Masaki Hata

Three-Dimensional High-Frequency Backscatter and Envelope Quantification of Cancerous Human Lymph Nodes

Quantitative imaging methods using high-frequency ultrasound (HFU) offer a means of characterizing biological tissue at the microscopic level. Previously, high-frequency, 3-D quantitative ultrasound (QUS) methods were developed to characterize 46 freshly-dissected lymph nodes of colorectal-cancer patients. 3-D ultrasound radiofrequency data were acquired using a 25.6 MHz center-frequency transducer and each node was inked before tissue fixation to recover orientation after sectioning for 3-D histological evaluation. Backscattered echo signals were processed using 3-D cylindrical regions-of-interest (ROIs) to yield four QUS estimates associated with tissue microstructure (i.e., effective scatterer size, acoustic concentration, intercept and slope). These QUS estimates, obtained by parameterizing the backscatter spectrum, showed great potential for cancer detection. In the present study, these QUS methods were applied to 112 lymph nodes from 77 colorectal and gastric cancer patients. Novel QUS methods parameterizing the envelope statistics of the ROIs using Nakagami and homodyned-K distributions were also developed; they yielded four additional QUS estimates. The ability of these eight QUS estimates to classify lymph nodes and detect cancer was evaluated using receiver operating characteristics (ROC) curves. An area under the ROC curve of 0.996 with specificity and sensitivity of 95% were obtained by combining effective scatterer size and one envelope parameter based on the homodyned-K distribution. Therefore, these advanced 3-D QUS methods potentially can be valuable for detecting small metastatic foci in dissected lymph nodes.

Three-dimensional High-frequency Characterization of Cancerous Lymph Nodes

High-frequency ultrasound (HFU) offers a means of investigating biologic tissue at the microscopic level. High-frequency, three-dimensional (3-D) quantitative-ultrasound (QUS) methods were developed to characterize freshly-dissected lymph nodes of cancer patients. Three-dimensional ultrasound data were acquired from lymph nodes using a 25.6-MHz center-frequency transducer. Each node was inked prior to tissue fixation to recover orientation after sectioning for 3-D histologic evaluation. Backscattered echo signals were processed using 3-D cylindrical regions-of-interest to yield four QUS estimates associated with tissue microstructure (i.e., effective scatterer size, acoustic concentration, intercept and slope). QUS estimates were computed following established methods using two scattering models. In this study, 46 lymph nodes acquired from 27 patients diagnosed with colon cancer were processed. Results revealed that fully-metastatic nodes could be perfectly differentiated from cancer-free nodes using slope or scatterer-size estimates. Specifically, results indicated that metastatic nodes had an average effective scatterer size (i.e., 37.1 +/- 1.7 microm) significantly larger (p < 0.05) than that in cancer-free nodes (i.e., 26 +/- 3.3 microm). Therefore, the 3-D QUS methods could provide a useful means of identifying small metastatic foci in dissected lymph nodes that might not be detectable using current standard pathology procedures.

Three-dimensional segmentation of high-frequency ultrasound echo signals from dissected lymph nodes

Quantitative high-frequency ultrasound (QHFU) imaging methods are under investigation to evaluate their ability to detect small nodal metastases in lymph nodes freshly dissected from cancer patients. To apply these methods, a critical preprocessing step is 3D segmentation of the lymph-node ultrasound echo-signal dataset. Segmenting the residual fat layer and the lymph node is critical in order to avoid bias in the QHFU estimates (e.g., scatterer size and acoustic concentration) due to attenuation and to exclude estimates obtained from the fat regions. Segmentation also provides absolute measurements of lymph-node dimensions that are necessary to match 3D ultrasound with 3D histology. In this study, a 3D region-based segmentation algorithm was developed and compared quantitatively using Dices mutual-overlap criterion with 2D manual segmentation of 9 representative cross sections. The method was tested on 13 lymph nodes, and resulting Dice scores had mean values of 0.81 and 0.78 for lymph node and fat segmentation, respectively.

Three-dimensional quantitative ultrasound for detecting lymph node metastases

PURPOSE Detection of metastases in lymph nodes (LNs) is critical for cancer management. Conventional histological methods may miss metastatic foci. To date, no practical means of evaluating the entire LN volume exists. The aim of this study was to develop fast, reliable, operator-independent, high-frequency, quantitative ultrasound (QUS) methods for evaluating LNs over their entire volume to effectively detect LN metastases. METHODS We scanned freshly excised LNs at 26 MHz and digitally acquired echo-signal data over the entire three-dimensional (3D) volume. A total of 146 LNs of colorectal, 26 LNs of gastric, and 118 LNs of breast cancer patients were enrolled. We step-sectioned LNs at 50-μm intervals and later compared them with 13 QUS estimates associated with tissue microstructure. Linear-discriminant analysis classified LNs as metastatic or nonmetastatic, and we computed areas (Az) under receiver-operator characteristic curves to assess classification performance. The QUS estimates and cancer probability values derived from discriminant analysis were depicted in 3D images for comparison with 3D histology. RESULTS Of 146 LNs of colorectal cancer patients, 23 were metastatic; Az = 0.952 ± 0.021 (95% confidence interval [CI]: 0.911-0.993); sensitivity = 91.3% (specificity = 87.0%); and sensitivity = 100% (specificity = 67.5%). Of 26 LNs of gastric cancer patients, five were metastatic; Az = 0.962 ± 0.039 (95% CI: 0.807-1.000); sensitivity = 100% (specificity = 95.3%). A total of 17 of 118 LNs of breast cancer patients were metastatic; Az = 0.833 ± 0.047 (95% CI: 0.741-0.926); sensitivity = 88.2% (specificity = 62.5%); sensitivity = 100% (specificity = 50.5%). 3D cancer probability images showed good correlation with 3D histology. CONCLUSIONS These results suggest that operator- and system-independent QUS methods allow reliable entire-volume LN evaluation for detecting metastases. 3D cancer probability images can help pathologists identify metastatic foci that could be missed using conventional methods.

Entire-volume Serial Histological Examination for Detection of Micrometastases in Lymph Nodes of Colorectal Cancers

The purpose of this study was to accurately detect lymph-node micrometastases, i.e., metastatic cancer foci that have a size between 2.0 and 0.2 mm, in nodes excised from colorectal cancer (CRC) patients, and to determine how frequently micrometastases might be missed when standard histological examination procedures are used. A total of 311 lymph nodes were removed and examined from 90 patients with Stage I to IV CRC. The number of slices of histology sections ranged from 6 to 75 per node (average = 25.5; SD = 11.1), which provided a total of 7,943 slices. Lymph nodes were examined in their entire volume at every 50-μm and 100-μm intervals for nodes smaller and larger than 5 mm respectively. The total number of thin sections examined in each node and the number of thin sections where metastatic foci were present were counted. The number of thin sections with metastatic foci and the total number of slices was determined for each node. In addition, the presence or absence of metastatic foci in the “central” slice was determined. Micrometastases were found in 12/311 (3.9%) of all lymph nodes. In the 12 lymph nodes with micrometastases, the rate of metastatic slices over all slices was 39.4% (range = 6.3 to 81.3%; SD = 25.8%) In the central slice of each node, micrometastases were present only in 6 of 12 lymph nodes (50%); accordingly, they were not present in the central slice for half the micrometastatic nodes. These 6 nodes represented 1.9% of the 311 nodes and 11.1% of the 54 metastatic nodes. This study suggests that a significant fraction of micrometastases can be missed by traditional singleslice sectioning; half of the micrometastases would have been overlooked in our data set of 311 nodes.

High-Frequency Quantitative Ultrasound Imaging of Cancerous Lymph Nodes

High-frequency ultrasound (HFU) offers a means of investigating biological tissue at the microscopic level. High-frequency, quantitative-ultrasound (QUS) methods were developed to characterize freshly-dissected lymph nodes of cancer patients. Three-dimensional (3D) ultrasound data were acquired from lymph nodes using a 25.6-MHz center-frequency transducer. Each node was inked prior to 3D histological fixation to recover orientation after sectioning. Backscattered echo signals were processed to yield two QUS estimates associated with tissue microstructure: scatterer size and acoustic concentration. The QUS estimates were computed following established methods using a Gaussian scattering model. Four lymph nodes from a patient with stage-3 colon cancer were evaluated as an illustrative case. QUS images were generated for this patient by expressing QUS estimates as color-encoded pixels and overlaying them on conventional gray-scale B-mode images. The single metastatic node had an average scatterer size that was significantly larger than the average scatterer size of the other nodes, and the statistics of both QUS estimates in the metastatic node showed greater variance than the statistics of the other nodes. Results indicate that the methods may provide a useful means of identifying small metastatic foci in dissected lymph nodes that might not be detectable using current standard pathology procedures.

Three-dimensional high-frequency characterization of excised human lymph nodes

High-frequency ultrasound (HFU, ≫20 MHz) offers a means of investigating biological tissue at the microscopic level because the short wavelengths and small focal-zone beam diameters of HFU transducers provide fine-resolution images (≪100 µm). In this study, three-dimensional (3D) quantitative-ultrasound (QUS) methods were developed and evaluated to detect metastases in freshly-dissected lymph nodes of cancer patients. Detection of metastases is critically important for staging and treatment planning. 3D radio-frequency (RF) data were acquired from scanning dissected lymph nodes using a 26-MHz single-element transducer. For each lymph node, overlapping cylindrical regions-of-interest (ROIs, 1-mm diameter, 1-mm deep) were processed to yield four QUS estimates. Spectral intercept (I) and spectral slope (S) were computed using a straight-line model and effective scatterer size (D) and acoustic concentration (CQ2) were estimated using a Gaussian scattering model. 3D QUS images were generated by expressing QUS estimates as color-encoded pixels and overlaying them on conventional 3D B-mode images. QUS estimates were obtained for 82 lymph nodes (65 devoid of metastases and 17 entirely filled by metastases) from 46 patients diagnosed with colon or gastric cancer and a statistical difference (p ≪0.05) was found for each QUS estimate for metastatic and non-metastatic nodes. Furthermore, areas under the ROC were greater than 0.99 for D or S alone. These initial results suggest that these methods may provide a clinically important means of identifying small metastatic foci that might not be detected using standard pathology procedures.

Assembling 3D histology volumes from sections of cancerous lymph nodes to match 3D high-frequency quantitative ultrasound images

High-Frequency Quantitative Ultrasound (HFQUS) imaging methods are under investigation to evaluate their ability to detect small metastases (< 2 mm) in lymph nodes freshly dissected from cancer patients. To assess the performance of these methods, 3D HFQUS must be compared to gold-standard histologic images. Histologic images have to be assembled to form volumetric histologic information. This study addresses this issue. The acquisition of high-frequency ultrasound (HFU) data with a 26-MHz center-frequency transducer and histologic preparation are described. Dissected nodes were longitudinally cut in half and pairs of histologic sections separated by 65 µm, for nodes < 5 mm, or 115 µm, for nodes > 5 mm, were photographed. Then a fully automatic method to assemble and orient a 3D histologic volume from a set of 2D images was developed and applied. Identification of the histology sections on each slide relies on a parametric shape modeling of the histologic sections with ellipses. Then a set of rigid transformations were estimated and applied to construct volumetric histologic data. The method was visually evaluated on a set of 50 lymph nodes and is valuable for comparing histologic data to HFQUS estimates in 3D.

Three-dimensional quantitative high-frequency characterization of freshly-excised human lymph nodes

High-frequency quantitative ultrasound (QUS) permits characterization of tissue microstructure using system-independent estimates. In this study, freshly-excised lymph nodes from cancer patients were evaluated using specifically designed three-dimensional (3D) QUS methods. The long-term objective was to develop 3D QUS methods for detecting metastases. Detection of metastases is critically important for cancer staging and treatment planning. A custom laboratory scanning system was used to acquire radio-frequency (RF) data in 3D from excised lymph nodes using a 26-MHz center-frequency transducer. Overlapping 1-mm cylindrical regions-of-interest (ROIs) of the RF data were processed to yield 13 QUS estimates associated with tissue microstructure. QUS estimates were obtained from more than 250 nodes from more than 150 colorectal-, gastric-, and breast-cancer patients. Cancer-detection performance was assessed for individual estimates and linear combinations of estimates. ROC results demonstrated excellent classification. For colorectal- and gastric-cancer nodes, the areas under the ROC curves (AUCs) were above 0.94. Slightly poorer results (AUC 0.87) were obtained for breast nodes. Images based on QUS parameters also permitted localization of cancer foci in some micrometastatic cases. Therefore, these advanced 3D QUS methods potentially can be valuable for detecting small metastatic foci in dissected lymph nodes.

Three-dimensional quantitative ultrasound to guide pathologists towards metastatic foci in lymph nodes

The detection of metastases in freshly-excised lymph nodes from cancer patients during lymphadenectomy is critically important for cancer staging, treatment, and optimal patient management. Currently, conventional histologic methods suffer a high rate of false-negative determinations because pathologists cannot evaluate each excised lymph nodes in its entirety. Therefore, lymph nodes are undersampled and and small but clinically relevant metastatic regions can be missed. In this study, quantitative ultrasound (QUS) methods using high-frequency transducers (i.e., >; 20 MHz) were developed and evaluated for their ability to detect and guide pathologists towards suspicious regions in lymph nodes. A custom laboratory scanning system was used to acquire radio-frequency (RF) data in 3D from excised lymph nodes using a 26-MHz center-frequency transducer. Overlapping 1-mm cylindrical regions-of-interest (ROIs) of the RF data were processed to yield 13 QUS estimates quantifying tissue microstructure and organization. These QUS methods were applied to more than 260 nodes from more than 160 colorectal-, gastric-, and breast-cancer patients. Cancer-detection performance was assessed for individual estimates and linear combinations of estimates. ROC results demonstrated excellent classification. For colorectal- and gastric-cancer nodes, the areas under the ROC curves (AUCs) were greater than 0.95. Slightly poorer results (AUC=0.85) were obtained for breast-cancer nodes. Images based on QUS parameters also permitted localization of cancer foci in some micrometastatic cases.