RESUMEN
Pulmonary arterial hypertension (PAH) is a complex disease involving increased resistance in the pulmonary arteries and subsequent right ventricular (RV) remodeling. Ventricular-arterial interactions are fundamental to PAH pathophysiology but are rarely captured in computational models. It is important to identify metrics that capture and quantify these interactions to inform our understanding of this disease as well as potentially facilitate patient stratification. Towards this end, we developed and calibrated two multi-scale high-resolution closed-loop computational models using open-source software: a high-resolution arterial model implemented using CRIMSON, and a high-resolution ventricular model implemented using FEniCS. Models were constructed with clinical data including non-invasive imaging and invasive hemodynamic measurements from a cohort of pediatric PAH patients. A contribution of this work is the discussion of inconsistencies in anatomical and hemodynamic data routinely acquired in PAH patients. We proposed and implemented strategies to mitigate these inconsistencies, and subsequently use this data to inform and calibrate computational models of the ventricles and large arteries. Computational models based on adjusted clinical data were calibrated until the simulated results for the high-resolution arterial models matched within 10% of adjusted data consisting of pressure and flow, whereas the high-resolution ventricular models were calibrated until simulation results matched adjusted data of volume and pressure waveforms within 10%. A statistical analysis was performed to correlate numerous data-derived and model-derived metrics with clinically assessed disease severity. Several model-derived metrics were strongly correlated with clinically assessed disease severity, suggesting that computational models may aid in assessing PAH severity.
RESUMEN
Colorectal cancer is the third most common cause of cancer-related deaths with approximately 40%-50% of people diagnosed experiencing subsequent metastases. Surgery is the only curative treatment for colorectal cancer, although chemotherapy and radiation are often used neoadjuvantly or adjuvantly to decrease recurrence rates and improve survival. Many individuals experience adverse effects and physical impairments secondary to extensive medical treatment. Therefore, the purpose of this case is to signify the important role of physical therapy in the continuum of care of a patient diagnosed with metastatic rectal cancer and subsequent spinal cord compression. The patient was a 70-year-old male admitted to the hospital for lower extremity (LE) numbness and weakness secondary to metastatic rectal cancer. Seventeen months prior to hospitalization, he was diagnosed with rectal cancer and underwent neoadjuvant chemotherapy and radiation followed by laparoscopic abdominoperineal resection with posterior prostatectomy en bloc with a colostomy. Adjuvant chemotherapy included FOLFIRI. While hospitalized, the patient experienced spinal cord compression secondary to metastasis and elected decompressive laminectomy with discectomy for palliation. Due to the poor prognosis of metastatic rectal cancer, the patient's functional mobility and independence declined throughout hospitalization. The patient was able to achieve one of two personal goals; he was able to tolerate sitting in an upright position for his daughter's wedding but unfortunately did not return home prior to expiration. Although the patient suffered eventual mortality, consistent physical therapy allowed him to achieve a major life goal, serving as an important motivator and improved quality of life (QoL) even in end-of-life conditions. Unfortunately, physical therapy services are often overlooked and under-utilized in patients with terminal conditions receiving palliative care, despite the growing body of literature supporting the benefits. By utilizing rehabilitation in reverse as well as skilled maintenance, physical therapy assists in maintaining mobility and achieving personal goals of individuals with terminal cancer, thus improving QoL even with a poor prognosis.