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BIOMEDICAL RESEARCH AND REVIEWS (ISSN:2631-3944)

Perfusion and Oxygenation Changes after Isolated Limb Perfusion with TNF - alpha in Lower Limb Sarcoma: A Case Report

Katerina Nikiforaki1,2*, Georgios C. Manikis1,2, Maria Venianaki1,3, Eleftherios Kontopodis1,2, Eleni Lagoudaki4, Thomas G. Maris2, Kostas Marias1,5, Eelco de Bree6, Apostolos Karantanas1,2

1 Computational BioMedicine Laboratory (CBML), Foundation for Research & Technology, Heraklion, Crete, Greece
2 Department of Radiology, School of Medicine,, University of Crete, Greece
3 Image Analysis Research Unit, IMT School for Advanced Studies Lucca, Italy
4 Department of Pathology, , University Hospital of Crete, Greece
5 Technological Educational Institute of Crete, Department of Informatics Engineering, Greece
6 Department of Surgical Oncology, School of Medicine, University of Crete, Greece

CitationCitation COPIED

Nikiforaki K, Manikis GC, Venianaki M, Lagoudaki E, Maris TG, et al. Perfusion and oxygenation changes after isolated limb perfusion with TNF-? in lower limb sarcoma: a case report. Biomed Res Rev. 2018Mar; 1(1):101

Abstract

Tumor necrosis factor alpha (TNF-α) is known to cause selective destruction of tumor neovascularisation. Perfusion changes in tumor microenvironment were studied in a young patient with a high-grade myxoid liposarcoma after isolated limb perfusion with TNF-α and melphalan, using advanced MR imaging. Quantitative and semi-quantitative evaluation of perfusion metrics included ktrans/f/T2* shift and automatic extraction of enhancement patterns. Strong agreement between different methods is consistent with response to therapy, specifically reduced perfusion (mean ktrans shifted from 0.424 to 0.099 mL/g/min, mean f from 33.5 to 7.3%), reduced hypoxia indication (mean T2* increased from 72 to 82 ms) and prevalence of necrotic areas.

Keywords

Tumor Necrosis Factor-α; MR imaging/diagnosis; Pattern Recognition; Tumor hypoxia; Cancer imagenomics; Liposarcoma/treatment response

Abbreviations

(TNF-α) : Tumor Necrosis Factor Alpha

ILP : Isolated limb perfusion

DCE : Dynamic Contrast Enhanced

DWI : Diffusion Weighted Imaging

IVIM : Intravoxel Incoherent Motion

T2*r : T2* Relaxometry

BOLD : Blood Oxygen Level-Dependent

PK : Pharmacokinetic

ktrans  : Transendothelial permeability

dHb  : Deoxyhemoglobin

IMVD : Intratumoral Microvessel Density

FISH : Fluorescence In situ Hybridization

PR  : Pattern Recognition

Introduction

Isolated limb perfusion (ILP) has been used for locally advanced extremity soft tissue sarcoma in order to avoid amputation when wide excision of the tumor is not feasible [1]. Subsequently (marginal) excision of the tumor is performed 6 to 8 weeks after this regional chemotherapy treatment. A drug combination of tumor necrosis factor alpha (TNF-α) and melphalan is usually used. TNF-α is multifunctional cytokine that plays a major role in innate and acquired immunity while its binding to certain receptors leads to hemodynamic and antitumor effects [2]. The administration of TNF-α during ILP inhibits devastating systemic hemodynamic effects and shows a strong synergistic antitumor action with chemotherapeutic agents in sarcoma patients [3]. In the setting of ILP TNF-α has two distinct antitumor properties that may be related to each other: increased uptake of chemotherapeutic drugs such as melphalan into the tumor and selective destruction of tumor neovascularization [2]. In experimental studies TNF-α has led to increased vessel permeability and decreased interstitial pressure as immediate effects after administration [4,5]. These early antivascular effects lead to an up to 6-fold–increased uptake of melphalan into the tumor [6]. Late antivascular effects such as tumor vessel disintegration and endothelial apoptosis which may ultimately result in tumor necrosis are best demonstrated in imaging obtained before and after ILP with TNF-α [7].

The evaluation of tumor response to therapy by non-invasively assessing blood supply and oxygen level has been a long-standing endeavor in MR imaging (MRI). To this end clinically relevant perfusion biomarkers extracted from Dynamic Contrast Enhanced (DCE) Diffusion Weighted Imaging (DWI) and T2* relaxometry (T2*r) are indicative of various pathophysiological properties of tissue vascularity [8,9]. 

Specifically DCE MRI evaluates the temporal pattern of enhancement from multiple dynamic acquisitions of high temporal resolution. A recent semi-quantitative analysis framework relies on a pattern recognition (PR) method namely BU-NMF [10] which extracts automatically the principal enhancement patterns that describe DCE data and assigns a certain enhancement profile to each image pixel. These patterns can be labeled as necrotic hypoxic and well-perfused and were associated with the three most common enhancement patterns found in tumors [11] which are described by steady and subtle enhancement (Type 1) by delayed enhancement and some wash-out (Type 2) and by rapid enhancement and wash-out (Type 3). Additionally quantitative analysis based on pharmacokinetic (PK) models [12] provides estimates of transfer rates of the contrast agent from plasma to tissue (transendothelial permeability-ktrans). 

However the DCE is not the only MRI method providing metrics indicative of vascularity. Intravoxel incoherent motion (IVIM) model of DWI may separate microcirculatory from thermal diffusion effects and can be used to study microcirculatory blood flow properties by estimating the microperfusion fraction f [13] i.e. the fraction of DWI signal arising from incoherent blood flow motion.

A third MRI method related to blood supply is the Blood Oxygen Level-Dependent (BOLD) which indirectly measures the total amount of deoxyhemoglobin (dHb) levels in a voxel. Conceptually the paramagnetic nature of deoxyhemoglobin as opposed to oxyhemoglobin accelerates T2* relaxation shortening thus T2* constants of tissue around the blood vessels. Importantly dHb levels depend on a number of concurrent phenomena such as blood flow blood oxygenation vasculature hemoglobin levels etc. [14] Because of the complex interplay between blood supply and oxygen extraction changes in oxygen delivery (blood flow) are not directly related to changes of oxygen consumption and dHb changes do not always match the expected action of the vascular stimulus. T2*r can provide information regarding tumor microenvironment as it reflects tissue oxygen bioavailability. Larger T2* tissue constants as a result of lower dHb concentration may indicate lower blood flow lower tissue oxygenation deficient vascular network etc. and is consistent with tumor response to therapy [9].

Although based on different grounds all three techniques have been widely used for tumor characterization. To our knowledge MRI analysis of TNF induced perfusion have only been studied in animals [15] and have shown changes in endothelial permeability after therapy as measured by perfusion biomarkers. This case study shows the vascularity changes in a lower limb sarcoma after ILP with TNF-α based on quantitative and semi-quantitative MRI methods. 

Patient History

A 40-year-old patient was referred for MRI scan of the left foot. Six months prior to imaging he had suffered from local pain during walking and had noticed a gradually growing tumor at its dorsolateral site. X-Ray showed a soft tissue mass between the 4th and the 5th metatarsal bones of the right left foot with bone remodeling and deformity (Figure 1). The mass was painless and slowly growing. Advanced MRI was performed before any biopsy. Since an ultrasoundguided core needle biopsy was inconclusive an open biopsy from the dorsal site of the soft tissue tumor was performed. At histological examination of the macroscopically grey to white color tissue with a myxoid-fleshy consistency the lesion presented a subtle multinodular conformation exhibited areas of variable cellular density with enhancement of cellularity at the periphery and was composed of bland fusiform or round cells suspended individually in a myxoid matrix with a prominent network of arborizing thin-walled capillary vessels often in a “chicken-footprint” configuration (Figure 2). Pools of extracellular mucin with cellular condensation at the rim were focally present. Mitotic figures were absent and lipoblasts were not identified. Immunohistochemical staining was positive for Vimentin only. Based on rearrangement of DDIT-3 gene which was detected using Fluorescence in Situ Hybridization (FISH)the histopathological diagnosis of high grade myxoid liposarcoma was made.

CT of the lungs revealed small nodular lesions which were considered negative for metastatic disease at the following PET-CT.

In order to avoid amputative surgery the patient underwent ILP from the popliteal vessels with 1 mg TNF-α (administered at time 0’) and 65 mg (10 mg/L limb volume administered at time 30’) melphalan for a total of 90 minutes. The postoperative course was uneventful and gradual reduction and softening of the tumor were  observed. Two months after ILP and before the planned resection of the tumor MRI demonstrated reduction of the tumor size (Figure 3) whereas advanced MRI was performed for research purposes (Figure 4). A new CT of the lungs demonstrated the presence of multiple lung metastases. Since the patient was asymptomatic the planned resection of the tumor was abandoned and systemic chemotherapy was initiated.


Figure 1: Magnified oblique view of the left foot, shows a soft tissue mass (asterisk) with displacement and remodelling of the 4th metatarsal (arrow)


Figure 2: CD34 stain highlights the thin-walled mostly arborizing vasculature (magnification X200)

Results

Baseline perfusion study showed strong enhancement (Figure 3a) and further post processing with in-house built software [16,17] evaluated high ktrans (mean 0.424 mL/g/min) (Figure 4a) and f values (mean 33.5%) indicating functional vessel network to the neoplasm. The semi-quantitative PR results show that before therapy there is prevalence of the hypoxic enhancement pattern i.e. 59.02% (Figures. 5a, 6). T2* relaxometry showed a mean value for the 3D tumor ROI of 72 ms.

MRI findings before therapy were correlated with immunohistochemistry results (CD34) regarding intratumoral microvessel density (iMVD). The CD34-stained neoplastic vasculature consisted mostly in fine arborizing vessels with diameter greater than 06 mm and newly formed vessels of one to three endothelial cells. Vessel rich “hot spots” areas were located in the tumor periphery and interestingly correlated closely with the areas having the highest tumor cell proliferation activity (Figure 2). Two methods were used to assess iMVD: a) microvessel counting [18] and b) the relative microvessel area estimate (‘Chalkley count’) [19]. The absolute number of the vessel count obtained in the three fields x200 was 290 282 and 264 respectively resulting in a mean of 280.3 vessels. Chalkley grid score of each hot spot was 14 18 and 16 respectively resulting in a mean Chalkley count of 16.


Figure 3: Baseline and follow-up MR imaging Fat suppressed contrast enhanced sagittal T1-w MR image a) before TNF therapy and b) after TNF therapy, showing the soft tissue mass with intense and in homogenous enhancement (arrows in a) and response to treatment (arrows in b) with regard to both the size of the lesion and the degree of enhancement.


Figure 4: Screenshot from in-house built software platform for DCE longitudinal analysis [16] Pixel-based parametric (ktrans) maps and corresponding histograms from a single slice of the tumor a) before and b) after TNF therapy

Visualizing Response to Therapy

Since follow up MRI was performed two months after therapy this study focused on the late vascularity changes such as tumor vessel disintegration and endothelial apoptosis. Identical protocol showed minimal foci of enhancement and reduced number of pixels (873 before vs 618 pixels assigned as tumor after therapy counted in 128x128 DWI images) in the ROI volume (Figure 3b). The semi quantitative approach showed that after therapy the necrotic enhancement pattern is dominant representing a percentage of 97% of image pixels (Figures. 5b,6). All measured ktrans metrics [16] show remarkably reduced perfusion in the whole tumor volume (mean was reduced from 0.424 to 0.099 mL/g/min median from 0.349 to 0.06 mL/g/min and 95th percentile from 0.948 to 0.326 mL/g/min) (Figures 4b,7a) strongly indicating severe impairment of the vessel network. Reduced blood flow was also confirmed by decrease of the f metric (mean was reduced from 33.5 to 7.3% median from 33.8 to 5% and 95th percentile from 34.6 to 20.1%) (Figure 7b) [17]. However perfusion changes alone do not suffice to indicate areas of deprived oxygen supply which are important for patient management and assessment of response to therapy. To this end T2* relaxometry was additionally performed. In particular T2* relaxation became slower after therapy (mean was increased from 72 to 82ms median from 61 to 62ms and 95th percentile from 164 to 214ms) implying decreased levels of deoxyhemoglobin (Figure 7c). This finding is in accordance with the aforementioned findings derived from both DCE-MRI and DW-MRI.


Figure 5: Semi-quantitative results before TNF therapy

a) classification of a single slice of the tumor with the different enhancement patterns, i.e. well-perfused (green), hypoxic (blue) and necrotic (red), identified using pattern recognition techniques

b) plots of the three patterns and corresponding percentage contribution of each one to the whole tumor. The hypoxic pattern (blue) is the principal pattern before TNF therapy


Figure 6: Semi-quantitative results after TNF therapy

a) classification of a single slice of the tumor with the different enhancement patterns, i.e. well-perfused (green), hypoxic (blue) and necrotic (red), identified using pattern recognition techniques and

b) plots of the three patterns and corresponding percentage contribution of each one to the whole tumor. The necrotic pattern is dominant after TNF therapy.


Figure 7: Pixel based histogram analysis before (red) and after (green) TNF therapy from 3-dimensional tumor ROI. a) ktrans (mL/g/min), b) f ( *100%), c)T2* (ms).

Discussion

Quantitative MRI is a powerful tool to assess changes in tumor microenvironment after therapeutic interventions. Although there is no absolute threshold to characterize tumor proliferation hypoxia or necrosis relative changes of perfusion metrics are indicative of changes in vascular permeability oxygen consumption and vascularity and are therefore often used to assess response after therapy. Threedimensional ROI histogram analysis permits to analyze the whole tumor volume without the need for spatial co-registration between different time points. Mean value shifts in all biomarkers (ktrans f T2*) stemming from different methods (DCE DWI T2* respectively) are in accordance with the change of the characteristic dominant perfusion curve of the tumor volume supporting the hypothesis of response to therapy. All metrics compose a complete multifaceted analysis which supports satisfactorily the radiological interpretation. 

Conclusion

To conclude this study enabled us to obtain an objective evaluation of the non-invasive assessment of blood supply and oxygen delivery post TNF-a therapy using a combination of DCE DWI and T2*r MRI related biomarkers. To our knowledge no study combining more than one perfusion monitoring techniques was found in the recent and older literature in animal or patient population.

References

  1. Jakob J, Hohenberger P. Role of isolated limb perfusion withrecombinant human tumor necrosis factor α and melphalan inlocally advanced extremity soft tissue sarcoma. Cancer. 2016May;22(17):2624-2632.
  2. Locksley RM, Killeen N, Lenardo MJ. The TNF and TNF receptorsuperfamilies: Integrating mammalian biology. Cell. 2001Feb;104(4):487-501.
  3. Lienard D, Ewalenko P, Delmotte JJ, Renard N, Lejeune FJ. Highdose recombinant tumor necrosis factor alpha in combinationwith interferon gamma and melphalan in isolation perfusionof the limbs for melanoma and sarcoma. J Clin Oncol.1992Jan;10(1):52-60.
  4. Folli S, Pelegrin A, Chalandon Y, Yao X, Buchegger F, et al.Tumor-Necrosis-Factor Can Enhance Radio-Antibody Uptakein Human Colon-Carcinoma Xenografts by Increasing VascularPermeability.Int J Cancer.1993 Mar;53(5):829-836.
  5. Jahr J, Grande PO. In vivo effects of tumor necrosis factor-alpha on capillary permeability and vascular tone in a skeletal muscle. Acta Anaesthesiol Scand. 1996 Feb;40(2):256-261. 
  6. de Wilt JH, ten Hagen TL, de Boeck G, van Tiel ST, de BruijnE a, et al. Tumour necrosis factor alpha increases melphalanconcentration in tumour tissue after isolated limb perfusion. Br JCancer.2000 Mar;82(5):1000-1003.
  7. Ruegg C, Yilmaz A, Bieler G, Bamat J, Chaubert P, et al. “Evidencefor the involvement of endotheliai cell integrin αVβ3 in the disruption of the tumor vascuiature induced by TNF and IFN-γ.Nat Med. 1998 April;4:408-414.
  8. Sujlana P, Skrok J, Fayad LM. Review of dynamic contrastenhanced MRI: Technical aspects and applications in themusculoskeletal system. Journal of Magnetic ResonanceImaging.2018 Apr;47(4):875-890.
  9. Rumley CN, Lee MT, Holloway L, Rai R, Min M , et al. Multiparametricmagnetic resonance imaging in mucosal primary head and neckcancer: A prospective imaging biomarker study. BMC Cancer.2017 Jul;17(1):475.
  10. Venianaki M, Salvetti O, de Bree E, T. Maris, A. Karantanas, et al.Pattern recognition and pharmacokinetic methods on DCE-MRIdata for tumor hypoxia mapping in sarcoma. Multimedia Toolsand Application 2017 Aug;1-23.
  11. Kuhl CK, Mielcareck P, Klaschik S, Leutner C, Wardelmann E, et al.Dynamic breast MR imaging: are signal intensity time course datauseful for differential diagnosis of enhancing lesions? Radiology.1999 Apr;211(1):101-110.
  12. Tofts PS, Kermode AG. Measurement of the blood-brain barrierpermeability and leakage space using dynamic MR imaging. 1.Fundamental concepts. Magn Reson Med.1991 Feb;17(2):357-367.
  13. Federau C. Intravoxel incoherent motion MRI as a means tomeasure in vivo perfusion: A review of the evidence. NMRBiomed. 2017 Nov;30(11).
  14. Howe FA, Robinson SP, McIntyre DJO, Stubbs M, Griffiths JR. Issuesin flow and oxygenation dependent contrast (FLOOD) imaging oftumours. NMR Biomed. 2001 Nov-Dec;14(7-8):497-506.
  15. Preda A, Wielopolski Pa, Ten Hagen TLM, van Vliet M, VeenlandJF, et al. Dynamic contrast-enhanced MRI using macromolecularcontrast media for monitoring the response to isolated limbperfusion in experimental soft-tissue sarcomas. MAGMA. 2004Dec;17(3-6):296-302.
  16. Kontopodis E, Karatzanis I, Sakkalis V, Francesca B, Marias K. ADCE-MRI analysis workflow. In: CGI ’16:Proceedings of the 33rdComputer Graphics International Conference. 2016:101-104. 
  17. Manikis GC, Nikiforaki K, Papanikolaou N, Marias K. DiffusionModelling Tool (DMT) for the analysis of Diffusion WeightedImaging (DWI) Magnetic Resonance Imaging (MRI) data. In: CGI’16:Proceedings of the 33rd Computer Graphics InternationalConference. 2016:97-100. 
  18. Weidner N, Semple JP, Welch WR, Folkman J. Tumor angiogenesisand metastasis--correlation in invasive breast carcinoma. N EnglJ Med. 1991 Jan;324:1-8.
  19. Chalkley HW. Method for the quantitative morphologic analysis oftissues. J Natl Cancer Inst. 1943 Aug;4(1):47-53.