Dual-input tracer kinetic modeling of dynamic contrast-enhanced MRI in thoracic malignancies

Our plain-English summary of Dual-input tracer kinetic modeling of dynamic contrast-enhanced MRI in thoracic malignancies, by S.H. Lee, A. Rimner, J.O. Deasy, et al (Journal of Applied Clinical Medical Physics, 2019).

The study

• Authors: S.H. Lee, A. Rimner, J.O. Deasy, M.A. Hunt, N. Tyagi
• Journal: Journal of Applied Clinical Medical Physics
• Published: 2019;20(11):169-188
• Cited by: 5 articles, as counted by NIH iCite
• Read it: PubMed · Publisher · Free full text

Abstract

Pulmonary perfusion with dynamic contrast-enhanced (DCE-) MRI is typically assessed using a single-input tracer kinetic model. Preliminary studies based on perfusion CT are indicating that dual-input perfusion modeling of lung tumors may be clinically valuable as lung tumors have a dual blood supply from the pulmonary and aortic system. This study aimed to investigate the feasibility of fitting dual-input tracer kinetic models to DCE-MRI datasets of thoracic malignancies, including malignant pleural mesothelioma (MPM) and nonsmall cell lung cancer (NSCLC), by comparing them to single-input (pulmonary or systemic arterial input) tracer kinetic models for the voxel-level analysis within the tumor with respect to goodness-of-fit statistics. Fifteen patients (five MPM, ten NSCLC) underwent DCE-MRI prior to radiotherapy. DCE-MRI data were analyzed using five different single- or dual-input tracer kinetic models: Tofts-Kety (TK), extended TK (ETK), two compartment exchange (2CX), adiabatic approximation to the tissue homogeneity (AATH) and distributed parameter (DP) models. The pulmonary blood flow (BF), blood volume (BV), mean transit time (MTT), permeability-surface area product (PS), fractional interstitial volume (vI ), and volume transfer constant (KTrans ) were calculated for both single- and dual-input models. The pulmonary arterial flow fraction (γ), pulmonary arterial blood flow (BFPA ) and systemic arterial blood flow (BFA ) were additionally calculated for only dual-input models. The competing models were ranked and their Akaike weights were calculated for each voxel according to corrected Akaike information criterion (cAIC). The optimal model was chosen based on the lowest cAIC value. In both types of tumors, all five dual-input models yielded lower cAIC values than their corresponding single-input models. The 2CX model was the best-fitted model and most optimal in describing tracer kinetic behavior to assess microvascular properties in both MPM and NSCLC. The dual-input 2CX-model-derived BFA was the most significant parameter in differentiating adenocarcinoma from squamous cell carcinoma histology for NSCLC patients.

© 2019 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

In plain English

This was a small imaging-methods study, not a study of asbestos exposure. The authors tested whether computer models treating a chest tumor as fed by two blood supplies (pulmonary artery and aorta) fit contrast-enhanced MRI scans better than single-supply models. Fifteen patients were scanned as part of planning for radiation therapy: five with malignant pleural mesothelioma and ten with non-small cell lung cancer (five adenocarcinoma, five squamous cell carcinoma). Five models were fitted to each tumor voxel (small image unit). In both tumor types, every model fit better with two blood inputs than with one. The two-compartment exchange (2CX) model was most often the best fit. In the lung cancer patients, systemic arterial blood flow estimated by the dual-input 2CX model was higher in adenocarcinoma than in squamous cell carcinoma (P = 0.016). Under the dual-input 2CX, AATH and DP models, pulmonary arterial flow exceeded systemic flow in both tumor types, but systemic flow was not negligible in any model. The authors called this a pilot study and noted the small number of patients. They noted that a good fit does not necessarily mean accurate parameter estimates.

We wrote this plain-English summary from the full article with the help of AI, and a second AI model checked each sentence against the article. It is not the authors' wording; the abstract and the article are their own account.

What the study did and found

• Design: Prospective pilot imaging study comparing single-input and dual-input tracer kinetic models applied to dynamic contrast-enhanced MRI (DCE-MRI) data
• Who was studied: 15 patients with a single primary thoracic malignancy. Five had malignant pleural mesothelioma (MPM): 3 men and 2 women, ages 59 to 77, all epithelioid histology. Ten had non-small cell lung cancer (NSCLC): 6 men and 4 women, ages 51 to 89; 5 adenocarcinoma and 5 squamous cell carcinoma. Patients were scanned as part of their radiation therapy simulation. The authors are at Memorial Sloan Kettering Cancer Center, New York. Study dates are not given.
• Exposure: No asbestos exposure was studied. Asbestos is mentioned only as background. What the study compared was methods of analysing MRI scans taken after injection of a gadolinium contrast agent (Gd-DTPA): five tracer kinetic models (TK, ETK, 2CX, AATH, DP), each run with a pulmonary, a systemic or a dual arterial input.
• Main results:
  • In both MPM and NSCLC, all five models gave lower cAIC values (a measure where lower means a better statistical fit) with the dual input than with either single input.
  • The 2CX model was most often the best-fitting model. With the dual input, it was optimal in 46% of the 58,367 MPM voxels and 42.4% of the 165,864 NSCLC voxels. It was followed by the AATH, DP, TK and ETK models.
  • In the NSCLC patients (5 adenocarcinoma vs 5 squamous cell carcinoma), the only dual-input parameter that differed statistically significantly was systemic arterial blood flow estimated by the 2CX model. It was higher in adenocarcinoma: the population mean of intratumoral medians was 27.16 mL/min/100g for adenocarcinoma vs 4.118 for squamous cell carcinoma (P = 0.016).
  • With systemic arterial input only, three parameters from the DP model differed significantly between adenocarcinoma and squamous cell carcinoma (each P = 0.032). The authors noted that this model's fitting error was considerably larger than that of the dual-input 2CX model in NSCLC.
  • Pulmonary arterial blood flow was higher than systemic arterial blood flow for the dual-input 2CX, AATH and DP models in both tumor types. For the TK model this held only in NSCLC, and for the ETK model only in MPM. Systemic arterial flow was not negligible in any of the five models.
  • Correcting the images for breathing motion produced large differences in the estimated parameter values for all models.
• The authors' conclusion: The authors concluded that, for most voxels, the dual-input 2CX model best described contrast agent behavior in both MPM and NSCLC. They also concluded that, although pulmonary arterial flow exceeded systemic flow in both tumor types, the systemic arterial contribution to tumor perfusion could still be substantial.
• Limitations the authors state:
  • The number of patients was small.
  • A larger patient group is needed to validate the clinical usefulness of the approach.
  • A good statistical fit does not necessarily mean the parameter estimates are accurate.
  • The 2CX model assumes the contrast agent mixes instantly in the capillaries, which might be unrealistic.
  • Whether the arterial input model is appropriate depends on the injection protocol, temporal resolution and imaging duration.

Topics

The National Library of Medicine indexes this study under subjects our site covers: Lung cancer, Mesothelioma.

Medical terms in this study, explained in our Lexicon: Pleural Mesothelioma, Lung Cancer, Interstitial, Adenocarcinoma, Squamous Cell Carcinoma, Histology.

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