# Breath Analysis: A Promising Tool for Disease Diagnosis--The Role of Sensors
## 4 Differential Diagnosis and Disease Phenotyping and Staging in Breath Analysis
### The Case for Lung Diseases
In a different study, LC was accurately distinguished from pulmonary non-malignant diseases (PNMD; COPD, pulmonary tuberculosis, asthma) using 10 VOCs while 5 were selected as characteristic of LC in contrast to both PNMD and HC [213]. The differentiation of LC patients from patients with benign pulmonary nodules (BPN) has also been extensively reported. Apart from a study by [PERSON] et al. [18] which included patients with benign lung tumors, [PERSON] et al. have investigated the respective discriminant ability of carbonyl VOCs [214; 215; 216]. Four carbonyl VOCs, captured by a silicon micro-reactor, were found to present increased concentration in LC patients when compared to BPN patients and HC [214]. In a subsequent study, the same group achieved the differentiation of both early and III, IV stage LC patients from BPN patients, with high sensitivity (83%) and particularly increased specificity (74%) in comparison to positron emission tomography (90% and 39%, respectively) [215], while 6 carbonyl VOCs have permitted a classification accuracy of 89% of LC vs. BPN patients [216]. More recently, [PERSON] et al. identified 19 VOCs able to distinguish not only LC and BPN patients (this with an accuracy of 80.9%) but also early-stage LC patients from BPN (with an accuracy of 75.6%), being remarkably promising for early LC diagnosis [204]. LC histology and staging characterization using analytical methods is another important target of this research field. It was reported that 1-butanol, 3-hydroxy-2-butanone [9], as well as 4-hydroxyhexenal [214], can differentiate SCC from ADC patients with the former being decreased for SCC in contrast to the other 2 VOCs. Similarly, SCLC and NSCLC can be potentially distinguished from 4-hydroxymonenal and C\({}_{5}\)H\({}_{10}\)O [214]. Hexanal has also been found in higher concentrations for SCLC patients compared to NSCLC, potentially due to increased metabolic rates [209]; [PERSON] et al. have achieved NSCLC and SCLC differentiation, with an accuracy of 93.9%, using a pattern of 20 VOCs [204]. Concerning LC staging (I, II, III, or IV), a pattern of 19 VOCs was used to distinguish between early (I, II) and advanced LC stages (III, IV) with 82.7% accuracy [204] while [PERSON] et al. demonstrated that exhaled 2-butanone concentration is significantly different between stages I and II-IV [214]. Apart from LC, other lung diseases are also studied for accurate diagnosis. A series of studies have focused on asthma phenotyping using GC-MS. [PERSON] et al. identified 3 VOCs significantly correlated with sputum eosinophils [90], while [PERSON] et al. identified VOC-patterns differentiating eosinophil from non-eosinophilic (6 VOCs) and neutrophil from non-neutrophilic (7 VOCs) [217]. Recently, [PERSON] et al. identified 4 VOCs discriminating eosinophil from neutroph, eosinophilic from paucigranulocytic and neutrophil from paucigranulocytic asthma, with accuracy similar to blood eosinophils and FeNO tests [205]. In a more recent study, the same group used two-dimensional GC-high resolution-time-of-flight-MS, selected ion flow tube mass spectrometry (SIFT-MS), 10 VOCs, and 9 ion channels so as to achieve asthma phenotyping with an accuracy of 75% [206]. COPD phenotyping and staging has also been attempted using analytical tech niques. [PERSON] et al. identified 8 eosinophils- and 17 neutrophils-related VOCs, with only one VOC overlapping between the two subgroups. More VOCs were related with cell counts for Global Initiative for Obstructive Lung Disease (GOLD) stage II, in comparison to GOLD stage I [120]. In another study, 11 COPD patients with >1% and 6 with >2% eosinophil count were discriminated from non-eosinophilics (<1% and <2% eosinophil count, respectively) with accuracies of 79% and 92% [218]. Exacerbation prediction of both asthmatic children [219; 220; 221] and adults [90; 217] as well as COPD patients [222] also comprises a subject of study.