Publications by authors named "J T Dowling"

1,067 Publications

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Automatic radiotherapy delineation quality assurance on prostate MRI with deep learning in a multicentre clinical trial.

Phys Med Biol 2021 Sep 10. Epub 2021 Sep 10.

Institute of Medical Physics, University of Sydney School of Physics, Sydney, New South Wales, AUSTRALIA.

Volume delineation quality assurance (QA) is particularly important in clinical trial settings where consistent protocol implementation is required, as outcomes will affect future as well current patients. Currently, where feasible, this is conducted manually, which is time consuming and resource intensive. Although previous studies mostly focused on automating delineation QA on CT, magnetic resonance imaging (MRI) is being increasingly used in radiotherapy treatment. In this work, we propose to perform automatic delineation QA on prostate MRI for both the clinical target volume (CTV) and organs-at-risk (OARs) by using delineations generated by 3D Unet variants as benchmarks for QA. These networks were trained on a small gold standard atlas set and applied on a multicentre radiotherapy clinical trial dataset to generate benchmark delineations. Then, a QA stage was designed to recommend 'pass', 'minor correction' and 'major correction' for each manual delineation in the trial set by thresholding its Dice similarity coefficient to the network-generated delineation. Among all 3D Unet variants explored, the Unet with anatomical gates in an AtlasNet architecture performed the best in delineation QA, achieving an area under the receiver operating characteristics curve of 0.97, 0.92, 0.89 and 0.97 for identifying unacceptable (major correction) delineations with a sensitivity of 0.93, 0.73, 0.74 and 0.90 at a specificity of 0.93, 0.86, 0.86 and 0.95 for bladder, prostate CTV, rectum and gel spacer respectively. To the best of our knowledge, this is the first study to propose automated delineation QA for a multicentre radiotherapy clinical trial with treatment planning MRI. The methods proposed in this work can potentially improve the accuracy and consistency of CTV and OAR delineation in radiotherapy treatment planning.
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http://dx.doi.org/10.1088/1361-6560/ac25d5DOI Listing
September 2021

Endonasal Free Flap Reconstruction Combined With Draf Frontal Sinusotomy for Complex Cerebrospinal Fluid Leak: A Technical Report & Case Series.

Oper Neurosurg (Hagerstown) 2021 Aug 23. Epub 2021 Aug 23.

Department of Otolaryngology-Head and Neck Surgery, Washington University in St. Louis, Saint Louis, Missouri, USA.

Background: Frontal sinus cranialization with closure via bifrontal pericranial flaps is the gold standard for separating the nasofrontal recess from the intracranial cavity for posterior table defects. Despite the high success rate, cerebrospinal fluid (CSF) leak may persist and is particularly challenging when vascularized reconstructive options from the bicoronal incision are exhausted.

Objective: To assess a novel endonasal technique using an adipofascial radial forearm free flap delivered to the frontal recess through a Draf sinusotomy to repair complex CSF leaks from the frontal sinus.

Methods: A retrospective review of 3 patients (all male; ages 42, 43, and 69 yr) with persistent CSF leak despite frontal sinus cranialization and repair with bifrontal pericranium was performed. Etiology of injury was traumatic in 2 patients and iatrogenic in 1 patient after anaplastic meningioma treatment. To create space for the flap and repair the nasofrontal ducts, endoscopic Draf III (Case 1, 3) or Draf IIb left frontal sinusotomy (Case 2) was performed. The forearm flap was harvested, passed through a Caldwell-Luc exposure, and placed within the Draf frontal sinustomy. The flap vessels were tunneled to the left neck and anastomosed to the facial vessels by the mandibular notch.

Results: Intraoperatively, the flaps were well-seated and provided a watertight seal. Postoperative hospital courses were uncomplicated. There were no new CSF leaks or flap necrosis at 12, 14, and 16 mo.

Conclusion: Endoscopic endonasal free flap reconstruction through a Draf procedure is a novel viable option for persistent CSF leak after failed frontal sinus cranialization.
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http://dx.doi.org/10.1093/ons/opab309DOI Listing
August 2021

Pharmaceutical-loaded contact lenses as an ocular drug delivery system: A review of critical lens characterization methodologies with reference to ISO standards.

Cont Lens Anterior Eye 2021 Aug 2:101487. Epub 2021 Aug 2.

Ocular Therapeutics Research Group (OTRG), Pharmaceutical & Molecular Biotechnology Research Centre (PMBRC), Waterford Institute of Technology, Waterford City, County Waterford X91 K0EK, Ireland.

Therapeutic contact lenses for ocular drug delivery have received considerable interest as they can potentially enhance ocular bioavailability, increase patient compliance, and reduce side effects. Along with the successful in vitro and in vivo studies on sustained drug delivery through contact lenses, lens critical properties such as water content, optical transparency and modulus have also been investigated. Aside from issues such as drug stability or burst release, the potential for the commercialization of pharmaceutical-loaded lenses can be limited by the alteration of lens physical and chemical properties upon the incorporation of therapeutic or non-therapeutic components. This review outlines advances in the use of pharmaceutical-loaded contact lenses and their relevant characterization methodologies as a potential ocular drug delivery system from 2010 to 2020, while summarizing current gaps and challenges in this field. A key reference point for this review is the relevant ISO standards on contact lenses, relating to the associated characterization methodologies. The content of this review is categorized based on the chemical, physical and mechanical properties of the loaded lens with the shortcomings of such analytical technologies examined.
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http://dx.doi.org/10.1016/j.clae.2021.101487DOI Listing
August 2021

Salvage therapies for radiation-relapsed isocitrate dehydrogenase-mutant astrocytoma and 1p/19q codeleted oligodendroglioma.

Neurooncol Adv 2021 Jan-Dec;3(1):vdab081. Epub 2021 Jun 18.

Department of Radiation Oncology, Washington University School of Medicine, St. Louis, Missouri, USA.

Background: Optimal management for recurrent IDH-mutant glioma after radiation therapy (RT) is not well-defined. This study assesses practice patterns for managing recurrent IDH-mutant astrocytoma (Astro) and 1p/19q codeleted oligodendroglioma (Oligo) after RT and surveys their clinical outcomes after different salvage approaches.

Methods: Ninety-four recurrent Astro or Oligo patients after RT who received salvage systemic therapy (SST) between 2001 and 2019 at a tertiary cancer center were retrospectively analyzed. SST was defined as either alkylating chemotherapy (AC) or nonalkylating therapy (non-AC). Overall survival (OS) and progression-free survival (PFS) were calculated using the Kaplan-Meier method from the start of SST. Multivariable analysis (MVA) was conducted using Cox regression analysis.

Results: Recurrent Oligo (n = 35) had significantly higher PFS (median: 3.1 vs 0.8 years, respectively, = .002) and OS (median: 6.3 vs 1.5 years, respectively, < .001) than Astro (n = 59). Overall, 90% of recurrences were local. Eight-three percent received AC as the first-line SST; 50% received salvage surgery before SST; approximately 50% with local failure >2 years after prior RT received reirradiation. On MVA, non-AC was associated with worse OS for both Oligo and Astro; salvage surgery was associated with improved PFS and OS for Astro; early reirradiation was associated with improved PFS for Astro.

Conclusions: Recurrent radiation-relapsed IDH-mutant gliomas represent a heterogeneous group with variable treatment approaches. Surgery, AC, and reirradiation remain the mainstay of salvage options for retreatment.
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http://dx.doi.org/10.1093/noajnl/vdab081DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8324173PMC
June 2021

Deep learning for segmentation in radiation therapy planning: a review.

J Med Imaging Radiat Oncol 2021 Aug 26;65(5):578-595. Epub 2021 Jul 26.

Ingham Institute for Applied Medical Research and South Western Sydney Clinical School, UNSW, Liverpool, New South Wales, Australia.

Segmentation of organs and structures, as either targets or organs-at-risk, has a significant influence on the success of radiation therapy. Manual segmentation is a tedious and time-consuming task for clinicians, and inter-observer variability can affect the outcomes of radiation therapy. The recent hype over deep neural networks has added many powerful auto-segmentation methods as variations of convolutional neural networks (CNN). This paper presents a descriptive review of the literature on deep learning techniques for segmentation in radiation therapy planning. The most common CNN architecture across the four clinical sub sites considered was U-net, with the majority of deep learning segmentation articles focussed on head and neck normal tissue structures. The most common data sets were CT images from an inhouse source, along with some public data sets. N-fold cross-validation was commonly employed; however, not all work separated training, test and validation data sets. This area of research is expanding rapidly. To facilitate comparisons of proposed methods and benchmarking, consistent use of appropriate metrics and independent validation should be carefully considered.
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http://dx.doi.org/10.1111/1754-9485.13286DOI Listing
August 2021
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