Two New Cytotoxic Candidaspongiolides from An Indonesian Sponge

Marine sponges have been recognized as potentially rich sources of various bioactive molecules. In our continuing search for new secondary metabolites from Indonesian marine invertebrates, we collected a sponge, whose extract showed cytotoxicity against cultured cells at 0.1 μg/mL. Purification of the extract yielded two new macrolides 2 and 3 along with known candida spongiolide (1). The structures for compounds 2 and 3 were elucidated by spectral analysis (1H,13C,COSY,HMQC, HMBC) and by comparison of their NMR data with those of 1. Compounds 2 and 3 exhibited a little more potent cytotoxicity (IC 4.7 and 19 ng/mL) than that (IC5037 ng/mL) of candida spongiolide (1) against NBT-T2 cell

Usefulness of Simple Diffusion Kurtosis Imaging for Head and Neck Tumors: An Early Clinical Study

Diffusion kurtosis (DK) imaging (DKI), a type of restricted diffusion-weighted imaging, has been reported to be useful for tumor diagnoses in clinical studies. We developed a software program to simultaneously create DK images with apparent diffusion coefficient (ADC) maps and conducted an initial clinical study. Multi-shot echo-planar diffusion-weighted images were obtained at b-values of 0, 400, and 800 sec/mm2 for simple DKI, and DK images were created simultaneously with the ADC map. The usefulness of the DK image and ADC map was evaluated using a pixel analysis of all pixels and a median analysis of the pixels of each case. Tumor and normal tissues differed significantly in both pixel and median analyses. In the pixel analysis, the area under the curve was 0.64 for the mean kurtosis (MK) value and 0.77 for the ADC value. In the median analysis, the MK value was 0.74, and the ADC value was 0.75. The MK and ADC values correlated moderately in the pixel analysis and strongly in the median analysis. Our simple DKI system created DK images simultaneously with ADC maps, and the obtained MK and ADC values were useful for differentiating head and neck tumors from normal tissue

Characteristic Mean Kurtosis Values in Simple Diffusion Kurtosis Imaging of Dentigerous Cysts

We evaluated the usefulness of simple diffusion kurtosis (SD) imaging, which was developed to generate diffusion kurtosis images simultaneously with an apparent diffusion coefficient (ADC) map for 27 cystic disease lesions in the head and neck region. The mean kurtosis (MK) and ADC values were calculated for the cystic space. The MK values were dentigerous cyst (DC): 0.74, odontogenic keratocyst (OKC): 0.86, ranula (R): 0.13, and mucous cyst (M): 0, and the ADC values were DC: 1364 × 10−6 mm2/s, OKC: 925 × 10−6 mm2/s, R: 2718 × 10−6 mm2/s, and M: 2686 × 10−6 mm2/s. The MK values of DC and OKC were significantly higher than those of R and M, whereas their ADC values were significantly lower. One reason for the characteristic signal values in diffusion-weighted images of DC may be related to content components such as fibrous tissue and exudate cells. When imaging cystic disease in the head and neck region using SD imaging, the maximum b-value setting at the time of imaging should be limited to approximately 1200 s/mm2 for accurate MK value calculation. This study is the first to show that the MK values of DC are characteristically higher than those of other cysts

Enhancing Diagnostic Precision: Evaluation of Preprocessing Filters in Simple Diffusion Kurtosis Imaging for Head and Neck Tumors

Background: Our initial clinical study using simple diffusion kurtosis imaging (SDI), which simultaneously produces a diffusion kurtosis image (DKI) and an apparent diffusion coefficient map, confirmed the usefulness of SDI for tumor diagnosis. However, the obtained DKI had noticeable variability in the mean kurtosis (MK) values, which is inherent to SDI. We aimed to improve this variability in SDI by preprocessing with three different filters (Gaussian [G], median [M], and nonlocal mean) of the diffusion-weighted images used for SDI. Methods: The usefulness of filter parameters for diagnosis was examined in basic and clinical studies involving 13 patients with head and neck tumors. Results: The filter parameters, which did not change the median MK value, but reduced the variability and significantly homogenized the MK values in tumor and normal tissues in both basic and clinical studies, were identified. In the receiver operating characteristic curve analysis for distinguishing tumors from normal tissues using MK values, the area under curve values significantly improved from 0.627 without filters to 0.641 with G (sigma = 0.5) and 0.638 with M (radius = 0.5). Conclusions: Thus, image pretreatment with G and M for SDI was shown to be useful for improving tumor diagnosis in clinical practice