Prediction of tumor size in patients with invasive ductal carcinoma using FT-IR spectroscopy combined with chemometrics: a preliminary study

Author(s):  
Zhimin Zhu ◽  
Cheng Chen ◽  
Chen Chen ◽  
Ziwei Yan ◽  
Fangfang Chen ◽  
...  
Optik ◽  
2020 ◽  
Vol 204 ◽  
pp. 164225 ◽  
Author(s):  
Jie Liu ◽  
Hong Cheng ◽  
Xiaoyi Lv ◽  
Zhaoxia Zhang ◽  
Xiangxiang Zheng ◽  
...  

Author(s):  
Maciej Strzempek ◽  
Karolina A. Tarach ◽  
Kinga Góra-Marek ◽  
Fernando Rey ◽  
Miguel Palomino ◽  
...  

Abstract In this article the results of the statistical MC modelling corroborated by the FT-IR spectroscopy and gravimetric adsorption studies of the low aliphatic hydrocarbons in ZSM-5 (Si/Al =28 or...


2021 ◽  
Vol 22 (4) ◽  
pp. 2191
Author(s):  
Jing Huang ◽  
Nairveen Ali ◽  
Elsie Quansah ◽  
Shuxia Guo ◽  
Michel Noutsias ◽  
...  

In recent decades, vibrational spectroscopic methods such as Raman and FT-IR spectroscopy are widely applied to investigate plasma and serum samples. These methods are combined with drop coating deposition techniques to pre-concentrate the biomolecules in the dried droplet to improve the detected vibrational signal. However, most often encountered challenge is the inhomogeneous redistribution of biomolecules due to the coffee-ring effect. In this study, the variation in biomolecule distribution within the dried-sample droplet has been investigated using Raman and FT-IR spectroscopy and fluorescence lifetime imaging method. The plasma-sample from healthy donors were investigated to show the spectral differences between the inner and outer-ring region of the dried-sample droplet. Further, the preferred location of deposition of the most abundant protein albumin in the blood during the drying process of the plasma has been illustrated by using deuterated albumin. Subsequently, two patients with different cardiac-related diseases were investigated exemplarily to illustrate the variation in the pattern of plasma and serum biomolecule distribution during the drying process and its impact on patient-stratification. The study shows that a uniform sampling position of the droplet, both at the inner and the outer ring, is necessary for thorough clinical characterization of the patient’s plasma and serum sample using vibrational spectroscopy.


Breast Cancer ◽  
2021 ◽  
Author(s):  
Kiyo Tanaka ◽  
Norikazu Masuda ◽  
Naoki Hayashi ◽  
Yasuaki Sagara ◽  
Fumikata Hara ◽  
...  

Abstract Background We conducted a prospective study with the intention to omit surgery for patients with ductal carcinoma in situ (DCIS) of the breast. We aimed to identify clinicopathological predictors of postoperative upstaging to invasive ductal carcinoma (IDC) in patients preoperatively diagnosed with DCIS. Patients and methods We retrospectively analyzed patients with DCIS diagnosed through biopsy between April 1, 2010 and December 31, 2014, from 16 institutions. Clinical, radiological, and histological variables were collected from medical records. Results We identified 2,293 patients diagnosed with DCIS through biopsy, including 1,663 DCIS (72.5%) cases and 630 IDC (27.5%) cases. In multivariate analysis, the presence of a palpable mass (odds ratio [OR] 1.8; 95% confidence interval [CI] 1.2–2.6), mammography findings (≥ category 4; OR 1.8; 95% CI 1.2–2.6), mass formations on ultrasonography (OR 1.8; 95% CI 1.2–2.5), and tumor size on MRI (> 20 mm; OR 1.7; 95% CI 1.2–2.4) were independent predictors of IDC. Among patients with a tumor size on MRI of ≤ 20 mm, the possibility of postoperative upstaging to IDC was 22.1%. Among the 258 patients with non-palpable mass, nuclear grade 1/2, and positive for estrogen receptor, the possibility was 18.1%, even if the upper limit of the tumor size on MRI was raised to ≤ 40 mm. Conclusion We identified four independent predictive factors of upstaging to IDC after surgery among patients with DCIS diagnosed by biopsy. The combined use of various predictors of IDC reduces the possibility of postoperative upstaging to IDC, even if the tumor size on MRI is larger than 20 mm.


1989 ◽  
Author(s):  
Ning Xi ◽  
Shifu Weng ◽  
Jinguang Wu ◽  
Guangxian Xu

2020 ◽  
Author(s):  
Milena Pavlíková ◽  
Lenka Scheinherrová ◽  
Martina Záleská ◽  
Zbyšek Pavlík

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