Roaring Orchards

The seeds of Roaring Orchards were planted during a spring drive to Williams College. In one of the outdoor malls spread along the roads that lead east from the northbound curl of the Taconic Parkway, there is on Sundays a small farmers\u27 market. I stopped to get a carton of blueberries from the produce tent, and wandered to a table stacked with used books for sale. Most were illustrated biographies of baseball players and how-to books, but there were also a few dusty yellow paperbacks. I bought The Palm at the End of the Mind, Nostromo, and The Portable Chekov. It wasn\u27t until I got back to my car that, flipping through the pages of Chekov, I found teeth marks on the margins of the pages. I enjoyed for a moment imagining that these weren\u27t the work of a child but the result of a more visceral frustration with Chekov\u27s understated depiction of grief. That those teeth marks betokened an exasperation, a silent scream that inscribed what Chekov so often left unsaid. Roaring Orchards grew out of an attempt to articulate that impulse

Motion artifacts occurring at the lung/diaphragm interface using 4D CT attenuation correction of 4D PET scans

For PET/CT, fast CT acquisition time can lead to errors in attenuation correction, particularly at the lung/diaphragm interface. Gated 4D PET can reduce motion artifacts, though residual artifacts may persist depending on the CT dataset used for attenuation correction. We performed phantom studies to evaluate 4D PET images of targets near a density interface using three different methods for attenuation correction: a single 3D CT (3D CTAC), an averaged 4D CT (CINE CTAC), and a fully phase matched 4D CT (4D CTAC). A phantom was designed with two density regions corresponding to diaphragm and lung. An 8 mL sphere phantom loaded with 18F‐FDG was used to represent a lung tumor and background FDG included at an 8:1 ratio. Motion patterns of sin(x) and sin4(x) were used for dynamic studies. Image data was acquired using a GE Discovery DVCT‐PET/CT scanner. Attenuation correction methods were compared based on normalized recovery coefficient (NRC), as well as a novel quantity “fixed activity volume” (FAV) introduced in our report. Image metrics were compared to those determined from a 3D PET scan with no motion present (3D STATIC). Values of FAV and NRC showed significant variation over the motion cycle when corrected by 3D CTAC images. 4D CTAC‐ and CINE CTAC–corrected PET images reduced these motion artifacts. The amount of artifact reduction is greater when the target is surrounded by lower density material and when motion was based on sin4(x). 4D CTAC reduced artifacts more than CINE CTAC for most scenarios. For a target surrounded by water equivalent material, there was no advantage to 4D CTAC over CINE CTAC when using the sin(x) motion pattern. Attenuation correction using both 4D CTAC or CINE CTAC can reduce motion artifacts in regions that include a tissue interface such as the lung/diaphragm border. 4D CTAC is more effective than CINE CTAC at reducing artifacts in some, but not all, scenarios. PACS numbers: 87.57.qp, 87.57.c

Fluoroscopic 3D Image Generation from Patient-Specific PCA Motion Models Derived from 4D-CBCT Patient Datasets: A Feasibility Study

A method for generating fluoroscopic (time-varying) volumetric images using patient-specific motion models derived from four-dimensional cone-beam CT (4D-CBCT) images was developed. 4D-CBCT images acquired immediately prior to treatment have the potential to accurately represent patient anatomy and respiration during treatment. Fluoroscopic 3D image estimation is performed in two steps: (1) deriving motion models and (2) optimization. To derive motion models, every phase in a 4D-CBCT set is registered to a reference phase chosen from the same set using deformable image registration (DIR). Principal components analysis (PCA) is used to reduce the dimensionality of the displacement vector fields (DVFs) resulting from DIR into a few vectors representing organ motion found in the DVFs. The PCA motion models are optimized iteratively by comparing a cone-beam CT (CBCT) projection to a simulated projection computed from both the motion model and a reference 4D-CBCT phase, resulting in a sequence of fluoroscopic 3D images. Patient datasets were used to evaluate the method by estimating the tumor location in the generated images compared to manually defined ground truth positions. Experimental results showed that the average tumor mean absolute error (MAE) along the superior–inferior (SI) direction and the 95th percentile in two patient datasets were 2.29 and 5.79 mm for patient 1, and 1.89 and 4.82 mm for patient 2. This study demonstrated the feasibility of deriving 4D-CBCT-based PCA motion models that have the potential to account for the 3D non-rigid patient motion and localize tumors and other patient anatomical structures on the day of treatment

The evaluation of a hybrid biomechanical deformable registration method on a multistage physical phantom with reproducible deformation

Abstract Background Advanced clinical applications, such as dose accumulation and adaptive radiation therapy, require deformable image registration (DIR) algorithms capable of voxel-wise accurate mapping of treatment dose or functional imaging. By utilizing a multistage deformable phantom, the authors investigated scenarios where biomechanical refinement method (BM-DIR) may be better than the pure image intensity based deformable registration (IM-DIR). Methods The authors developed a biomechanical-model based DIR refinement method (BM-DIR) to refine the deformable vector field (DVF) from any initial intensity-based DIR (IM-DIR). The BM-DIR method was quantitatively evaluated on a novel phantom capable of ten reproducible gradually-increasing deformation stages using the urethra tube as a surrogate. The internal DIR accuracy was inspected in term of the Dice similarity coefficient (DSC), Hausdorff and mean surface distance as defined in of the urethra structure inside the phantom and compared with that of the initial IM-DIR under various stages of deformation. Voxel-wise deformation vector discrepancy and Jacobian regularity were also inspected to evaluate the output DVFs. In addition to phantom, two pairs of Head&Neck patient MR images with expert-defined landmarks inside parotids were utilized to evaluate the BM-DIR accuracy with target registration error (TRE). Results The DSC and surface distance measures of the inner urethra tube indicated the BM-DIR method can improve the internal DVF accuracy on masked MR images for the phases of a large degree of deformation. The smoother Jacobian distribution from the BM-DIR suggests more physically-plausible internal deformation. For H&N cancer patients, the BM-DIR improved the TRE from 0.339 cm to 0.210 cm for the landmarks inside parotid on the masked MR images. Conclusions We have quantitatively demonstrated on a multi-stage physical phantom and limited patient data that the proposed BM-DIR can improve the accuracy inside solid organs with large deformation where distinctive image features are absent