Modification of a melanoma discrimination index derived from hyperspectral data: a clinical trial conducted in 2 centers between March 2011 and December 2013

Nagaoka, Takashi; Kiyohara, Yoshio; Koga, Hiroshi; Nakamura, Atsushi; Saida, Toshiaki; Sota, Takayuki

doi:10.1111/srt.12188

Cited by 18 publications

(32 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A number of optical imaging and spectroscopic technologies have been developed for noninvasive detection of skin cancers . These include RCM, optical coherence tomography (OCT), diffuse reflectance spectroscopy including multi‐ and hyper‐spectral approaches, two‐photon microscopy, Raman spectroscopy, and multimodal spectroscopy . Of these, RCM imaging is currently the furthest along in clinical settings, with level I and level II evidence supporting its role in enabling dermatologists to discriminate benign from malignant lesions with high sensitivity and specificity.…”

Section: Introductionmentioning

confidence: 99%

“…Another multispectral approach, called spectro‐photometric intracutaneous analysis (SIAscopy or MoleMate), performs with sensitivity of 84–98% and specificity of 84–46% for melanocytic and non‐melanocytic lesions . Other developments include multi‐ and hyper‐spectroscopy, reporting range of sensitivities from 69% to 97% and specificities from 72% to 87% . Multimodal spectral approaches, combining reflectance, fluorescence, and Raman, can classify melanocytic and non‐melanocytic lesions with sensitivity 90–100% and specificity 71% to 100% .…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reflectance confocal microscopy of skin in vivo: From bench to bedside

et al. 2016

View full text Add to dashboard Cite

Following more than two decades of effort, reflectance confocal microscopy (RCM) imaging of skin was granted codes for reimbursement by the US Centers for Medicare and Medicaid Services. Dermatologists in the USA have started billing and receiving reimbursement for the imaging procedure and for the reading and interpretation of images. RCM imaging combined with dermoscopic examination is guiding the triage of lesions into those that appear benign, which are being spared from biopsy, against those that appear suspicious, which are then biopsied. Thus far, a few thousand patients have been spared from biopsy of benign lesions. The journey of RCM imaging from bench to bedside is certainly a success story, but still much more work lies ahead toward wider dissemination, acceptance, and adoption. We present a brief review of RCM imaging and highlight key challenges and opportunities. The success of RCM imaging paves the way for other emerging optical technologies, as well—and our bet for the future is on multimodal approaches.

show abstract

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Reflectance confocal microscopy of skin in vivo: From bench to bedside

et al. 2016

View full text Add to dashboard Cite

show abstract

“…We are in the process of developing an automated melanoma diagnosis system [16][17][18]. In previous studies, the entropy of the spectral angle [19] was calculated from HSD and used as a melanoma diagnostic index.…”

Section: Introductionmentioning

confidence: 99%

Performance Improvement of Automated Melanoma Diagnosis System by Data Augmentation

Kato

Nemoto

Kimura

et al. 2020

ABE

View full text Add to dashboard Cite

Color information is an important tool for diagnosing melanoma. In this study, we used a hyperspectral imager (HSI), which can measure color information in detail, to develop an automated melanoma diagnosis system. In recent years, the effectiveness of deep learning has become more widely accepted in the eld of image recognition. We therefore integrated the deep convolutional neural network with transfer learning into our system. We tried data augmentation to demonstrate how our system improves diagnostic performance. 283 melanoma lesions and 336 non-melanoma lesions were used for the analysis. The data measured by HSI, called the hyperspectral data (HSD), were converted to a single-wavelength image averaged over plus or minus 3 nm. We used GoogLeNet which was pre-trained by ImageNet and then was transferred to analyze the HSD. In the transfer learning, we used not only the original HSD but also arti cial augmentation dataset to improve the melanoma classi cation performance of GoogLeNet. Since GoogLeNet requires three-channel images as input, three wavelengths were selected from those single-wavelength images and assigned to three channels in wavelength order from short to long. The sensitivity and speci city of our system were estimated by 5-fold cross-validation. The results of a combination of 530, 560, and 590 nm (combination A) and 500, 620, and 740 nm (combination B) were compared. We also compared the diagnostic performance with and without the data augmentation. All images were augmented by inverting the image vertically and/or horizontally. Without data augmentation, the respective sensitivity and speci city of our system were 77.4% and 75.6% for combination A and 73.1% and 80.6% for combination B. With data augmentation, these numbers improved to 79.9% and 82.4% for combination A and 76.7% and 82.2% for combination B. From these results, we conclude that the diagnostic performance of our system has been improved by data augmentation. Furthermore, our system succeeds to differentiate melanoma with a sensitivity of almost 80%.

show abstract

“…Malignant melanoma (MM) is a type of highly malignant tumor that primarily develops in adults over the age of 30 years, and is associated with a high rate of mortality (1). The morbidity rate of MM, which has gradually increased over recent years, particularly in younger generations, accounts for ~2% of all malignant tumors, and ranks third among skin malignancies (6-20% of skin malignancies) (2). MM can occur on any region of the skin, with skin regions exposed to the highest levels of friction at the extremities being the most vulnerable, and is characterized by early metastasis, aggressive invasion and poor prognosis (3).…”

Section: Introductionmentioning

confidence: 99%

Clinical significance of miR-138 in patients with malignant melanoma through targeting of PDK1 in the PI3K/AKT autophagy signaling pathway

Meng

Zhang²,

et al. 2017

Oncology Reports

View full text Add to dashboard Cite

The present study investigated the clinical significance of miR-138 in patients with malignant melanoma (MM), which has previously been associated with tumor growth. In patients with MM, we found that the expression of miR-138 was significantly downregulated when compared with healthy control subjects. Overexpression of miR-138 in the human melanoma cell line A2058 inhibited cell proliferation and induced cell apoptosis, and increased caspase-3 and Bax protein expression when compared with a negative control group. Meanwhile, miR-138 overexpression promoted cell autophagy, induced LC3 protein expression, and suppressed the PI3K/AKT/mTOR signaling pathway and PDK1 protein expression in A2058 cells. LY294002, an inhibitor of PI3K, suppressed PI3K/AKT/mTOR signaling, induced apoptosis, inhibited cell proliferation, increased caspase-3 and Bax protein expression, and decreased PDK1 protein expression in A2058 cells following miR-138 overexpression. Collectively, our findings indicate the clinical significance of miR-138 in patients with MM through its targeting of PDK1 expression in the PI3K/AKT/mTOR autophagy signaling pathway.

show abstract

Modification of a melanoma discrimination index derived from hyperspectral data: a clinical trial conducted in 2 centers between March 2011 and December 2013

Abstract: The new index had a higher sensitivity and adequate specificity, indicating that it is more useful than the old index.

Cited by 18 publications

References 12 publications

Reflectance confocal microscopy of skin in vivo: From bench to bedside

Reflectance confocal microscopy of skin in vivo: From bench to bedside

Performance Improvement of Automated Melanoma Diagnosis System by Data Augmentation

Clinical significance of miR-138 in patients with malignant melanoma through targeting of PDK1 in the PI3K/AKT autophagy signaling pathway

Contact Info

Product

Resources

About