W.; Beets-Tan, R.G.H.; Bartels-Rutten, A. Diffusion-weighted MRI with ADC mapping for response prediction and assessment of oesophageal cancer: A systematic review. Radiother. Oncol. 2020, 142, 17–26. [Google Scholar] [CrossRef]
  41. Odawara, S.; Kitajima, K.; Katsuura, T.; Kurahashi, Y.; Shinohara, H.; Yamaka, K. Tumor Response to Neoadjuvant Chemotherapy in Patients With Esophageal Cancer Assessed With CT and FDG-PET/CT-RECIST 1.1 vs. PERCIST 1. Eur. J. Radiol. 2018, 101, 65–71. [Google Scholar] [CrossRef]
  42. Swisher, S.G.; Maish, M.; Erasmus, J.J.; Correa, A.M.; Komaki, R.; Macapinlac, H. Utility of PET, CT, and EUS to Identify Pathologic Responders in Esophageal Cancer. Ann. Thorac. Surg. 2004, 78, 1152–1160. [Google Scholar] [CrossRef]
  43. Arnett, A.H.; Merrell, K.W.; Macintosh, E.M.; James, S.E.; Nathan, M.A.; Shen, K.R. Utility of 18F-FDG PET for Predicting Histopathologic Response in Esophageal Carcinoma following Chemoradiation. J. Thorac. Oncol. 2016, 12, 121–128. [Google Scholar] [CrossRef]
  44. Higuchi, I.; Yasuda, T.; Yano, M.; Doki, Y.; Miyata, H.; Tatsumi, M. Lack of fludeoxyglucose F 18 uptake in posttreatment positron emission tomography as a significant predictor of survival after subsequent surgery in multimodality treatment for patients with locally advanced esophageal squamous cell carcinoma. J. Thorac. Cardiovasc. Surg. 2008, 136, 205–212. [Google Scholar] [CrossRef] [PubMed]
  45. Ott, K.; Weber, W.A.; Lordick, F.; Becker, K.; Busch, R.; Herrmann, K.; Wieder, H. Metabolic imaging predicts response, survival, and recurrence in adenocarcinomas of the esophagogastric junction. J. Clin. Oncol. 2006, 24, 4692–4698. [Google Scholar] [CrossRef] [PubMed]
  46. Izumi, D.; Yoshida, N.; Watanabe, M.; Shiraishi, S.; Ishimoto, T.; Kosumi, K. Tumor/normal esophagus ratio in (18)F-fluorodeoxyglucose positron emission tomography/computed tomography for response and prognosis stratification after neoadjuvant chemotherapy for esophageal squamous cell carcinoma. J. Gastroenterol. 2016, 51, 788–795. [Google Scholar] [CrossRef] [PubMed]
  47. Yasuda, T.; Yano, M.; Miyata, H.; Yamasaki, M.; Higuchi, I.; Takiguchi, S. Systemic control and evaluation of the response to neoadjuvant chemotherapy in resectable thoracic esophageal squamous cell carcinoma with 18F-fluorodeoxyglucose positron emission tomography-positive lymph nodes. Surg. Today 2015, 45, 335–345. [Google Scholar] [CrossRef] [PubMed]
  48. Hamai, Y.; Hihara, J.; Emi, M.; Ibuki, Y.; Murakami, Y.; Nishibuchi, I. Clinical Significance of 18F-Fluorodeoxyglucose-Positron Emission Tomography-Positive Lymph Nodes to Outcomes of Trimodal Therapy for Esophageal Squamous Cell Carcinoma. Ann. Surg. Oncol. 2019, 26, 1869–1878. [Google Scholar] [CrossRef]
  49. Yip, C.; Davnall, F.; Kozarski, R.; Landau, D.B.; Cook, G.J.; Ross, P. Assessment of changes in tumor heterogeneity following neoadjuvant chemotherapy in primary esophageal cancer. Dis. Esophagus 2015, 28, 172–179. [Google Scholar] [CrossRef]
  50. Ganeshan, B.; Skogen, K.; Pressney, I.; Coutroubis, D.; Miles, K. Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: Preliminary evidence of an association with tumour metabolism, stage, and survival. Clin. Radiol. 2012, 67, 157–164. [Google Scholar] [CrossRef]
  51. Yip, C.; Landau, D.; Kozarski, R.; Ganeshan, B.; Thomas, R.; Michaelidou, A. Primary esophageal cancer: Heterogeneity as potential prognostic biomarker in patients treated with definitive chemotherapy and radiation therapy. Radiology 2014, 270, 141–148. [Google Scholar] [CrossRef]
  52. Liu, S.; Zheng, H.; Pan, X.; Chen, L.; Shi, M.; Guan, Y. Texture analysis of CT imaging for assessment of esophageal squamous cancer aggressiveness. J. Thorac. Dis. 2017, 9, 4724–4732. [Google Scholar] [CrossRef]
  53. Okazumi, S.; Shimada, H.; Matsubara, H. Estimation of downstaging after chmoradiotherapy for T4 esophageal cancer by qualitative response evaluation using rendered MD-CT and the outcome of curative resection. Dis. Esophagus 2018, 31 (Suppl. S1), 140–141. [Google Scholar] [CrossRef]
Jcm 13 00632 g001
Figure 1. (Upper) plain CT image. (Lower) Calculated image using perfusion-CT for esophageal squamous cell carcinoma. Arrows indicate the esophageal tumor.
Figure 1. (Upper) plain CT image. (Lower) Calculated image using perfusion-CT for esophageal squamous cell carcinoma. Arrows indicate the esophageal tumor.
Jcm 13 00632 g001
Jcm 13 00632 g002
Figure 2. (Upper) Contrast-enhanced CT image. (Lower) Diffusion image obtained with 1.5T-MRI for esophageal squamous cell carcinoma. Arrows indicate the esophageal tumor.
Figure 2. (Upper) Contrast-enhanced CT image. (Lower) Diffusion image obtained with 1.5T-MRI for esophageal squamous cell carcinoma. Arrows indicate the esophageal tumor.
Jcm 13 00632 g002
Jcm 13 00632 g003
Figure 3. Comparison of the change in diffusion-MRI images of the tumor over the course of CRT for esophageal squamous cell carcinoma between responders and non-responders. Arrows indicate the tumor. Responders showed higher change in tumor diffusion than non-responders.
Figure 3. Comparison of the change in diffusion-MRI images of the tumor over the course of CRT for esophageal squamous cell carcinoma between responders and non-responders. Arrows indicate the tumor. Responders showed higher change in tumor diffusion than non-responders.
Jcm 13 00632 g003
Jcm 13 00632 g004
Figure 4. Downstaging evaluation using fibrous-tissue-enhanced CT reconstruction image of the case of esophageal squamous cell carcinoma after CRT. Contrast-enhanced CT was performed using multi-detector CT (GE light speed ultra). Arrows show the tumor. The upper is pre-CRT T4 image, which shows no interstitial plane between the tumor and aorta. The lower is post-CRT image, which shows fibrous plane as green and the case was diagnosed as downstaging and curatively resected with surgery.
Figure 4. Downstaging evaluation using fibrous-tissue-enhanced CT reconstruction image of the case of esophageal squamous cell carcinoma after CRT. Contrast-enhanced CT was performed using multi-detector CT (GE light speed ultra). Arrows show the tumor. The upper is pre-CRT T4 image, which shows no interstitial plane between the tumor and aorta. The lower is post-CRT image, which shows fibrous plane as green and the case was diagnosed as downstaging and curatively resected with surgery.
Jcm 13 00632 g004
Table 3. The diagnostic indices of qualitative imaging modalities for the evaluation of the effect of neoadjuvant therapy for advanced esophageal cancer.
Table 3. The diagnostic indices of qualitative imaging modalities for the evaluation of the effect of neoadjuvant therapy for advanced esophageal cancer.
Perfusion CTDCE-MRIDiffusion-MRIFDG-PETTissue Selected Rendering CE-CT
PreRPhigh blood flowhigh Ktrans valuehigh ADC value(-)(-)
DurRP(-) (-) increase in ADC valuedecrease in SUV(-)
REdecrease in tumor blood flow◿Ktransincrease in ADC valuedecrease in SUVdecrease in CT value
DSE(-)(-)(-)(-)appearance of fibrous changed layer
DCE-MRI: dynamic contrast-enhanced MRI; CE-CT: contrast-enhanced CT; ADC: apparent diffusion coefficient; PreRP: pretreatment responder prediction; DurRP: during treatment responder prediction; RE: response evaluation after treatment; DSE: downstaging evaluation for surgical resectability; FDG-PET: fluorodeoxyglucose-PET.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Okazumi, S.; Ohira, G.; Hayano, K.; Aoyagi, T.; Imanishi, S.; Matsubara, H. Novel Advances in Qualitative Diagnostic Imaging for Decision Making in Multidisciplinary Treatment for Advanced Esophageal Cancer. J. Clin. Med. 2024, 13, 632. https://doi.org/10.3390/jcm13020632

AMA Style

Okazumi S, Ohira G, Hayano K, Aoyagi T, Imanishi S, Matsubara H. Novel Advances in Qualitative Diagnostic Imaging for Decision Making in Multidisciplinary Treatment for Advanced Esophageal Cancer. Journal of Clinical Medicine. 2024; 13(2):632. https://doi.org/10.3390/jcm13020632

Chicago/Turabian Style

Okazumi, Shinichi, Gaku Ohira, Koichi Hayano, Tomoyoshi Aoyagi, Shunsuke Imanishi, and Hisahiro Matsubara. 2024. "Novel Advances in Qualitative Diagnostic Imaging for Decision Making in Multidisciplinary Treatment for Advanced Esophageal Cancer" Journal of Clinical Medicine 13, no. 2: 632. https://doi.org/10.3390/jcm13020632

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop