Early detection of colorectal adenocarcinoma: a clinical decision support tool based on plasma porphyrin accumulation and risk factors.

BACKGROUND: An increase in naturally-occurring porphyrins has been described in the blood of subjects bearing different kinds of tumors, including colorectal, and this is probably related to a systemic alteration of heme metabolism induced by tumor cells. The aim of our study was to develop an artificial neural network (ANN) classifier for early detection of colorectal adenocarcinoma based on plasma porphyrin accumulation and risk factors. METHODS: We measured the endogenous fluorescence of blood plasma in 100 colorectal adenocarcinoma patients and 112 controls using a conventional spectrofluorometer. Height, weight, personal and family medical history, use of alcohol, red meat, vegetables and tobacco were all recorded. An ANN model was built up from demographic data and from the integral of the fluorescence emission peak in the range 610-650 nm. We used the Receiver Operating Characteristic (ROC) curve to assess performance in distinguishing colorectal adenocarcinoma patients and controls. A liquid chromatography-high resolution mass spectrometry (LC-HRMS) analytical method was employed to identify the agents responsible for native fluorescence. RESULTS: The fluorescence analysis indicated that the integral of the fluorescence emission peak in the range 610-650 nm was significantly higher in colorectal adenocarcinoma patients than controls (p < 0.0001) and was weakly correlated with the TNM staging (Spearman's rho = 0.224, p = 0.011). LC-HRMS measurements showed that the agents responsible for the fluorescence emission were mainly protoporphyrin-IX (PpIX) and coproporphyrin-I (CpI). The overall accuracy of our ANN model was 88% (87% sensitivity and 90% specificity) with an area under the ROC curve of 0.83. CONCLUSIONS: These results confirm that tumor cells accumulate a diagnostic level of endogenous porphyrin compounds and suggest that plasma porphyrin concentrations, indirectly measured through fluorescence analysis, may be useful, together with risk factors, as a clinical decision support tool for the early detection of colorectal adenocarcinoma. Our future efforts will be aimed at examining how plasma porphyrin accumulation correlates with survival and response to therapy.

Colorectal cancer detection by means of optical fluoroscopy. A study on 494 subjects.

In the present work we investigated the possible role of the native fluorescence of blood plasma in the management of colorectal cancer (CRC) and its feasibility as a new tumor marker. Sample of blood was collected from 248 asymptomatic blood donors and from 246 CRC patients. The native fluorescence of blood plasma was measured using a conventional spectrofluorimeter. The intensity of fluorescence of blood plasma at 623 nm (IF623), reasonably ascribed to endogenous porphyrins, was significantly higher in CRC patients than in healthy subjects. The diagnostic capability of IF623 in the discrimination between healthy subjects and CRC patients was tested by Receiving Operating Characteristic (ROC) curve analysis, which resulted in an Area Under the Curve (AUC) of 0.72+/-0.01. Fluorescence measurement of blood plasma might be considered diagnostically useful as a candidate for a new tumor marker for CRC management. The procedure is characterised by a great acceptability and by a very low cost, and might be used in a two-step screening wherein an IF623 positive result is followed by colonoscopy.

In vivo evaluation of melanoma thickness by multispectral imaging and an artificial neural network. A retrospective study on 250 cases of cutaneous melanoma.

AIMS AND BACKGROUND: Noninvasive diagnostic methods such as dermoscopy, sonography, palpation or combined approaches have been developed in an attempt to preoperatively estimate melanoma thickness. However, the clinical presentation is often complex and the evaluation subjective. Multispectral image analysis of melanomas allows selection of features related to the content and distribution of absorbers, mainly melanin and hemoglobin, present within the lesion. Hence, it is reasonable to assume that the same features might be useful to predict melanoma thickness. METHODS: A multispectral image system was used to analyze in vivo 1939 pigmented skin lesions. The lesion selection was based on clinical and/or dermoscopic features that supported a suspicion for melanoma. All the lesions were then subjected to surgery for the histopathological diagnosis, and 250 were melanomas. From the multispectral images of the melanomas, we selected 12 features, seven of which were used to train and test an artificial neural network on 155 and 95 melanomas, respectively. RESULTS: Sensitivity (i.e., melanoma > or = 0.75 mm thick correctly classified) and specificity (i.e., melanoma < 0.75 mm thick correctly classified) evaluated from the receiving operating characteristic curves ranged from 76 to 90% and from 91 to 74%, respectively. CONCLUSIONS: Our approach provides results similar to those obtained with other methods and has the advantage that it is not related to the expertise of the clinician. In addition, the physical interpretation of the selected features suggests a possible role of spectrophotometry as an objective method to study the natural history of the early phases of the disease.

Natural fluorescence spectroscopy of human blood plasma in the diagnosis of colorectal cancer: feasibility study and preliminary results.

AIM AND BACKGROUND: Fluorescence spectroscopy of biomolecules is considered a promising method to discriminate in vivo normal tissue from malignant tissue at various sites including breast, cervix, lung, and colon. However, only few studies have been reported on the feasibility of exploiting fluorescence spectroscopy of blood to characterize pathological changes usable in diagnostic oncology. In this study, the fluorescence characteristics of human blood plasma have been studied in the visible spectral range in an attempt to discriminate patients with colorectal cancer from subjects of a control population. PATIENTS AND METHODS: The study involved 341 subjects, including 169 blood donors with no evidence of disease, 143 patients bearing colorectal adenocarcinomas (36 in the colon, 38 in the sigmoid colon and 69 in the rectum), 11 patients with local relapse, 10 patients with familial adenomatous polyposis and 8 with single adenomas. Blood samples were collected from all subjects and plasma fluorescence spectrum was analyzed using a conventional spectrofluorometer. RESULTS: The intensity of a fluorescence emission peak around 615-635 nm, which could reasonably be ascribed to endogenous porphyrins, was significantly different between patients bearing colorectal cancer and blood donors. The diagnostic capacity of the method was tested by ROC analysis, which resulted in an area under the curve of 0.72, close to that reported for the CEA test. CONCLUSION: These results, although preliminary, suggest the potential of fluorescence measurements of blood plasma as an additional method for diagnostic application in colon cancer.

Automated segmentation of pigmented skin lesions in multispectral imaging.

The aim of this study was to develop an algorithm for the automatic segmentation of multispectral images of pigmented skin lesions. The study involved 1700 patients with 1856 cutaneous pigmented lesions, which were analysed in vivo by a novel spectrophotometric system, before excision. The system is able to acquire a set of 15 different multispectral images at equally spaced wavelengths between 483 and 951 nm. An original segmentation algorithm was developed and applied to the whole set of lesions and was able to automatically contour them all. The obtained lesion boundaries were shown to two expert clinicians, who, independently, rejected 54 of them. The 97.1% contour accuracy indicates that the developed algorithm could be a helpful and effective instrument for the automatic segmentation of skin pigmented lesions.

Automated melanoma detection with a novel multispectral imaging system: results of a prospective study.

The aim of this research was to evaluate the performance of a new spectroscopic system in the diagnosis of melanoma. This study involves a consecutive series of 1278 patients with 1391 cutaneous pigmented lesions including 184 melanomas. In an attempt to approach the 'real world' of lesion population, a further set of 1022 not excised clinically reassuring lesions was also considered for analysis. Each lesion was imaged in vivo by a multispectral imaging system. The system operates at wavelengths between 483 and 950 nm by acquiring 15 images at equally spaced wavelength intervals. From the images, different lesion descriptors were extracted related to the colour distribution and morphology of the lesions. Data reduction techniques were applied before setting up a neural network classifier designed to perform automated diagnosis. The data set was randomly divided into three sets: train (696 lesions, including 90 melanomas) and verify (348 lesions, including 53 melanomas) for the instruction of a proper neural network, and an independent test set (347 lesions, including 41 melanomas). The neural network was able to discriminate between melanomas and non-melanoma lesions with a sensitivity of 80.4% and a specificity of 75.6% in the 1391 histologized cases data set. No major variations were found in classification scores when train, verify and test subsets were separately evaluated. Following receiver operating characteristic (ROC) analysis, the resulting area under the curve was 0.85. No significant differences were found among areas under train, verify and test set curves, supporting the good network ability to generalize for new cases. In addition, specificity and area under ROC curve increased up to 90% and 0.90, respectively, when the additional set of 1022 lesions without histology was added to the test set. Our data show that performance of an automated system is greatly population dependent, suggesting caution in the comparison with results reported in the literature. In our opinion, scientific reports should provide, at least, the median values of thickness and dimension of melanomas, as well as the number of small (6 mm) melanomas.