|Year : 2020 | Volume
| Issue : 8 | Page : 34-38
Predicting outcome of advanced head-and-neck cancer by measuring tumor blood perfusion in patients receiving neoadjuvant chemotherapy
Kishore Singh1, Rubu Sunku2, Arun K Rathi1, Gaurav S Pradhan3
1 Department of Radiation Oncology, Maulana Azad Medical College, Delhi, India
2 Department of Radiation Oncology, Dr. B. Borooah Cancer Institute, Guwahati, Assam, India
3 Department of Radiodiagnosis, Maulana Azad Medical College, Delhi, India
|Date of Submission||29-Mar-2018|
|Date of Decision||20-Jun-2018|
|Date of Acceptance||25-Jul-2019|
|Date of Web Publication||05-Nov-2020|
Department of Radiation Oncology, Dr. B. Borooah Cancer Institute, Guwahati, Assam
Source of Support: None, Conflict of Interest: None
Purpose: The purpose of this study was to correlate treatment response with tumor blood perfusion in patient of advanced head-and-neck cancer undergoing neoadjuvant chemotherapy.
Materials and Methods: A total of 40 patients of advanced head-and-neck cancer, who were planned for neoadjuvant chemotherapy, were included in the study. All patients underwent diagnostic computed tomography (CT) with perfusion study for staging and quantitative measurement of tumor volume as well as perfusion parameters (including tumor blood volume, blood flow, permeability, and time to peak enhancement), at baseline and after completion of neoadjuvant chemotherapy. Total 3 cycles of neoadjuvant chemotherapy with paclitaxel, cisplatin, and 5 fluorouracil were given. Tumor response was evaluated in terms of change in tumor volume and correlated with perfusion parameters.
Results: Out of 40 patients, 22 patients had more than 50% reduction in tumor volume, who were grouped as responder and remaining 18 patients had <50% decrease in tumor volume, grouped as nonresponder. Both the groups were similar in terms of age, gender, performance status, stage, nodal status, or addiction. Baseline CT scan shows a significant difference in tumor blood flow (P = 0.048) and marginal difference in time to peak enhancement (P = 0.058) in two groups. However, there is no difference in tumor blood volume (P = 0.32) and permeability surface area (P = 0.07).
Conclusions: Evaluation of tumor blood flow by perfusion CT is helpful in predicting chemotherapy outcome and deciding appropriate treatment modality, but further evaluation with more number of patients is required for validating the predictive role of each perfusion parameters.
Keywords: Neoadjuvant chemotherapy, perfusion computed tomography, perfusion parameters
|How to cite this article:|
Singh K, Sunku R, Rathi AK, Pradhan GS. Predicting outcome of advanced head-and-neck cancer by measuring tumor blood perfusion in patients receiving neoadjuvant chemotherapy. J Can Res Ther 2020;16, Suppl S1:34-8
|How to cite this URL:|
Singh K, Sunku R, Rathi AK, Pradhan GS. Predicting outcome of advanced head-and-neck cancer by measuring tumor blood perfusion in patients receiving neoadjuvant chemotherapy. J Can Res Ther [serial online] 2020 [cited 2021 Jan 25];16:34-8. Available from: https://www.cancerjournal.net/text.asp?2020/16/8/34/300114
| > Introduction|| |
The incidence of head-and-neck cancer in India is one of the highest in the world and majority of the patients present in very advanced stage of disease. Radiotherapy with or without chemotherapy is the mainstay of organ preservation treatment in these cases. Despite intensive therapy, half of these patients end up with residual disease coupled with treatment-related morbidity, leading to dismal quality of life.
If we can predict the outcome, such intensive treatment can be reserved for responders only. Tumor microvasculature is an important tumor characteristic which indicates tumor aggressiveness. Tumor hypoxia suspected as a major factor imparting radioresistance to tumors treated with low energy transfer irradiation, including X-ray and gamma rays and leading to failure of therapy. Low blood perfusion is presumed to be associated with impaired chemotherapy response. Microvessel density assessment has been established as prognostic indicator for many cancers, but its clinical use is limited because of the requirement to do periodic rebiopsies.
Functional imaging modalities such as perfusion magnetic resonance imaging (MRI) or computed tomography (CT) have capability to assess tumor vascularization. Perfusion CT (pCT) can measure the tumor blood perfusion, permeability, and blood volume and gives a fair idea about tumor angiogenesis. pCT demonstrates substantially increased tumor blood perfusion in squamous cell cancer of head-and-neck region when compared with adjacent normal tissues.
We intend to study the feasibility of predicting treatment response by studying changes in perfusion by CT in patients of head-and-neck cancer undergoing neoadjuvant chemotherapy.
| > Materials and Methods|| |
A total of 40 newly diagnosed case of locally advanced squamous cell cancer of head-and-neck was prospectively included in the study. Subsites of head-and-neck included were oropharynx, hypopharynx, and larynx, while oral cavity, nasopharynx, and paranasal sinus cancer were excluded from the study. Patients included were between 18 and 60 years of age with performance status of ECOG 0–2. Exclusion criteria included uncontrolled comorbidities such as diabetes and hypertension, deranged hematological profile, or any history of previous malignancy. Out of 40 patients, 39 were male and 1 were female. Twelve patients had Stage III disease, 26 had Stage IV A disease, and only two patients had Stage IV B disease according to AJCC 2007 (10th Edition).
After a baseline investigation, patients were subjected to pCT before starting chemotherapy. CT is performed in 128-slice multidetector CT (SOMATOM Sensation, Siemens ®, definition AS +). Baseline unenhanced CT with wide coverage is done to include the organ of interest and localize the appropriate tissue area to be included in the contrast-enhanced dynamic image range. Nonionic contrast (iomeprol), which contains iodine at the concentration of 350 mg of iodine per ml, is used as contrast media. Sharp bolus injection of 50 ml contrast is injected at a rate of 4.5 ml/s. Scan is acquired at voltage of 120 kVp and 80 mAs.
Gross tumor volume was contoured on all relevant axial computerized images without interpolation and measured in milliliter. Measurement of volume done twice:First was done before starting neoadjuvant chemotherapy and second was done 12–16 days after completion of 3 cycles of chemotherapy. Pre- and post-chemotherapy readings were compared. According to the proportion of decrease in tumor volume, patients are grouped into responder and nonresponder. Patients with decrease of >50% were put in the responder, while patients with <50% decrease or increase in tumor volume were grouped under nonresponder. Volume of lymph node also assessed before and after chemotherapy.
Perfusion parameters obtained are blood flow, blood volume, permeability, and time to peak enhancement. Blood volume is defined as volume of flowing blood within a vasculature in tissue region, measured in ml per 100 g and blood flow is defined as blood flow rate through vasculature in tissue region, measured in ml per 100 g/min. Both the parameters attributed to initial phase when contrast is within the intravascular space usually lasts approximately 40–60 s. Blood permeability or permeability surface area product is defined as total flux from plasma to interstitial space, measured in ml per 100 g/min. It is a marker for immature leaky vessels and obtained when contrasts pass from intravascular to extravascular compartment across the capillary membrane. Time to peak enhancement is defined as time from arrival of the contrast in major vessels to the peak enhancement, measured in seconds. Peak tissue enhancement results from contrast distribution between the two compartments that is between intravascular and extravascular compartments. Tumor mass shows shorter time to peak enhancement of contrast than normal reference tissue.
Perfusion parameter of tumor measured is compared with of that of adjacent normal reference tissue and percentage difference between perfusion of normal tissue and tumor is calculated. Reading obtained is compared between responder and nonresponder, and same is compared before and after chemotherapy.
Patients are taken up for chemotherapy after CT scan and prechemotherapy laboratory investigation. All patients received 3 cycles of neoadjuvant chemotherapy including injection paclitaxel 175 mg/m 2 intravenous (IV) on Day 1, injection cisplatin 100 mg/m 2 IV on D2, and injection 5 fluorouracil 500 mg/m 2 confidence interval on D2 to D6, which was repeated at interval of 21 days. Toxicity documentation is done after every cycle according to the Common Terminology Criteria for of NCI Adverse Events v4.0 (CTCAE). Supportive treatment is given as indicated. Treatment was interrupted in patient having Grade 3 or higher toxicity not recovering in time. After 3rd cycle of chemotherapy, repeat CT scan for response evaluation as well as perfusion study was done.
Statistical analysis was done by IBM SPSS Version 16 software. The difference in perfusion parameters between tumor mass and normal tissue was assessed using Wilcoxon signed-rank test. Evaluation of difference in prechemotherapy perfusion parameters between responder and nonresponder was done using Mann–Whitney test. Comparison of any difference in possible compounding factor influencing the treatment response, between responder and nonresponders such as treatment-related toxicity and addiction of patients was assessed by unpaired t-test.
| > Results|| |
A total of 40 patients of advanced head-and-neck cancer registered in the Department of Radiotherapy were included in the study. Patients were comparable in both groups in terms of gender, initial hemoglobin level, performance status, histopathology, and addiction, with the exception of age and stage of disease [Table 1]. There were higher numbers of younger patients in responders than in nonresponder. In stage-wise analyses, 45.4% (10 out of 22) of responder had Stage III disease and none of the responders had Stage IV B disease, while among nonresponder, only 11% (2 out of 18) of the patients had Stage III disease and equal number, that is, 11% of patients had Stage IV B disease.
|Table 1: Comparison of patients characteristics among responder and nonresponder group|
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CT was done for staging, assessment of tumor volume, and perfusion study in the Department of Radiology, before starting treatment. To avoid any variation due to difference in innate tissue perfusion between individual patients, the percentage difference in perfusion parameter of tumor to normal tissue perfusion was obtained for each patient. Normal reference tissues taken for comparison were paraspinal muscle and masseter muscle, whichever is more appropriate according to tumor location [Figure 1]a and [Figure 1]b. Comparative study shows that perfusion parameter of tumor tissues was much higher as compared to normal tissue in almost all patients [Figure 2]; but in few patients, it was similar or lower than the normal tissue perfusion parameters [Table 2]. Percentage difference in perfusion parameters was compared between both the groups later on. Following initial pCT scan, all 40 patients completed 3 cycles chemotherapy as planned for the study. Repeat CT scan with perfusion study was done after chemotherapy, following which patients were assigned into responder group and nonresponder group according to change in tumor volume.
|Figure 1: (a) Axial Computed Tomography scan of a patient with supraglottic cancer. (b) Perfusion computed tomography image of the same patient showing difference in perfusion parameters between normal surrounding tissue (1) and tumor tissue (2)|
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|Figure 2: Difference in perfusion parameters between normal tissue (1) and tumor tissue (2) of the patient in Figure 1|
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|Table 2: Comparison of perfusion parameters between tumor mass and normal tissue|
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Comparison of prechemotherapy perfusion parameter between the two groups shows that blood flow was significantly higher in responder compared to nonresponder (P = 0.048), while permeability and time to peak enhancement were marginally higher but failed to reach statistical significance (P = 0.07 for permeability and P = 0.058 for time to peak enhancement), and no difference was seen in tumor blood volume in both the group (P = 0.32) [Table 3].
|Table 3: Comparison of percentage difference in perfusion parameters between responder and nonresponder|
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In postchemotherapy pCT scan, no difference was seen in perfusion parameters between responder and nonresponder.
| > Discussion|| |
Feasibility of predicting treatment response can help avoid treatment-related morbidity and associated financial wastage. Understanding tumor biology can profoundly help in individualizing management of cancer. Angiogenesis is one of the key factors of tumor proliferation, which can be quantified by microvascular density (MVD) assessment by various endothelial cell markers such as radioactive microsphere technique. MVD has been established as prognostic indicator for many cancers, but it would require periodic biopsies; therefore, it is not practical for routine use.,, Alternative method to assess tumor microvasculature is by functional imaging such as O 15 labeled positron emission tomography scan, functional MRI, or pCT scan.
In our study using pCT scan, we found that there is a significant difference in normal tissue perfusion between individuals. Therefore, tumor perfusion parameter obtained in each individual should be standardized with his/her own adjacent reference normal tissue perfusion before comparing it with different treatment groups. A significant difference in perfusion parameter of tumor tissue and normal tissue (P > 0.001) was seen in all individual, which emphasizes the significance of functional imaging with pCT scan that can possibly be used in detection of occult malignancy also. Several studies have already suggested its possible use in prognostic information, delineation of tumor with benefits for radiotherapy planning, biopsy, and detection of hepatic metastases.,, A Phase II study done on the patient receiving neoadjuvant bevacizumab followed by radiotherapy in soft-tissue sarcoma also showed that tumor tissue perfusion is more sensitive than change in tumor size in monitoring early and late response. Induction chemotherapy in head-and-neck cancer is often studied for its possible role as indicator of response predictor in patients planned for radiation or chemoradiotherapy.,, Correlation of pretreatment biological characteristics of tumor and morphological change after induction chemotherapy can guide in selecting patient for organ conserving treatment, while unfavorable cases can be taken up for surgery instead.,,
We assessed treatment response in terms of volumetric change, which was correlated with perfusion parameter of tumor. We found that blood flow of tumor tissue was significantly associated with tumor response (P = 0.048), while blood volume had no appreciable correlation with volume change (P = 0.32). Permeability and mean transition time had marginal association with the response of tumor tissue to chemotherapy (P = 0.07 and P = 0.058, respectively). A similar perfusion study was done by Petralia et al., where it was seen that blood flow and blood volume were significantly associated with treatment response. Gandhi et al. and Zima in 2006 and 2007, respectively, had also showed similar finding, showing significant association of blood volume and blood flow with tumor response to induction chemotherapy., Ursino et al. have recently studied the prediction ability of perfusion parameters in response to radiochemotherapy. Rana et al. studying the perfusion in patients receiving chemoradiotherapy showed that single best predictor of response is high blood flow (83.3%), while addition of low permeability surface can give 100% predictability of complete response irrespective of tumor stage. In contrast with above studies using induction chemotherapy, Ursino et al. showed that there was a significant change in all the perfusion parameters after radiochemotherapy.
A K Bahadur, Manoj Sharma, Priya Balakrishnan, Shashank Shekhar, Kunal Goel, Sabeena Katharia, Mukesh Sonkaria, Mayank Agarwal, Archana Jha.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3]