Applications in women’s health

Three papers describe applications that address health concerns specific to women, an often underrepresented group in medical imaging research. These applications include teleoperated hysterectomy (AllardShubertBell https://doi.org/10.1117/1.JMI.5.2.021213), pelvic floor disorder assessment (Bonmatiet al. https://doi.org/10.1117/1.JMI.5.2.021206), and twin-to-twin transfusion syndrome (Tella-Amoet al. https://doi.org/10.1117/1.JMI.5.2.021217).

Integration of machine learning

Four papers reflect recent intensified interest in machine learning (deep learning) and data science in medical imaging, applied here in the context of therapeutic systems. Acknowledging the need for large datasets in deep learning, Zhenget al. https://doi.org/10.1117/1.JMI.5.2.021204 trained a convolutional neural network (CNN) with a combination of synthetic and real images for 2D to 3D registration. Tianet al. https://doi.org/10.1117/1.JMI.5.2.021208 propose a CNN-based prostate segmentation algorithm evaluated with 140 MRI scans. Bonmatiet al. https://doi.org/10.1117/1.JMI.5.2.021206 supplemented training data with multiple images of the same patient for fully automated ultrasound examination. Reflecting the increased interest in radiomics (the extraction of high dimensional information from medical images), Rathoreet al. https://doi.org/10.1117/1.JMI.5.2.021219 used features extracted from multi-parametric MRI to predict recurrence in glioblastoma patients undergoing radiotherapy.

Real-world systems

Several papers detail the use of novel systems with an emphasis on clinical workflow and real-world use of technology. A variety of clinical applications are described, representing the growing need for application-specific solutions. Andresset al. https://doi.org/10.1117/1.JMI.5.2.021209 describe a portable surgical support system capable of augmented reality in any operating room, which aims to minimize the disruptions in surgical workflow inherent in many surgical guidance systems. XiaBreen https://doi.org/10.1117/1.JMI.5.2.021221 propose an automated image registration method to optimally position patients for radiotherapy to improve image quality and registration accuracy. Edgcumbeet al. https://doi.org/10.1117/1.JMI.5.2.021216 provide an end-to-end projector-based system for laparoscopic partial nephrectomy in which the real-time position of the tumor is provided during resection. Zhanget al. https://doi.org/10.1117/1.JMI.5.2.021202 describe a system to calculate the overlap of neural stimulation in cochlear implants including a comparison with previously described work. Linteet al. https://doi.org/10.1117/1.JMI.5.2.021218 modeled and visualized lesions for real-time navigation inside the beating heart for cardiac ablative therapy, with the goal of reducing the re-operation rate for this complex procedure. Fotouhiet al. https://doi.org/10.1117/1.JMI.5.2.021205 propose intraoperative component planning which incorporates two C-arm images for the correct alignment of the implant in hip replacement surgery. Nguyenet al. https://doi.org/10.1117/1.JMI.5.2.021220 explored the overlay of fluorescence imaging on tissue for surgical guidance. The integration of molecular imaging into surgical workflows has the potential to augment surgical displays with cancer detection capabilities.

Lastly, there are two novel studies aimed at augmenting image-guided surgery systems with computational models to correct for misalignment due to deformations of soft tissue. Gerardet al. https://doi.org/10.1117/1.JMI.5.2.021210 propose a novel approach combining intraoperative ultrasound, augmented reality, and patient-specific models for correcting brain deformation in image-guided neurosurgery systems. Heiselmanet al. https://doi.org/10.1117/1.JMI.5.2.021203 provide a detailed study describing liver deformation during minimally invasive laparoscopic surgery followed by a complete realization of a novel approach to image-to-physical registration using patient-specific models and sparse laparoscopic surface data.

Robotic systems and sensing

Novel combinations of robotics and sensors are proposed for a variety of clinical applications. Chenget al. https://doi.org/10.1117/1.JMI.5.2.021223 propose photoacoustic-based catheter tracking where a piezoelectric sensor is placed at the tip of the catheter. The pose of the photoacoustic markers is determined by a stereo-camera. Yiet al. https://doi.org/10.1117/1.JMI.5.2.021212 describe a robotically held drill guide for supplanting traditional surgical navigation. Zhanget al. https://doi.org/10.1117/1.JMI.5.2.021224 discuss a needle insertion platform where a single ultrasound transducer is mounted to the tip of a needle, and sweeping the needle forms images. Lastly, the work by Uffet al. https://doi.org/10.1117/1.JMI.5.2.021211 demonstrate the impact of tumor mobility on axial strain elastograms used within the context of soft tissue discrimination when detecting lesions.

Mock surgery validation and software tools

Novel phantoms were proposed in two papers: Lainget al. https://doi.org/10.1117/1.JMI.5.2.021222 describe a patient-specific cardiac phantom for training and surgical planning, and Jinet al. https://doi.org/10.1117/1.JMI.5.2.021207 propose a dynamic phantom with breathing motion. Brownet al. https://doi.org/10.1117/1.JMI.5.2.021215 provide 3D printing tools for constructing optical tracking targets. In the work by Xiaet al. https://doi.org/10.1117/1.JMI.5.2.021214, robust techniques are demonstrated in ultrasound segmentation for measuring geometry and pathology of mitral valves for the purpose of recapitulating these characteristics in a patient-specific phantom.

The papers in this special section represent a complex scaffolding of technologies, all primarily focused on one goal – to treat disease with human-scale systems. From the perspective of clinical outcomes, this is, of course, a laudable and important goal. However, we also note that these systems provide an incredible opportunity to study other important aspects of disease in humans. In fact, many of these investigations, while addressing a fundamental clinical need, are a first step towards developing instrumentation to facilitate correlative studies between therapy and disease. For example, the Heiselmanet al. https://doi.org/10.1117/1.JMI.5.2.021203 study focuses on understanding the nature of deformation during laparoscopic liver procedures and proposes a method to re-establish precise tumor localization; this tool would greatly facilitate investigations into disease recurrence within the context of locoregional therapies. It is nearly impossible to optimize therapies when one is uncertain of the relationship between the target and all other forms of image-based information.

Scanning the special section topics, we see example after example of investigations focused on the precise relationships among the intraoperative tissue domain, available patient-specific preoperative and intraoperative sensing, and the delivery of a therapy. These investigations represent the power of image guidance to impact the study of human disease and to inform quantitative measurement of outcomes in response to therapeutics.

We thank the following guest associate editors for their dedication and contribution to the special section: