Targeting prostate lesions on multiparametric MRI with HDR brachytherapy: Optimal planning margins determined using whole-mount digital histology.

PURPOSE: Multiparametric magnetic resonance imaging (mpMRI) has demonstrated the ability to localize intraprostatic lesions. It is our goal to determine how to optimally target the underlying histopathological cancer within the setting of high-dose-rate brachytherapy (HDR-BT). METHODS AND MATERIALS: Ten prostatectomy patients had pathologist-annotated mid-gland histology registered to pre-procedural mpMRI, which were interpreted by four different observers. Simulated HDR-BT plans with realistic catheter placements were generated by registering the mpMRI lesions and corresponding histology annotations to previously performed clinical HDR-BT implants. Inverse treatment planning was used to generate treatment plans that treated the entire gland to a single dose of 15 Gy, as well as focally targeted plans that aimed to escalate dose to the mpMRI lesions to 20.25 Gy. Three margins to the lesion were explored: 0 mm, 1 mm, and 2 mm. The analysis compared the dose that would have been delivered to the corresponding histologically-defined cancer with the different treatment planning techniques. RESULTS: mpMRI-targeted plans delivered a significantly higher dose to the histologically-defined cancer (p < 0.001), in comparison to the standard treatment plans. Additionally, adding a 1 mm margin resulted in significantly higher D98, and D90 to the histologically-defined cancer in comparison to the 0 mm margin targeted plans (p = 0.019 & p = 0.0026). There was no significant difference between plans using 1 mm and 2 mm margins. CONCLUSIONS: Adding a 1 mm margin to intraprostatic mpMRI lesions significantly increased the dose to histologically-defined cancer, in comparison applying no margin. No significant effect was observed by further expanding the margins.

Higher Anti-tumor Necrosis Factor-α Levels Correlate With Improved Radiologic Outcomes in Crohn's Perianal Fistulas.

BACKGROUND & AIMS: Higher anti-tumor necrosis factor-α (TNF) drug levels are associated with improved clinical healing of Crohn's perianal fistulas. It is unclear whether this leads to improved healing on radiologic assessment. We aimed to evaluate the association between anti-TNF drug levels and radiologic outcomes in perianal fistulising Crohn's disease. METHODS: A cross-sectional retrospective multicenter study was undertaken. Patients with perianal fistulising Crohn's disease on maintenance infliximab or adalimumab, with drug levels within 6 months of perianal magnetic resonance imaging were included. Patients receiving dose changes or fistula surgery between drug level and imaging were excluded. Radiologic disease activity was scored using the Van Assche Index, with an inflammatory subscore calculated using indices: T2-weighted imaging hyperintensity, collections >3 mm diameter, rectal wall involvement. Primary endpoint was radiologic healing (inflammatory subscore ≤6). Secondary endpoint was radiologic remission (inflammatory subscore = 0). RESULTS: Of 193 patients (infliximab, n = 117; adalimumab, n = 76), patients with radiologic healing had higher median drug levels compared with those with active disease (infliximab 6.0 vs 3.9 µg/mL; adalimumab 9.1 vs 6.2 µg/mL; both P < .05). Patients with radiologic remission also had higher median drug levels compared with those with active disease (infliximab 7.4 vs 3.9 µg/mL; P < .05; adalimumab 9.8 vs 6.2 µg/mL; P = .07). There was a significant incremental reduction in median inflammatory subscores with higher anti-TNF drug level tertiles. CONCLUSIONS: Higher anti-TNF drug levels were associated with improved radiologic outcomes on magnetic resonance imaging in perianal fistulising Crohn's disease, with an incremental improvement at higher drug level tertiles for both infliximab and adalimumab.

A multiobserver study investigating the effectiveness of prostatic multiparametric magnetic resonance imaging to dose escalate corresponding histologic lesions using high-dose-rate brachytherapy.

PURPOSE: Using multiparametric MRI data and the pathologic data from radical prostatectomy specimens, we simulated the treatment planning of dose-escalated high-dose-rate brachytherapy (HDR-BT) to the Multiparametric MRI dominant intraprostatic lesion (mpMRI-DIL) to compare the dose potentially delivered to the pathologically confirmed locations of the high-grade component of the cancer. METHODS AND MATERIALS: Pathologist-annotated prostatectomy midgland histology sections from 12 patients were registered to preprostatectomy mpMRI scans that were interpreted by four radiologists. To simulate realistic HDR-BT, we registered each observer's mpMRI-DILs and corresponding histology to two transrectal ultrasound images of other HDR-BT patients with a 15-Gy whole-gland prescription. We used clinical inverse planning to escalate the mpMRI-DILs to 20.25 Gy. We compared the dose that the histopathology would have received if treated with standard treatment plans to the dose mpMRI-targeting would have achieved. The histopathology was grouped as high-grade cancer (any Gleason Grade 4 or 5) and low-grade cancer (only Gleason Grade 3). RESULTS: 212 mpMRI-targeted HDR-BT plans were analyzed. For high-grade histology, the mpMRI-targeted plans achieved significantly higher median [IQR] D98 and D90 values of 18.2 [16.7-19.5] Gy and 19.4 [17.8-20.9] Gy, respectively, in comparison with the standard plans (p = 0.01 and p = 0.003). For low-grade histology, the targeted treatment plans would have resulted in a significantly higher median D90 of 17.0 [16.1-18.4] Gy in comparison with standard plans (p = 0.015); the median D98 was not significantly higher (p = 0.2). CONCLUSIONS: In this retrospective pilot study of 12 patients, mpMRI-based dose escalation led to increased dose to high-grade, but not low-grade, cancer. In our data set, different observers and mpMRI sequences had no substantial effect on dose to histologic cancer.

Vascular assessment in small bowel obstruction: can CT predict requirement for surgical intervention?

PURPOSE: Small bowel obstruction (SBO) is a common cause of emergency presentations for abdominal pain and can be complicated by mesenteric ischemia. Computed tomography is currently central to diagnosis and management planning. Currently accepted signs identify secondary effects of the root physiological insult, which is vascular obstruction. We hypothesized that with advancements in CT technology and reconstruction algorithms, we can now more closely interrogate the mesenteric vasculature for obstruction and more accurately predict the need for surgical intervention. METHODS: We retrospectively audited the charts of all patients presenting with a clinical diagnosis of SBO at a single institution in a 12-month period. Two blinded consultant radiologists were then asked to analyze 3D MIP reconstruction CT scans for vascular obstruction in addition to any currently accepted signs of ischemia. Comparison between vascular cutoff and accepted current signs in the need for surgical intervention and the presence of any signs of ischemia in theater were recorded. RESULTS: Vascular cutoff had a comparable, with a trend towards superiority, sensitivity and specificity and inter-observer agreement to currently accepted signs of ischemia. The absence of a cut off sign has an excellent negative predictive value for ischemia with only 2 (3.7%) patients demonstrating ischemia at surgery where the vascular cutoff sign was not seen to be present. CONCLUSION: Interrogating vascular obstruction using 3D MIP reconstructions in small bowel obstruction may be a more sensitive and specific sign for prediction of surgical intervention, possibly occurring earlier in the obstruction pathway.

A quality audit of MRI knee exams with the implementation of a novel 2-point DIXON sequence.

INTRODUCTION: The objective of this study was to evaluate the effect on diagnostic image quality and acquisition time utilising a DIXON sequence to replace two standard proton density (PD) fat saturation (FS) sequences in routine magnetic resonance (MR) evaluation of the knee. METHODS: Thirty-one consecutive patients referred for an MR examination of the knee were examined using the routine departmental protocol along with the addition of a DIXON sequence. The sequences were all evaluated by a senior radiologist and feedback provided via both written and scored responses. The sequences were then repackaged for two additional reviewers with the sagittal PD FS (Chemical Shift Selective Fat Saturation or CHESS) and sagittal PD removed and replaced with the DIXON (fat suppressed and in-phase, respectively) sequence equivalents. Scored and written responses were tabled and reviewed to assess the suitability of sequence replacement. RESULTS: The DIXON-based images were judged as being comparable replacements for the sagittal PD fat sat and PD sequences. There was no report of any loss in diagnostic confidence across the 31 patients (total of 32 knees) with a time saving of just over 10% gained. The most common issues raised affecting image quality, though not affecting diagnostic attributes, were patient motion and a minor chemical shift artefact. CONCLUSION: The use of the DIXON technique in place of the PD sequences was of equivalent diagnostic quality with'good' to 'outstanding' fat suppression observed for the majority of cases using the DIXON sequence with an incremental time saving obtained.

Prostate lesion delineation from multiparametric magnetic resonance imaging based on locality alignment discriminant analysis.

PURPOSE: Multiparametric MRI (mpMRI) has shown promise in the detection and localization of prostate cancer foci. Although techniques have been previously introduced to delineate lesions from mpMRI, these techniques were evaluated in datasets with T2 maps available. The generation of T2 map is not included in the clinical prostate mpMRI consensus guidelines; the acquisition of which requires repeated T2-weighted (T2W) scans and would significantly lengthen the scan time currently required for the clinically recommended acquisition protocol, which includes T2W, diffusion-weighted (DW), and dynamic contrast-enhanced (DCE) imaging. The goal of this study is to develop and evaluate an algorithm that provides pixel-accurate lesion delineation from images acquired based on the clinical protocol. METHODS: Twenty-five pixel-based features were extracted from the T2-weighted (T2W), apparent diffusion coefficient (ADC), and dynamic contrast-enhanced (DCE) images. The pixel-wise classification was performed on the reduced space generated by locality alignment discriminant analysis (LADA), a version of linear discriminant analysis (LDA) localized to patches in the feature space. Postprocessing procedures, including the removal of isolated points identified and filling of holes inside detected regions, were performed to improve delineation accuracy. The segmentation result was evaluated against the lesions manually delineated by four expert observers according to the Prostate Imaging-Reporting and Data System (PI-RADS) detection guideline. RESULTS: The LADA-based classifier (60 ± 11%) achieved a higher sensitivity than the LDA-based classifier (51 ± 10%), thereby demonstrating, for the first time, that higher classification performance was attained on the reduced space generated by LADA than by LDA. Further sensitivity improvement (75 ± 14%) was obtained after postprocessing, approaching the sensitivities attained by previous mpMRI lesion delineation studies in which nonclinical T2 maps were available. CONCLUSION: The proposed algorithm delineated lesions accurately and efficiently from images acquired following the clinical protocol. The development of this framework may potentially accelerate the clinical uses of mpMRI in prostate cancer diagnosis and treatment planning.

A self-tuned graph-based framework for localization and grading prostate cancer lesions: An initial evaluation based on multiparametric magnetic resonance imaging.

Multiparametric magnetic resonance imaging (mpMRI) has been established as the state-of-the-art examination for the detection and localization of prostate cancer lesions. Prostate Imaging-Reporting and Data System (PI-RADS) has been established as a scheme to standardize the reporting of mpMRI findings. Although lesion delineation and PI-RADS ratings could be performed manually, human delineation and ratings are subjective and time-consuming. In this article, we developed and validated a self-tuned graph-based model for PI-RADS rating prediction. 34 features were obtained at the pixel level from T2-weighted (T2W), apparent diffusion coefficient (ADC) and dynamic contrast enhanced (DCE) images, from which PI-RADS scores were predicted. Two major innovations were involved in this self-tuned graph-based model. First, graph-based approaches are sensitive to the choice of the edge weight. The proposed model tuned the edge weights automatically based on the structure of the data, thereby obviating empirical edge weight selection. Second, the feature weights were tuned automatically to give heavier weights to features important for PI-RADS rating estimation. The proposed framework was evaluated for its lesion localization performance in mpMRI datasets of 12 patients. In the evaluation, the PI-RADS score distribution map generated by the algorithm and from the observers' ratings were binarized by thresholds of 3 and 4. The sensitivity, specificity and accuracy obtained in these two threshold settings ranged from 65 to 77%, 86 to 93% and 85 to 88% respectively, which are comparable to results obtained in previous studies in which non-clinical T2 maps were available. The proposed algorithm took 10s to estimate the PI-RADS score distribution in an axial image. The efficiency achievable suggests that this technique can be developed into a prostate MR analysis system suitable for clinical use after a thorough validation involving more patients.

Magnetic resonance imaging of the prostate and targeted biopsy, Comparison of PIRADS and Gleason grading.

INTRODUCTION: Multiparametric magnetic resonance imaging (mpMRI) of the prostate has become integral in the investigation of suspected prostate cancer. Regions of interest are graded using the PIRADS scoring system, and in our institution, lesions graded as PIRADS 3-5 undergo sampling by MRI-guided biopsy. Limited data currently exists on PIRADS grading and biopsy results. METHODS: Retrospective review of 343 MRI-guided biopsies (MRGB) performed between April 2013 and December 2016 was conducted. This included patients irrespective of whether they were biopsy naïve, biopsy negative or known low-grade malignancy. A Gleason score (G) >= 3+4 was considered to reflect clinically significant disease (CSD). RESULTS: Of the 18 PIRADS 2 cases (at referrer request) who went to biopsy, 16 were negative and two had small volume Gleason 6 cancer. A total of 75 PIRADS 3 cases were biopsied with 88% negative or small volume Gleason 6 cancer, only 12% yielded ≥ G 3+4. Of the 133 PIRADS 4 lesions, 24% were negative, 25% were G6 and 51% were ≥ G 3+4. A total of 117 PIRADS 5 cases were biopsied with 7% negative, 13% Gleason 6 and 80% considered significant (≥ G 3+4). Of all biopsies, 230 (67%) had a positive result (≥ G6) with 171 of these (75%) being considered CSD, with overall CSD of 50% (171/343). CONCLUSIONS: This paper demonstrates the incidence of CSD for different PIRADS grades. The low incidence of CSD in PIRADS 3 lesions suggests that in low clinical risk men, follow up in priority to biopsy may be an alternative treatment pathway.

Accuracy Validation of an Automated Method for Prostate Segmentation in Magnetic Resonance Imaging.

Three dimensional (3D) manual segmentation of the prostate on magnetic resonance imaging (MRI) is a laborious and time-consuming task that is subject to inter-observer variability. In this study, we developed a fully automatic segmentation algorithm for T2-weighted endorectal prostate MRI and evaluated its accuracy within different regions of interest using a set of complementary error metrics. Our dataset contained 42 T2-weighted endorectal MRI from prostate cancer patients. The prostate was manually segmented by one observer on all of the images and by two other observers on a subset of 10 images. The algorithm first coarsely localizes the prostate in the image using a template matching technique. Then, it defines the prostate surface using learned shape and appearance information from a set of training images. To evaluate the algorithm, we assessed the error metric values in the context of measured inter-observer variability and compared performance to that of our previously published semi-automatic approach. The automatic algorithm needed an average execution time of ∼60 s to segment the prostate in 3D. When compared to a single-observer reference standard, the automatic algorithm has an average mean absolute distance of 2.8 mm, Dice similarity coefficient of 82%, recall of 82%, precision of 84%, and volume difference of 0.5 cm3 in the mid-gland. Concordant with other studies, accuracy was highest in the mid-gland and lower in the apex and base. Loss of accuracy with respect to the semi-automatic algorithm was less than the measured inter-observer variability in manual segmentation for the same task.

Postediting prostate magnetic resonance imaging segmentation consistency and operator time using manual and computer-assisted segmentation: multiobserver study.

Prostate segmentation on T2w MRI is important for several diagnostic and therapeutic procedures for prostate cancer. Manual segmentation is time-consuming, labor-intensive, and subject to high interobserver variability. This study investigated the suitability of computer-assisted segmentation algorithms for clinical translation, based on measurements of interoperator variability and measurements of the editing time required to yield clinically acceptable segmentations. A multioperator pilot study was performed under three pre- and postediting conditions: manual, semiautomatic, and automatic segmentation. We recorded the required editing time for each segmentation and measured the editing magnitude based on five different spatial metrics. We recorded average editing times of 213, 328, and 393 s for manual, semiautomatic, and automatic segmentation respectively, while an average fully manual segmentation time of 564 s was recorded. The reduced measured postediting interoperator variability of semiautomatic and automatic segmentations compared to the manual approach indicates the potential of computer-assisted segmentation for generating a clinically acceptable segmentation faster with higher consistency. The lack of strong correlation between editing time and the values of typically used error metrics ([Formula: see text]) implies that the necessary postsegmentation editing time needs to be measured directly in order to evaluate an algorithm's suitability for clinical translation.

Toward Prostate Cancer Contouring Guidelines on Magnetic Resonance Imaging: Dominant Lesion Gross and Clinical Target Volume Coverage Via Accurate Histology Fusion.

PURPOSE: Defining prostate cancer (PCa) lesion clinical target volumes (CTVs) for multiparametric magnetic resonance imaging (mpMRI) could support focal boosting or treatment to improve outcomes or lower morbidity, necessitating appropriate CTV margins for mpMRI-defined gross tumor volumes (GTVs). This study aimed to identify CTV margins yielding 95% coverage of PCa tumors for prospective cases with high likelihood. METHODS AND MATERIALS: Twenty-five men with biopsy-confirmed clinical stage T1 or T2 PCa underwent pre-prostatectomy mpMRI, yielding T2-weighted, dynamic contrast-enhanced, and apparent diffusion coefficient images. Digitized whole-mount histology was contoured and registered to mpMRI scans (error ≤2 mm). Four observers contoured lesion GTVs on each mpMRI scan. CTVs were defined by isotropic and anisotropic expansion from these GTVs and from multiparametric (unioned) GTVs from 2 to 3 scans. Histologic coverage (proportions of tumor area on co-registered histology inside the CTV, measured for Gleason scores [GSs] ≥6 and ≥7) and prostate sparing (proportions of prostate volume outside the CTV) were measured. Nonparametric histologic-coverage prediction intervals defined minimal margins yielding 95% coverage for prospective cases with 78% to 92% likelihood. RESULTS: On analysis of 72 true-positive tumor detections, 95% coverage margins were 9 to 11 mm (GS ≥ 6) and 8 to 10 mm (GS ≥ 7) for single-sequence GTVs and were 8 mm (GS ≥ 6) and 6 mm (GS ≥ 7) for 3-sequence GTVs, yielding CTVs that spared 47% to 81% of prostate tissue for the majority of tumors. Inclusion of T2-weighted contours increased sparing for multiparametric CTVs with 95% coverage margins for GS ≥6, and inclusion of dynamic contrast-enhanced contours increased sparing for GS ≥7. Anisotropic 95% coverage margins increased the sparing proportions to 71% to 86%. CONCLUSIONS: Multiparametric magnetic resonance imaging-defined GTVs expanded by appropriate margins may support focal boosting or treatment of PCa; however, these margins, accounting for interobserver and intertumoral variability, may preclude highly conformal CTVs. Multiparametric GTVs and anisotropic margins may reduce the required margins and improve prostate sparing.

A new diagnostic approach to popliteal artery entrapment syndrome.

A new method of diagnosing and defining functional popliteal artery entrapment syndrome is described. By combining ultrasonography and magnetic resonance imaging techniques with dynamic plantarflexion of the ankle against resistance, functional entrapment can be demonstrated and the location of the arterial occlusion identified. This combination of imaging modalities will also define muscular anatomy for guiding intervention such as surgery or Botox injection.

Spatially varying accuracy and reproducibility of prostate segmentation in magnetic resonance images using manual and semiautomated methods.

PURPOSE: Three-dimensional (3D) prostate image segmentation is useful for cancer diagnosis and therapy guidance, but can be time-consuming to perform manually and involves varying levels of difficulty and interoperator variability within the prostatic base, midgland (MG), and apex. In this study, the authors measured accuracy and interobserver variability in the segmentation of the prostate on T2-weighted endorectal magnetic resonance (MR) imaging within the whole gland (WG), and separately within the apex, midgland, and base regions. METHODS: The authors collected MR images from 42 prostate cancer patients. Prostate border delineation was performed manually by one observer on all images and by two other observers on a subset of ten images. The authors used complementary boundary-, region-, and volume-based metrics [mean absolute distance (MAD), Dice similarity coefficient (DSC), recall rate, precision rate, and volume difference (ΔV)] to elucidate the different types of segmentation errors that they observed. Evaluation for expert manual and semiautomatic segmentation approaches was carried out. Compared to manual segmentation, the authors' semiautomatic approach reduces the necessary user interaction by only requiring an indication of the anteroposterior orientation of the prostate and the selection of prostate center points on the apex, base, and midgland slices. Based on these inputs, the algorithm identifies candidate prostate boundary points using learned boundary appearance characteristics and performs regularization based on learned prostate shape information. RESULTS: The semiautomated algorithm required an average of 30 s of user interaction time (measured for nine operators) for each 3D prostate segmentation. The authors compared the segmentations from this method to manual segmentations in a single-operator (mean whole gland MAD = 2.0 mm, DSC = 82%, recall = 77%, precision = 88%, and ΔV = - 4.6 cm(3)) and multioperator study (mean whole gland MAD = 2.2 mm, DSC = 77%, recall = 72%, precision = 86%, and ΔV = - 4.0 cm(3)). These results compared favorably with observed differences between manual segmentations and a simultaneous truth and performance level estimation reference for this data set (whole gland differences as high as MAD = 3.1 mm, DSC = 78%, recall = 66%, precision = 77%, and ΔV = 15.5 cm(3)). The authors found that overall, midgland segmentation was more accurate and repeatable than the segmentation of the apex and base, with the base posing the greatest challenge. CONCLUSIONS: The main conclusions of this study were that (1) the semiautomated approach reduced interobserver segmentation variability; (2) the segmentation accuracy of the semiautomated approach, as well as the accuracies of recently published methods from other groups, were within the range of observed expert variability in manual prostate segmentation; and (3) further efforts in the development of computer-assisted segmentation would be most productive if focused on improvement of segmentation accuracy and reduction of variability within the prostatic apex and base.

Tight orbit syndrome: a previously unrecognized cause of open-angle glaucoma.

PURPOSE: To describe a new syndrome of tight orbit and intractable glaucoma with a poor visual prognosis. METHODS: A retrospective observational case series of six patients seen at two centres between 2001 and 2007 assessing intraocular pressure (IOP), best-corrected visual acuity and visual field. RESULTS: Three men and three women, ranging in age at diagnosis from 14 to 53 years, demonstrated similar orbital features and progressive visual field loss despite intensive management with medication and laser and operative surgery. Highest IOPs ranged from 30 to 50 mmHg. Trabeculectomy and/or glaucoma drainage devices were attempted in five patients but all failed. One patient underwent orbital decompression with achievement of IOP control. Final IOP at last follow-up was variable; only two patients achieved IOP in the normal range, with the rest ranging from 25 to 40 mmHg. All patients had advanced visual field loss. CONCLUSION: Tight orbit syndrome presents a serious clinical challenge. Despite maximum medical therapy and surgical intervention IOP is difficult to control, resulting in progressive visual field loss.