MRI in predicting the response of gastrointestinal stromal tumor to targeted therapy: a patient-based multi-parameter study

Multiparametric MRI for characterization of the tumour microenvironment

Our understanding of tumour biology has evolved over the past decades and cancer is now viewed as a complex ecosystem with interactions between various cellular and non-cellular components within the tumour microenvironment (TME) at multiple scales. However, morphological imaging remains the mainstay of tumour staging and assessment of response to therapy, and the characterization of the TME with non-invasive imaging has not yet entered routine clinical practice. By combining multiple MRI sequences, each providing different but complementary information about the TME, multiparametric MRI (mpMRI) enables non-invasive assessment of molecular and cellular features within the TME, including their spatial and temporal heterogeneity. With an increasing number of advanced MRI techniques bridging the gap between preclinical and clinical applications, mpMRI could ultimately guide the selection of treatment approaches, precisely tailored to each individual patient, tumour and therapeutic modality. In this Review, we describe the evolving role of mpMRI in the non-invasive characterization of the TME, outline its applications for cancer detection, staging and assessment of response to therapy, and discuss considerations and challenges for its use in future medical applications, including personalized integrated diagnostics.

CT and MRI of Gastrointestinal Stromal Tumors: New Trends and Perspectives

Gastrointestinal stromal tumors (GISTs) are defined as mesenchymal tumors of the gastrointestinal tract that express positivity for CD117, which is a c-KIT proto-oncogene antigen. Expression of the c-KIT protein, a tyrosine kinase growth factor receptor, allows the distinction between GISTs and other mesenchymal tumors such as leiomyoma, leiomyosarcoma, schwannoma and neurofibroma. GISTs can develop anywhere in the gastrointestinal tract, as well as in the mesentery and omentum. Over the years, the management of GISTs has improved due to a better knowledge of their behaviors and risk or recurrence, the identification of specific mutations and the use of targeted therapies. This has resulted in a better prognosis for patients with GISTs. In parallel, imaging of GISTs has been revolutionized by tremendous progress in the field of detection, characterization, survival prediction and monitoring during therapy. Recently, a particular attention has been given to radiomics for the characterization of GISTs using analysis of quantitative imaging features. In addition, radiomics has currently many applications that are developed in conjunction with artificial intelligence with the aim of better characterizing GISTs and providing a more precise assessment of tumor burden. This article sums up recent advances in computed tomography and magnetic resonance imaging of GISTs in the field of image/data acquisition, tumor detection, tumor characterization, treatment response evaluation, and preoperative planning.

Whole tumor based texture analysis of magnetic resonance diffusion imaging for colorectal liver metastases: A prospective study for diffusion model comparison and early response biomarker

PURPOSE

To evaluate and compare the diagnostic value of diffusion-related texture analysis parameters obtained from various magnetic resonance diffusion models as early predictors of the clinical response to chemotherapy in patients with colorectal liver metastases (CRLM).

METHODS

Patients (n = 145) with CRLM were prospectively and consecutively enrolled and scanned using diffusion-weighted imaging (DWI)-magnetic resonance imaging (MRI)/intravoxel incoherent motion (IVIM)/diffusion kurtosis imaging (DKI) before (baseline) and two-three weeks after (follow-up) commencing chemotherapy. Therapy response was evaluated based on the Response Evaluation Criteria in Solid Tumors (RECIST, version 1.1). The histogram and texture parameters of each diffusion-related parametric map were analysed between the responding and non-responding groups, screened using LASSO, and fitted with binary logistic regression models. The diagnostic efficacy of each model in the early prediction of CRLM was analysed, and the corresponding receiver operating characteristic (ROC) curve was drawn. The area under the curve (AUC) and 95% confidence intervals (CI) were calculated.

RESULTS

Of the 145 analysed patients, 69 were in the responding group and 76 were in the non-responding group. Among all models, the difference value based on the histogram and texture features of the DKI-derived parameters performed best for the early prediction of CRLM treatment efficacy. The AUC of the DKI model in the validation set reached 0.795 (95% CI 0.652-0.938). Among the IVIM-derived parameters, the difference model based on D and D* performed best, and the AUC in the validation set reached 0.737 (95% CI 0.586-0.889). Finally, in the DWI sequence, the model comprising baseline features performed the best, with an AUC of 0.699 (95% CI 0.537-0.86) in the validation set.

CONCLUSIONS

Baseline DWI parameters and follow-up changes in IVIM and DKI parameters predicted the chemotherapeutic response in patients with CRLM. In addition, as very early predictors, DKI-derived parameters were more effective than DWI- and IVIM-related parameters, in which changes in D-parameters performed best.

Molecular and functional imaging in cancer-targeted therapy: current applications and future directions

Targeted anticancer drugs block cancer cell growth by interfering with specific signaling pathways vital to carcinogenesis and tumor growth rather than harming all rapidly dividing cells as in cytotoxic chemotherapy. The Response Evaluation Criteria in Solid Tumor (RECIST) system has been used to assess tumor response to therapy via changes in the size of target lesions as measured by calipers, conventional anatomically based imaging modalities such as computed tomography (CT), and magnetic resonance imaging (MRI), and other imaging methods. However, RECIST is sometimes inaccurate in assessing the efficacy of targeted therapy drugs because of the poor correlation between tumor size and treatment-induced tumor necrosis or shrinkage. This approach might also result in delayed identification of response when the therapy does confer a reduction in tumor size. Innovative molecular imaging techniques have rapidly gained importance in the dawning era of targeted therapy as they can visualize, characterize, and quantify biological processes at the cellular, subcellular, or even molecular level rather than at the anatomical level. This review summarizes different targeted cell signaling pathways, various molecular imaging techniques, and developed probes. Moreover, the application of molecular imaging for evaluating treatment response and related clinical outcome is also systematically outlined. In the future, more attention should be paid to promoting the clinical translation of molecular imaging in evaluating the sensitivity to targeted therapy with biocompatible probes. In particular, multimodal imaging technologies incorporating advanced artificial intelligence should be developed to comprehensively and accurately assess cancer-targeted therapy, in addition to RECIST-based methods.

Mesenchymal Neoplasms of the Prostate and Seminal Vesicles: Spectrum of Disease with Radiologic-Pathologic Correlation

There is a wide spectrum of benign and malignant mesenchymal neoplasms of the prostate, which account for less than 1% of all prostatic tumors. These include distinctive tumors that arise from the specialized prostatic stroma and site-agnostic neoplasms such as smooth muscle tumors, fibrous or myofibroblastic neoplasms, neurogenic tumors, vascular tumors, and a plethora of sarcomas. Select tumors show classic sites of origin within the prostate. While stromal tumors of uncertain malignant potential (STUMPs) commonly involve the peripheral zone at the prostate base, leiomyomas typically originate from the central prostate toward the apex. Some "prostatic" neoplasms such as gastrointestinal stromal tumors, solitary fibrous tumor (SFT), paragangliomas, and neurogenic tumors arise primarily from periprostatic soft tissues. Most mesenchymal tumors of the prostate and seminal vesicles manifest as large tumors that cause nonspecific symptoms; prostate-specific antigen level is not typically elevated. Diverse mesenchymal neoplasms demonstrate characteristic histopathologic and immunocytochemical features and variable cross-sectional imaging findings. While leiomyoma and SFT typically display low signal intensity on T2-weighted images, synovial sarcomas commonly show hemorrhage. Diagnosis is difficult because of the rarity and lack of awareness of the tumors and the significant overlap in histopathologic features. Select tumors show characteristic genetic abnormalities that allow the diagnosis to be established. For example, more than 90% of SFTs are characterized by a unique NAB2-STAT6 gene fusion, and more than 95% of synovial sarcomas are associated with a distinctive SYT-SSX chimeric transcript. Accurate diagnosis is imperative for optimal management owing to markedly different tumor biology as well as attendant therapeutic and prognostic implications. While STUMPs commonly recur, sarcomas typically charter an aggressive course with poor prognosis. Online supplemental material is available for this article. ^©RSNA, 2022.

Multimodal functional imaging for early response assessment in patients with gastrointestinal stromal tumor treated with tyrosine kinase inhibitors

BACKGROUND

Several imaging modalities are used in the early work-up of patients with gastrointestinal stromal tumor (GIST) receiving tyrosine kinase inhibitor (TKI) treatment and there is a need to establish whether they provide similar or complimentary information.

PURPOSE

To compare 18F-fluorodeoxyglucose positron emission tomography (FDG PET), computed tomography (CT) and magnetic resonance imaging (MRI) as early predictors of three-month outcomes for patients with GIST receiving TKI treatment.

MATERIAL AND METHODS

Thirty-five patients with advanced GIST were prospectively included between February 2011 and June 2017. FDG PET, contrast-enhanced CT (CECT), and MRI were performed before and early after onset of TKI treatment (range 8-18 days). Early response was categorized according to mRECIST (CT), the Choi criteria (CECT), and PERCIST (FDG PET/CT). For MRI, volumetry from T2-weighted images and change in apparent diffusion coefficient (ADC) from diffusion-weighted imaging was used. The reference standard for early assessment was the three-month mRECIST evaluation based on CT. At three months, both stable disease (SD) and partial response (PR) were categorized as response. Clinical usefulness was defined as agreement between early and three-month assessment.

RESULTS

At the three-month assessment, 91% (32/35) were responders, 37% (13/35) PR, 54% (19/35) SD, and 9% (3/35) had progressive disease (PD). Early assessment correctly predicted three-month response in 93% (27/29) for MRI, 80% (28/35) for PERCIST, 74% (26/35) for Choi, and 23% (8/35) for mRECIST. Six patients had non-FDG-avid tumors. For the FDG-avid tumors, PET/CT correctly predicted three-month response in 97% (28/29).

CONCLUSION

MRI was superior to CECT for early assessment of TKI-treatment response in GIST. If the tumor was FDG-avid, PET and MRI were equally good. Changes in functional parameters were superior to changes in longest tumor diameter (mRECIST).

Diffusion kurtosis imaging in the prediction of poor responses of locally advanced gastric cancer to neoadjuvant chemotherapy

PURPOSE

To assess the efficacy of diffusion kurtosis imaging (DKI) in the prediction of the treatment response to neoadjuvant chemotherapy in patients with locally advanced gastric cancer (LAGC).

METHODS

A total of 31 LAGC patients were enrolled in this prospective study. All patients underwent diffusion-weighted MRI examination (with b = 0₁, 200₁, 500₁, 800₂, 1000₄, 1500₄, 2000₆ s/mm², the subscript denotes the number of signal averages) before and after chemotherapy. DKI and mono-exponential (b = 0, 800 s/mm²) models were built. Apparent diffusion coefficient (ADC), mean diffusivity (MD) and mean kurtosis (MK) of the LAGC tumors were measured. The absolute change values (ΔX) and percentage change values (%ΔX) of the above parameters post neoadjuvant chemotherapy (NACT) were calculated. The response was evaluated according to the pathological tumor regression grade scores (effective response group: TRG 0-2, poor response group: TRG 3). Mann-Whitney U test and receiver operating characteristic (ROC) curves were applicated for statistical analysis.

RESULTS

There were 17 patients in the effective response group (ERG), and 14 patients in the poor response group (PRG). The MK_pre and MK_post values in PRG were significantly higher than those in ERG [(0.671 ± 0.026) and (0.641 ± 0.019) vs. (0.584 ± 0.023) and (0.519 ± 0.018), p < 0.001]. ADC_post and MD_post in PRG were significantly lower than those in ERG (p = 0.005, p =0.001). Significant differences were also observed for % ΔMK, ΔMD and ΔMK between the two groups (p < 0.05). The area under the curve (AUC) for the prediction of PRG was highest for MK_post (AUC = 0.958, cutoff value = 0.614). The MK_pre and MK_post had the highest sensitivity (91.70 %) and specificity (93.80 %) in the prediction of PRG, respectively.

CONCLUSION

Both DKI and ADC values show potential for the prediction of the PRG in LAGC patients. The DKI parameters, especially MK_post displayed the best performance.

BRD4 promotes tumor progression and NF-κB/CCL2-dependent tumor-associated macrophage recruitment in GIST

The most commonly occurring sarcoma of the soft tissue is gastrointestinal stromal tumor (GIST). Treatment and prevention of the disease necessitate an understanding of the molecular mechanisms involved. However, the role of BRD4 in the progression of GIST is still unclear. While it is known there are abundant infiltrating tumor-associated macrophages (TAMs) in the tumor microenvironment, the exact role of these cells has yet to be studied. This work showed an upregulation of BRD4 in GIST that was associated with GIST prognosis. Through gain and loss of function studies, it was found that BRD4 promotes GIST growth and angiogenesis in vitro and in vivo. Mechanistically, BRD4 enhances CCL2 expression by activating the NF-κB signaling pathway. Furthermore, this CCL2 upregulation causes recruitment of macrophages into the tumor leading to tumor growth. A likely mechanism for interactions in the GIST microenvironment has been outlined by this work to show the role and potential use of BRD4 as a treatment target in GIST.

Prognosis assessment in metastatic gastrointestinal stromal tumors treated with tyrosine kinase inhibitors based on CT-texture analysis

PURPOSE

Identification of prognostic CT-textural features in patients with gastrointestinal stromal tumors undergoing tyrosine kinase inhibitor (TKI) therapy.

METHODS AND MATERIALS

We identified 25 GIST patients (mean age, 70.58 ± 9.7 years; range, 41.25-84.08 years; 20 males, 5 females) with a total of 123 scans, each examined with a standardized CT protocol between 1/2014-7/2018. 92 texture features, based on pyradiomics library, were extracted and correlated to response categories; evaluated with help of modified Choi criteria. All patients underwent therapy with imatinib in the first line and different tyrosine kinase inhibitors after disease progression. KIT and PDGFR-mutations were registered in all patients as well as the number of previous treatment regimens, patient's age as well as gender and the presence of contrast enhancement (vitality) in tumor. The lesion with the largest diameter was chosen and contoured using the spherical VOI tool. Inter-rater testing was performed by a second experienced radiologist. Regression and AUC analysis was performed.

RESULTS

Ten variables could be confirmed to be significantly associated with disease progression. Of them, four textural parameters were significantly positively associated with disease progression and negatively with progression free survival (Glcm Id [grey-level co-occurrence matrix inverse difference], p = 0.012, HR 3.83; 95% CI 1.697-8.611, Glcm Idn [grey-level co-occurrence matrix inverse difference normalized], p = 0.045, HR 2.06, 95% CI 1.015-4.185, Glrlm [grey-level run length matrix] normalized, p = 0.005, HR 3.181; 95% CI 1.418-7.138 and Ngtdm [neighboring grey-tone difference matrix] coarseness, p < 0.001, HR 3.156, 95% CI 1.554-6.411). Single variables were shown to be significantly inferior to the combination of all variables. After 6 months, 90% of patients with 0-1 risk factors (group 1), 64.4% with 2-3 risk variables and 38.1% of patients presenting > 3 structural risk variables showed stable disease. Gclm Id, Gclm Idn and Glrlm non-uniformity were associated with the number of previous treatments, Glrlm non-uniformity also with tumor vitality (enhancement), whereas Gclm Idn and Ngtdm coarseness were associated with the number of tumor mutations.

CONCLUSION

Some of the CT-textural features correlate with disease progression and the progressive free survival as well as with the number of gene mutations and the number of treatment regimens the patients were exposed to as well as with the tumor enhancement. All these features reflect tumor homogeneity.

Relationship between diagnostic imaging features and prognostic outcomes in gastrointestinal stromal tumors (GIST)

Gastrointestinal stromal tumors (GISTs), the most frequent mesenchymal neoplasms of the gastrointestinal tract, are a relatively recently described entity. GISTs can occur across any age but are more common in patients older than 50 years. GISTs most commonly are in the stomach (60-70%), followed by the small intestine (20%-30%); they also rarely occur in the abdominal cavity, such as in the mesentery, the omentum and the retroperitoneum. Contrast-enhanced multi-detector computed tomography (MDCT) is the most largely used imaging modality for the localization, characterization and staging of GISTs. All patterns of enhancement on contrast-enhanced MDCT can be seen with GISTs, including hypoenhancing, isoenhancing, and hyperenhancing neoplasms. A lot of prognostication systems have been proposed for the risk stratification of GISTs. This review outlines the relationship between different diagnostic imaging features and prognostic outcomes in GISTs.