RESUMEN
BACKGROUND: The poor prognosis of patients with colorectal-cancer liver metastases (CRLM) and the insufficiency of available treatments have raised the need for alternative curative strategies. We aimed to assess the therapeutic potential of TL-118, a new anti-angiogenic drug combination, for CRLM treatment, in a mouse model. METHODS: The therapeutic potential of TL-118 was evaluated and compared with B20-4.1.1 (B20; anti-VEGF antibody) and rapamycin in CRLM-bearing mice. Tumour progression and the vascular changes were monitored by MRI. Additionally, mice survival, cell proliferation, apoptosis and vessel density were evaluated. RESULTS: This study demonstrated an unequivocal advantage to TL-118 therapy by significantly prolonging survival (threefold) and reducing metastasis perfusion and vessel density (ninefold). The underlying mechanism for TL-118-treatment success was associated with hepatic perfusion attenuation resulting from reduced nitric-oxide (NO) serum levels as elucidated by using hemodynamic response imaging (HRI, a functional MRI combined with hypercapnia and hyperoxia). Further, systemic hepatic perfusion reduction during the initial treatment phase by adding NO inhibitor has proven to be essential for reaching maximal therapeutic effects for both TL-118 and B20. CONCLUSION: TL-118 harbours a potential clinical benefit to CLRM patients. Moreover, the reduction of hepatic perfusion at early stages of anti-angiogenic therapies by adding NO inhibitor is crucial for achieving maximal anti-tumour effects.
Asunto(s)
Inhibidores de la Angiogénesis/farmacología , Cimetidina/uso terapéutico , Neoplasias Colorrectales/patología , Ciclofosfamida/uso terapéutico , Diclofenaco/uso terapéutico , Neoplasias Hepáticas/prevención & control , Neoplasias Hepáticas/secundario , Sulfasalazina/uso terapéutico , Inhibidores de la Angiogénesis/uso terapéutico , Animales , Cimetidina/farmacología , Neoplasias Colorrectales/irrigación sanguínea , Neoplasias Colorrectales/tratamiento farmacológico , Neoplasias Colorrectales/mortalidad , Ciclofosfamida/farmacología , Diclofenaco/farmacología , Progresión de la Enfermedad , Combinación de Medicamentos , Humanos , Neoplasias Hepáticas/tratamiento farmacológico , Neoplasias Hepáticas/metabolismo , Imagen por Resonancia Magnética , Masculino , Ratones , Óxido Nítrico/metabolismo , Sulfasalazina/farmacologíaRESUMEN
This paper presents a machine-learning approach to the interactive classification of suspected liver metastases in fMRI images. The method uses fMRI-based statistical modeling to characterize colorectal hepatic metastases and follow their early hemodynamical changes. Changes in hepatic hemodynamics are evaluated from T2*-W fMRI images acquired during the breathing of air, air-CO2, and carbogen. A classification model is build to differentiate between tumors and healthy liver tissues. To validate our method, a model was built from 29 mice datasets, and used to classify suspicious regions in 16 new datasets of healthy subjects or subjects with metastases in earlier growth phases. Our experimental results on mice yielded an accuracy of 78% with high precision (88%). This suggests that the method can provide a useful aid for early detection of liver metastases.