Predictive model based on magnetic resonance imaging for chemotherapy response in colorectal cancer: Toward a radiologic biopsy approach

Abstract

We read with great interest the investigation of Kang et al related the applications of the multiparametric magnetic resonance imaging-based predictive model for assessing chemotherapy efficacy in colorectal cancer patients with gene mutations. The authors focused on decision-making based on the integration of tumor differentiation, signal intensity ratio, margin distance, and magnetic resonance imaging-detected lymph node metastasis. Indeed, these multiparameter predictive models could also be used for diagnosis as an alternative to invasive tissue examination methods. However, progress in this field enables us to shift the paradigm to radiology biopsies, particularly given the nonlinear effects of various radiation sources.

Key Words: Biopsy; Cancer; Extracellular matrix; Oncology; Radiology; Tumor microenvironment; Tumorigenesis

Core Tip: This letter comments on Kang et al’s magnetic resonance imaging-based model for evaluating chemo efficacy in mutated colorectal cancer, notes its diagnostic potential, and suggests shifting to radiology biopsies considering radiation nonlinear effects. Advanced contrast agents and super-resolution methods allow for novel diagnostic procedures, radiologic biopsies, which can be used for cancer diagnostics and to provide basic data on the extracellular matrix alterations.

TO THE EDITOR

We read with great interest the investigation by Kang et al[1] regarding the application of a multiparametric magnetic resonance imaging (MRI)-based predictive model to assess the efficacy of chemotherapy in patients with colorectal cancer and gene mutations. The authors focused on decision-making based on integrating tumor differentiation, signal intensity ratio, margin distance, and MRI-detected lymph node metastasis. However, these multiparameter predictive models could also be used for diagnosis as a noninvasive method of tissue examination.

Currently, non-invasive biopsy remains unavailable, leaving only liquid biopsy, needle biopsy, and other minimally invasive approaches for deriving biomaterials for biochemical analysis. In non-invasive procedures, the hypothetical use of radiological methods for cancer diagnosis is limited by detector resolution and sensitivity[2]. Although spectral approaches are available to identify cancer stroma patterns, they require minimal surgical access and chemical enhancers of the optical signal[3]. However, progress in this field allows to change the paradigm, especially in light of nonlinear effects of radiation methods, which allows for super-resolution to be achieved using either technical equipment or an enhancer of optical signals, such as biochemically inert “quantum dots”.

Radiologic biopsy vs radiology-guided biopsy

Advances in improving the effectiveness of routine radiological methods and signal processing have increased the diagnostic value of medical devices[4]. Noninvasive photothermal therapy of nasopharyngeal cancer, guided by high-efficiency optical-absorption nanomaterials enhanced by near-infrared photoacoustic imaging, has been studied[5]. The primary diagnostic responsibility of radiologists is to detect synchronous and metachronous lesions in order to identify colorectal liver metastases[6]. MRI tumor volumetry is a new staging tool for diagnosing and treating oral cancer[7]. Beyond less invasive biopsies and liquid biopsies, advanced contrast agents allow for novel diagnostic procedures, such as radiology biopsies, which can be used for cancer diagnostics and extracellular matrix (ECM) alterations.

The radiologic biopsy differs from current approaches of radiology-guided biopsy, which use the known anatomical landmarks to guide the needle. This proposed approach is strongly based on the unique biochemical and macromolecular properties of tumor cells and their ECM[8]. For example, the cellular density of malignant lymphoma can be evaluated using equivalent cross-relaxation rate imaging[9]. A radiologic biopsy approach that identifies tumors based on spectral patterns and could, in the future, will eliminate the need for contrast agents to derive the high-resolution data[10-12] (Table 1).

Table 1 Comparison of the key parameters of radiology-guided and radiologic biopsy approaches.

Parameter	Radiology-guided biopsy	Radiologic biopsy
Invasiveness	Mini-invasive surgical/needle extraction	Minimally invasive (contrast agent injection only)
Spatial coverage	Single small sample	Entire lesion, margins, surrounding tissue
Spatial resolution	High	Medium
Temporal resolution	Histology processing time (days)	Real-time to minutes
3D information	Limited (serial sections)	Complete 3D reconstruction
Molecular profiling	Histology, IHC, genomics	Multiplexed (limited markers)
Sampling error	High (tumor heterogeneity)	Medium (complete lesion surveyed)
Repeat assessment	Requires new biopsy	Non-destructive, repeatable
Functional information	Static snapshot	Limited dynamics

IHC: Immunohistochemistry.

The additional value of the radiologic biopsy is related to the modulation properties of the ECM, which are regulated by immune cell infiltration[13]. Additionally, immune cells modify the molecular composition and mechanical structure of the tumor stroma[14]. The interactions between resident cell regulation and ECM patterns allow us to investigate radiological contrast objects for diagnosis and prognosis.

Previously, evaluating ECM properties was mostly important for diagnostic purposes, such as identifying tumor patterns in histological slides. Currently, the novel concept of ECM-driven malignancy transformation, called “oncomatrix”[8], allows one to theoretically identify the properties of the cellular microenvironment that could shift cellular regulation toward tumor growth. This effect could transform the diagnostic and predictive applications, including the prediction of the effectiveness of advanced therapies, such as chimeric antigen receptor-modified T therapy for solid tumors and mRNA vaccines.

Conclusion

The dramatic progress in the development of radiological devices and embedded software could allow for precision diagnostics and differential diagnostics of tumors and pre-tumor conditions. These methods are based on unique patterns associated with tumor ECM formation and maturation.