OBJECTIVE: The purpose of this study was to test the efficacy of static and dynamic cumulative maximum intensity (CMI) subharmonic imaging (SHI) in breast ultrasound studies. METHODS: Contrast-enhanced SHI was performed in 14 women using a modified LOGIQ 9 scanner (GE Healthcare, Milwaukee, WI) transmitting/receiving at 4.4/2.2 MHz. Following mammography, baseline scans of gray scale ultrasound and power Doppler imaging (PDI) were performed. Contrast-enhanced PDI and gray scale SHI were performed after contrast agent administration. Static CMI-SHI is a composite image summarizing blood flow over multiple frames using the maximum intensity projection technique. The dynamic CMI-SHI mode depicts the gradual inflow pattern of the contrast agent in blood vessels. Both CMI-SHI modes were set up using a new automated sum-absolute-difference-based block-matching algorithm to reduce noise and blurring and compensate for motion artifacts. Evaluation of the imaging modes for detecting breast cancer was done by an experienced radiologist, blinded to histopathologic findings. Sensitivity, specificity, and receiver operating characteristic (ROC) analyses were computed and compared for all ultrasound imaging modes and mammography. Results Of the 16 lesions, 4 were malignant. The area under the ROC curve (A(z)) for the diagnosis of breast cancer was 0.64 for gray scale and PDI, 0.67 for contrast-enhanced PDI, 0.76 for mammography, 0.78 for SHI, and 0.75 for static CMI-SHI. For the dynamic CMI-SHI mode, the A(z) increased to 0.90, and this was significantly better than mammography (P = .03). CONCLUSIONS: The new dynamic CMI-SHI mode produced the highest A(z) for the diagnosis of breast cancer compared to conventional techniques and thus appears to improve diagnosis of breast cancer relative to conventional techniques, albeit based on a limited patient population.
OBJECTIVE: The purpose of this study was to test the efficacy of static and dynamic cumulative maximum intensity (CMI) subharmonic imaging (SHI) in breast ultrasound studies. METHODS: Contrast-enhanced SHI was performed in 14 women using a modified LOGIQ 9 scanner (GE Healthcare, Milwaukee, WI) transmitting/receiving at 4.4/2.2 MHz. Following mammography, baseline scans of gray scale ultrasound and power Doppler imaging (PDI) were performed. Contrast-enhanced PDI and gray scale SHI were performed after contrast agent administration. Static CMI-SHI is a composite image summarizing blood flow over multiple frames using the maximum intensity projection technique. The dynamic CMI-SHI mode depicts the gradual inflow pattern of the contrast agent in blood vessels. Both CMI-SHI modes were set up using a new automated sum-absolute-difference-based block-matching algorithm to reduce noise and blurring and compensate for motion artifacts. Evaluation of the imaging modes for detecting breast cancer was done by an experienced radiologist, blinded to histopathologic findings. Sensitivity, specificity, and receiver operating characteristic (ROC) analyses were computed and compared for all ultrasound imaging modes and mammography. Results Of the 16 lesions, 4 were malignant. The area under the ROC curve (A(z)) for the diagnosis of breast cancer was 0.64 for gray scale and PDI, 0.67 for contrast-enhanced PDI, 0.76 for mammography, 0.78 for SHI, and 0.75 for static CMI-SHI. For the dynamic CMI-SHI mode, the A(z) increased to 0.90, and this was significantly better than mammography (P = .03). CONCLUSIONS: The new dynamic CMI-SHI mode produced the highest A(z) for the diagnosis of breast cancer compared to conventional techniques and thus appears to improve diagnosis of breast cancer relative to conventional techniques, albeit based on a limited patient population.
Authors: Anush Sridharan; John R Eisenbrey; Maria Stanczak; Priscilla Machado; Daniel A Merton; Annina Wilkes; Alexander Sevrukov; Haydee Ojeda-Fournier; Robert F Mattrey; Kirk Wallace; Flemming Forsberg Journal: Acad Radiol Date: 2019-12-16 Impact factor: 3.173
Authors: John R Eisenbrey; Jaydev K Dave; Daniel A Merton; Juan P Palazzo; Anne L Hall; Flemming Forsberg Journal: J Ultrasound Med Date: 2011-01 Impact factor: 2.153
Authors: J R Eisenbrey; J K Dave; V G Halldorsdottir; D A Merton; P Machado; J B Liu; C Miller; J M Gonzalez; S Park; S Dianis; C L Chalek; K E Thomenius; D B Brown; V Navarro; F Forsberg Journal: Ultrasonics Date: 2011-05-10 Impact factor: 2.890
Authors: Flemming Forsberg; Maria Stanczak; Andrej Lyshchik; David Loren; Patrick O'Kane; Ali Siddiqui; Thomas E Kowalski; Cynthia Miller; Traci Fox; Ji-Bin Liu; John R Eisenbrey Journal: J Ultrasound Med Date: 2017-07-06 Impact factor: 2.153
Authors: Jaydev K Dave; Valgerdur G Halldorsdottir; John R Eisenbrey; Daniel A Merton; Ji-Bin Liu; Jian-Hua Zhou; Hsin-Kai Wang; Suhyun Park; Scott Dianis; Carl L Chalek; Feng Lin; Kai E Thomenius; Daniel B Brown; Flemming Forsberg Journal: Ultrasound Med Biol Date: 2012-08-21 Impact factor: 2.998