Browsing Scholarly Projects 2021 by Subjects
Now showing items 1-3 of 3
Anaplastic Thyroid Cancer: The Trajectory of Prolonged Diagnosis and Short SurvivalPurpose: Anaplastic thyroid cancer (ATC) is almost uniformly lethal in its progression, but due to its rarity and complexity, its presentation is difficult to recognize and manage by physicians and patients alike. Delayed diagnosis is common and makes ATC virtually untreatable. We aim to examine the number of appointments with healthcare providers, imaging studies performed, and admission days as metrics of delayed diagnosis in order to identify opportunities to expedite care of ATC patients in the future. Methods: A retrospective electronic medical record review was conducted to include 8 patients from January 2016 to December 2018. Both pre- and post-diagnosis variables were examined and include: number of unique encounters, type/number of imaging studies, demographics (sex, ethnicity, residence, employment, religion, language, marital status), days admitted inpatient, time to diagnosis, and specific medical specialties utilized. Pre- and post-diagnosis imaging studies included computer tomography (CT), magnetic resonance imaging (MRI), ultrasound (US), radiographs (X-ray), and positron emission tomography (PET). IRB approval was obtained through the UA BEACON© registry. Results: We analyzed 4 women and 4 men with ATC whose mean time to diagnosis (TTD) from initial chief complaint was 53 days. In that time, 12 clinicians per patient (median) provided care. Men had a far longer mean TTD compared to women (75 vs 31 days), as well as longer mean inpatient admission for evaluation (19 vs 11 days). After ATC diagnosis, the median number of encounters per patient rose to 24.5, reflecting multispecialty care required for treatment. Here also, men had more median post-diagnosis specialist encounters than women (41.5 vs 11). Female patients had a median number of 4 imaging studies pre-diagnosis and 2 imaging studies post-diagnosis while male patients had a median number of 6 imaging studies pre-diagnosis and 12.5 imaging studies post-diagnosis. Discussion: This study suggests that male patients with ATC have a more difficult trajectory both pre- and post-diagnosis compared to female patients. They require longer time and more imaging studies before physicians arrive at the ATC diagnosis. Subsequently, men stay longer in the hospital, still with significantly higher numbers of studies and physician encounters. The root causes of this gender discrepancy are unclear and likely multifactorial, but could represent greater ATC disease severity and gender-specific barriers to care. This study highlights the need to recognize early signs of ATC and consider this diagnosis sooner.
CT Texture Analysis (CTTA): Developing a Diagnostic Imaging Biomarker for KRAS Mutation in Metastatic Colon CancerPURPOSE To evaluate multi-parametric modeling on imaging textures from contrast-enhanced, multiphasic computed tomography (CT) for identification of Kirsten rat sarcoma (KRAS) gene mutations in metastatic colon cancer to the liver. METHOD AND MATERIALS This retrospective study included 99 patients diagnosed histologically with colon cancer: 51 KRAS wild-type and 48 KRAS gene mutation. Matched-size regions of interest (ROIs) were drawn over viable tumor and unaffected background liver on multiphase CT. Paired ROIs were spatially rescaled, intensity-normalized, and then analyzed using 3 Texture Algorithms: GLCM, LBP, and Gabor. Feature selection method was based on KNN classifier and DEFS (Differential Evolution-based Feature Selection). For each of the 30 independent experiments, patients were randomly allocated into training (n = 79) and testing (n = 20) datasets to develop predictive models for KRAS gene mutation. Classification models were generated based on: 1) All features; and 2) Selected features as per DEFS. RESULTS Predictive models utilizing all 56 features (13 GLCM, 26 LBP, and 14 Gabor) resulted in an average accuracy/sensitivity/specificity of 61/54/62%; ranging from a single best model (80/80/90%) to a single worst model (35/20/20%). Predictive models utilizing a DEFS optimized 3-feature subset resulted in average accuracy/sensitivity/specificity of 89/80/84%; ranging from a single best model (95/92/96%) to a single worst model (80/68/68%). Among the three texture algorithms, LBP provided better discriminatory power compared to GLCM and Gabor. CONCLUSION Utilizing advanced analytics with machine learning techniques (CTTA and DEFS selection analysis), multi-textural data obtained from conventional, multiphase CT images has the capability to detect a therapeutically relevant genetic aberration (KRAS mutation) in metastatic colon cancer with high accuracy, sensitivity and specificity.
How Are Pancreas Cancer Surgery Outcomes Affected by Tumor Board Decisions?Tumor board review of complex patients is an important factor for quality and safety. In this study, we compare the surgical outcomes of patients presented at two gastrointestinal cancerspecific tumor boards within a large healthcare system. Site A represents an academic-type tumor board with a focus on neoadjuvant therapy, whereas Site B represents a community-type tumor board with a primary surgical approach.