Lydia Liao

In vivo motion and force measurement of surgical needle intervention during prostate brachytherapy

In this paper, we present needle insertion forces and motion trajectories measured during actual brachytherapy needle insertion while implanting radioactive seeds in the prostate glands of 20 different patients. The needle motion was captured using ultrasound images and a 6 degree-of-freedom electromagnetic-based position sensor. Needle velocity was computed from the position information and the corresponding time stamps. From in vivo data we found the maximum needle insertion forces to be about 15.6 and 8.9N for 17gauge (1.47mm) and 18gauge (1.27mm) needles, respectively. Part of this difference in insertion forces is due to the needle size difference (17G and 18G) and the other part is due to the difference in tissue properties that are specific to the individual patient. Some transverse forces were observed, which are attributed to several factors such as tissue heterogeneity, organ movement, human factors in surgery, and the interaction between the template and the needle. However, theses insertion forces are significantly responsible for needle deviation from the desired trajectory and target movement. Therefore, a proper selection of needle and modulated velocity (translational and rotational) may reduce the tissue deformation and target movement by reducing insertion forces and thereby improve the seed delivery accuracy. The knowledge gleaned from this study promises to be useful for not only designing mechanical/robotic systems but also developing a predictive deformation model of the prostate and real-time adaptive controlling of the needle.

A real-time prostate cancer detection technique using needle insertion force and patient-specific criteria during percutaneous intervention

In this article, the authors present a novel real-time cancer detection technique by using needle insertion forces in conjunction with patient-specific criteria during percutaneous interventions. Needle insertion experiments and pathological analysis were performed for developing a computer-aided detection (CAD) model. Backward stepwise regression method was performed to identify the statistically significant patient-specific factors. A baseline force model was then developed using these significant factors. The threshold force model that estimated the lower bound of the cancerous tissue forces was formulated by adding an adjustable classifier to the baseline force model. Tradeoff between sensitivity and specificity was obtained by varying the threshold value of the classifier, from which the receiver-operating characteristic (ROC) curve was generated. Sequential quadratic programming was used to optimize the CAD model by maximizing the area under the ROC curve (AUC) using a set of model-training patient data. When the CAD model was evaluated using an independent set of model-validation patient data, an AUC of 0.90 was achieved. The feasibility of cancer detection in real time during percutaneous interventions was established.

Contrast-enhanced spectral mammography (CESM) versus breast magnetic resonance imaging (MRI): A retrospective comparison in 66 breast lesions

OBJECTIVE The purpose of this study was to retrospectively compare the diagnostic performance of contrast-enhanced spectral mammography (CESM) with that of breast magnetic resonance imaging (BMRI) in breast cancer detection using parameters, including sensitivity, positive predictive value (PPV), lesion size, morphology, lesion and background enhancement, and examination time. MATERIALS AND METHODS A total of 48 women (mean age, 56years±10.6 [SD]) with breast lesions detected between October 2012 and March 2014 were included. Both CESM and BMRI were performed for each patient within 30 days. The enhancement intensity of lesions and breast background parenchyma was subjectively assessed for both modalities and was quantified for comparison. Statistical significance was analyzed using paired t-test for mean size of index lesions in all malignant breasts (an index lesion defined as the largest lesion in each breast), and a mean score of enhancement intensity for index lesions and breast background. PPV, sensitivity, and accuracy were calculated for both CESM and BMRI. The average duration time of CESM and MRI examinations was also compared. RESULTS A total of 66 lesions were identified, including 62 malignant and 4 benign lesions. Both CESM and BMRI demonstrated a sensitivity of 100% for detection of breast cancer. There was no statistically significant difference between the mean size of index lesions (P=0.108). The enhancement intensity of breast background was significantly lower for CESM than for BMRI (P<0.01). The mean score of enhancement intensity of index lesions on CESM was significantly less than that for BMRI (P<0.01). The smallest lesion that was detected by both modalities measured 4mm. CESM had a higher PPV than BMRI (P>0.05). The average examination time for CESM was significantly shorter than that of BMRI (P<0.01). CONCLUSION CESM has similar sensitivity than BMRI in breast cancer detection, with higher PPV and less background enhancement. CESM is associate with significantly shorter exam time thus a more accessible alternative to BMRI, and has the potential to play an important tool in breast cancer detection and staging.

Contrast-enhanced Spectral Mammography

RATIONALE AND OBJECTIVES Contrast-enhanced spectral mammography (CESM) combines the benefits of full field digital mammography with the concept of tumor angiogenesis. Technique and practical applications of CESM are discussed. MATERIALS AND METHODS An overview of the technique is followed by a demonstration of practical applications of CESM in our practice. RESULTS We have successfully implemented CESM into our practice as a screening, diagnostic, staging, and treatment response tool. CONCLUSION It is important to understand the technique of CESM and how to incorporate it into practice.

Amyloidosis of the Breast with Multicentric DCIS and Pleomorphic Invasive Lobular Carcinoma in a Patient with Underlying Extranodal Castleman's Disease

We present an interesting case of focal amyloidosis of the left breast which was intermixed with ductal carcinoma in situ (DCIS). On subsequent staging bilateral breast magnetic resonance imaging (MRI), the patient was found to have an additional suspicious enhancing mass with spiculated borders within the left breast. This mass was biopsy proven to represent pleomorphic invasive lobular carcinoma. A pulmonary nodule within the lingula was also noted on the staging bilateral breast MRI and was biopsy proven to represent extranodal Castlemans disease. Therefore, it is believed that our patient had secondary amyloidosis due to Castlemans disease.

Case Report: Ductal Carcinoma In Situ in the Male Breast

High-grade ductal carcinoma in situ is incredibly rare in male patients. The prognosis for ductal carcinoma in situ (DCIS) in a male patient is the same as it would be for a female with the same stage disease; therefore, early recognition and diagnosis are of the utmost importance. We present a case of a male with unilateral invasive ductal carcinoma who was diagnosed with DCIS in the contralateral breast. The DCIS presented as microcalcifications on mammography and was found to be biopsy proven grade 3 papillary DCIS. This case also illustrates the importance of family history and risk factors, all of which need to be evaluated in any male presenting with a breast mass or nipple discharge.

Clinical study of a noninvasive multimodal sono-contrast induced spectroscopy system for breast cancer diagnosis.

PURPOSE To present a noninvasive multimodal sono-contrast induced spectroscopy (SCIS) system for breast cancer detection. METHODS An IRB approved clinical study was carried out to evaluate its diagnostic power. A total of 66 subjects were enrolled with informed consent. The study data were grouped into healthy breast tissue (26), histologically proven cancer (14), and benign mass (26). The diffuse reflectance optical intensity and low intensity focused ultrasound (LIFU) signals, as well as ultrasound images, were collected during each study. The ratio of optical intensities at wavelengths 685 and 830 nm was analyzed using wavelet technique to compare the LIFU effects in cancer and noncancerous tissues. The ultrasound images were also processed to obtain tissue texture parameters, such as correlation, energy, contrast, homogeneity, etc. Backward stepwise regression method was performed to identify the statistically significant factors correlating to tissue types (cancer vs benign mass). RESULTS Comparison of the optical signals showed that LIFU induced transitory fluctuation in noncancerous tissue, but not in malignant tissue, as quantified by the ratio of mean absolute deviation (RMAD) of the high frequency component. Statistical analysis revealed that the RMAD ratios were significantly different in tumor vs noncancerous masses (p ≪ 0.01). For tissue texture parameters, energy and correlation were found to statistically correlate with the tissue types. A cancer characterization model was developed using the weighted factors to differentiate the tumor from the benign mass. Trade-off between sensitivity and specificity was obtained by varying the threshold value that estimated the upper-bound of the cancer output factor, from which the receiver-operating characteristic (ROC) curve was generated. The characterization model was optimized using ten modeling datasets and verified using another ten validation datasets randomly generated from the database. The optimization results show that an AUC of 0.93 can be achieved. With threshold 0.3, sensitivity of 96.0%, specificity of 84.1%, and negative predictive value (NPV) of 97.3% can be achieved. CONCLUSIONS The feasibility of the multimodal system in characterizing breast cancer vs benign mass is established.

A multimodal sono-contrast NIR spectroscopy system for breast cancer Diagnosis: System design and safety considerations

This paper presents a novel multimodal imaging system, which combines optical spectroscopy, ultrasonography and acoustic radiation force (ARF) for improving diagnosis of breast cancer based on noninvasive interrogation of vasculature. System design including both hardware and software is described in detail. Patient safety related considerations are also addressed in this paper. Calibrations and tests have been performed accordingly. Based on safety guidelines, the maximum exposure to skin for laser was controlled within 0.2 W·cm−2; exposure from ARF fields were maintained below the FDA diagnostic limit (0.72 W·cm−2), and electrical leakage was controlled below 300 µA. This multimodal system has the potential to improve tumor detection by deploying ARF to produce a measurable difference in the dynamic behavior of the tissue blood supply environment as interrogated by optical spectroscopy, which was demonstrated to be highly diagnostic in a murine tumor model. Pilot clinical study is being carried out.

Sono-contrast spectroscopy for breast cancer detection

In a preclinical study, we demonstrated that blood flow and tissue oxygenation could be manipulated by focused ultrasound; the effects of such manipulation were interrogated via optical spectroscopy at wavelengths where oxy- and deoxy-hemoglobin display different extinction properties. We have designed a clinical breast scanner based on these noninvasive techniques. In addition to the focused ultrasound field intersecting with the volume of optical illumination and points of spectral collection, a diagnostic quality breast imaging probe is incorporated into the scanhead to achieve image guidance. Experimental confirmation of the system performance of the focused ultrasound field properties, diagnostic imaging capabilities and NIR spectroscopy subsystem has been carried out to demonstrate readiness for a clinical study involving 200 patients who are scheduled to undergo ultrasound-guided biopsy to rule out breast cancers.

Tactile sensation imaging for artificial palpation

In this paper we investigated a novel tactile sensation imaging method using a flexible, transparent waveguide and the total internal reflection principle. The developed sensor is used to detect and identify inclusions within tissues. To test the performance of the proposed sensor, a realistic tissue phantom with hard inclusions (tumor models) is developed. The proposed tactile imaging sensor estimated the inclusion diameter within 4.09% and the inclusion depth within 7.55%.