Volumetric accuracy of different imaging modalities in acute intracerebral hemorrhage

Background Follow-up imaging in intracerebral hemorrhage is not standardized and radiologists rely on different imaging modalities to determine hematoma growth. This study assesses the volumetric accuracy of different imaging modalities (MRI, CT angiography, postcontrast CT) to measure hematoma size. Methods 28 patients with acute spontaneous intracerebral hemorrhage referred to a tertiary stroke center were retrospectively included between 2018 and 2019. Inclusion criteria were (1) spontaneous intracerebral hemorrhage (supra- or infratentorial), (2) noncontrast CT imaging performed on admission, (3) follow-up imaging (CT angiography, postcontrast CT, MRI), and (4) absence of hematoma expansion confirmed by a third cranial image within 6 days. Two independent raters manually measured hematoma volume by drawing a region of interest on axial slices of admission noncontrast CT scans as well as on follow-up imaging (CT angiography, postcontrast CT, MRI) using a semi-automated segmentation tool (Visage image viewer; version 7.1.10). Results were compared using Bland–Altman plots. Results Mean admission hematoma volume was 18.79 ± 19.86 cc. All interrater and intrarater intraclass correlation coefficients were excellent (1; IQR 0.98–1.00). In comparison to hematoma volume on admission noncontrast CT volumetric measurements were most accurate in patients who received postcontrast CT (bias of − 2.47%, SD 4.67: n = 10), while CT angiography often underestimated hemorrhage volumes (bias of 31.91%, SD 45.54; n = 20). In MRI sequences intracerebral hemorrhage volumes were overestimated in T2* (bias of − 64.37%, SD 21.65; n = 10). FLAIR (bias of 6.05%, SD 35.45; n = 13) and DWI (bias of-14.6%, SD 31.93; n = 12) over- and underestimated hemorrhagic volumes. Conclusions Volumetric measurements were most accurate in postcontrast CT while CT angiography and MRI sequences often substantially over- or underestimated hemorrhage volumes.

Imaging of Fibrosis in Chronic Pancreatitis

Chronic pancreatitis (CP) describes long-standing inflammation of the pancreas, which leads to irreversible and progressive inflammation of the pancreas with fibrosis. CP also leads to abdominal pain, malnutrition, and permanent impairment of exocrine/endocrine functions. However, it is difficult to assess CP pathologically, and imaging modalities therefore play an important role in the diagnosis and assessment of CP. There are four modalities typically used to assess CP. Pancreatic duct features are assessed with magnetic resonance cholangiopancreatography (MRCP) and endoscopic retrograde cholangiopancreatography (ERCP). However, ERCP is a rather invasive diagnostic modality for CP, and can result in adverse events such as post-ERCP pancreatitis. Computed tomography (CT) is often the most appropriate initial imaging modality for patients with suspected CP, and has high diagnostic specificity. However, CT findings typically only appear in advanced stages of CP, and it is difficult to detect early CP. Endoscopic ultrasonography (EUS) provides superior spatial resolution compared with other imaging modalities such as CT and magnetic resonance imaging (MRI), and is considered the most reliable and efficient diagnostic modality for pancreatic diseases. The EUS-based Rosemont classification plays an important role in diagnosing CP in clinical practice. Evaluation of tissue stiffness can be another option to assess the diagnosis and progression of CP, and MRI and EUS can be used to assess CP not only with imaging, but also with elasticity measurement. MR and EUS elastography are expected to provide new alternative diagnostic tools for assessment of fibrosis in CP, which is difficult to evaluate pathologically.

Intra-osseous migration in calcific rotator cuff tendinopathy- A novel depiction of temporal evolution on multi-modality imaging

We present a case of calcific tendinopathy of the rotator cuff with intraosseous migration of the calcification, treated with ultrasound-guided bursal steroid injection and followed up with multiple imaging modalities for a year following the initial presentation. The radiographs, ultrasound, CT, nuclear scintigraphy, and MRI images demonstrate the temporal evolution of the intraosseous migrated calcium and show how this pathology, in its acute phase, can mimic other pathologies like osteoid osteoma. The follow-up imaging also illustrated how the migrated intraosseous focus of calcification took a much longer time to heal compared to its intratendinous counterpart, possibly leading to the protracted course of recovery. This report also highlights a previously undescribed pattern of healing of the intraosseous migrated calcium on multiple imaging modalities.

Combined Structural MR and Diffusion Tensor Imaging Classify the Presence of Alzheimer’s Disease With the Same Performance as MR Combined With Amyloid Positron Emission Tomography: A Data Integration Approach

Background: In recent years, classification frameworks using imaging data have shown that multimodal classification methods perform favorably over the use of a single imaging modality for the diagnosis of Alzheimer’s Disease. The currently used clinical approach often emphasizes the use of qualitative MRI and/or PET data for clinical diagnosis. Based on the hypothesis that classification of isolated imaging modalities is not predictive of their respective value in combined approaches, we investigate whether the combination of T1 Weighted MRI and diffusion tensor imaging (DTI) can yield an equivalent performance as the combination of quantitative structural MRI (sMRI) with amyloid-PET.Methods: We parcellated the brain into regions of interest (ROI) following different anatomical labeling atlases. For each region of interest different metrics were extracted from the different imaging modalities (sMRI, PiB-PET, and DTI) to be used as features. Thereafter, the feature sets were reduced using an embedded-based feature selection method. The final reduced sets were then used as input in support vector machine (SVM) classifiers. Three different base classifiers were created, one for each imaging modality, and validated using internal (n = 41) and external data from the ADNI initiative (n = 330 for sMRI, n = 148 for DTI and n = 55 for PiB-PET) sources. Finally, the classifiers were ensembled using a weighted method in order to evaluate the performance of different combinations.Results: For the base classifiers the following performance levels were found: sMRI-based classifier (accuracy, 92%; specificity, 97% and sensitivity, 87%), PiB-PET (accuracy, 91%; specificity, 89%; and sensitivity, 92%) and the lowest performance was attained with DTI (accuracy, 80%; specificity, 76%; and sensitivity, 82%). From the multimodal approaches, when integrating two modalities, the following results were observed: sMRI+PiB-PET (accuracy, 98%; specificity, 98%; and sensitivity, 99%), sMRI+DTI (accuracy, 97%; specificity, 99%; and sensitivity, 94%) and PiB-PET+DTI (accuracy, 91%; specificity, 90%; and sensitivity, 93%). Finally, the combination of all imaging modalities yielded an accuracy of 98%, specificity of 97% and sensitivity of 99%.Conclusion: Although DTI in isolation shows relatively poor performance, when combined with structural MR, it showed a surprising classification performance which was comparable to MR combined with amyloid PET. These results are consistent with the notion that white matter changes are also important in Alzheimer’s Disease.

Different radiographic imaging modalities with a proton computed tomography demonstrator

Proton computed tomography aims at improving proton-beam therapy, which is an established method to treat deep-seated tumours in cancer therapy. In treatment planning, the stopping power (SP) within a patient, describing the energy loss of a proton in a tissue, has to be known with high accuracy. However, conventional computed tomography (CT) returns Hounsfield units (HU), which have to be converted to SP values to perform the required treatment planning, thus introducing range uncertainties in the calculated dose distribution. Using protons not only for therapy but also for the preceding planning CT enables the direct measurement of the SP. Hence, this imaging modality eliminates the need for further conversion and therefore offers the possibility to improve treatment planning in proton therapy. In order to examine the principles of such a proton CT (pCT) setup, a demonstrator system, consisting of four double-sided silicon strip detectors and a range telescope, was built. The performance of the pCT demonstrator was tested with measurements at the MedAustron facility in Wiener Neustadt, Austria. In this paper, 2D imaging modalities going beyond the idea of a standard proton radiography, will be discussed. Namely, fluence loss imaging and scattering radiography results obtained with the demonstrator will be shown. The advantage of these modalities is that they do not rely on an additional energy measurement and can therefore be conducted only with the tracker of the demonstrator.

Towards an Effective Imaging-Based Decision Support System for Skin Cancer

The usage of expert systems to aid in medical decisions has been employed since 1980s in distinct applications. With the high demands of medical care and limited human resources, these technologies are required more than ever. Skin cancer has been one of the pathologies with higher growth, which suffers from lack of dermatology experts in most of the affected geographical areas. A permanent record of examination that can be further analyzed are medical imaging modalities. Most of these modalities were also assessed along with machine learning classification methods. It is the aim of this research to provide background information about skin cancer types, medical imaging modalities, data mining and machine learning methods, and their application on skin cancer imaging, as well as the disclosure of a proposal of a multi-imaging modality decision support system for skin cancer diagnosis and treatment assessment based in the most recent available technology. This is expected to be a reference for further implementation of imaging-based clinical support systems.

Pencitraan Kedokteran Nuklir Pada Pasien Metastasis Tulang dengan Kanker Payudara

Bone is the most common site to which breast cancer metastasizes and sometimes is the first affected site in a substantial proportion of women with advanced breast cancer. A lot of study has highlighted that imaging modalities visualize different aspects of osseous tissues (cortex or marrow). Imaging bone metastases is problematic because the lesions can be osteolytic, osteoblastic, or mixed, and imaging modalities are based on either direct anatomic visualization of the bone or tumor or indirect measurements of bone or tumor metabolism. Bone imaging by skeletal scintigraphy can be an essential part, and positron emission tomography or single-photon emission computed tomography have a potential of evaluating bone metastases, but no consensus exists as to the best modality for diagnosing the lesion and for assessing its response to treatment. In this review, we discuss the use of each nuclear imaging for bone modality for diagnosing bone metastases from breast cancer

Functionalized Nanomaterials as Tailored Theranostic Agents in Brain Imaging

Functionalized nanomaterials of various categories are essential for developing cancer nano-theranostics for brain diseases; however, some limitations exist in their effectiveness and clinical translation, such as toxicity, limited tumor penetration, and inability to cross blood–brain and blood-tumor barriers. Metal nanomaterials with functional fluorescent tags possess unique properties in improving their functional properties, including surface plasmon resonance (SPR), superparamagnetism, and photo/bioluminescence, which facilitates imaging applications in addition to their deliveries. Moreover, these multifunctional nanomaterials could be synthesized through various chemical modifications on their physical surfaces via attaching targeting peptides, fluorophores, and quantum dots (QD), which could improve the application of these nanomaterials by facilitating theranostic modalities. In addition to their inherent CT (Computed Tomography), MRI (Magnetic Resonance Imaging), PAI (Photo-acoustic imaging), and X-ray contrast imaging, various multifunctional nanoparticles with imaging probes serve as brain-targeted imaging candidates in several imaging modalities. The primary criteria of these functional nanomaterials for translational application to the brain must be zero toxicity. Moreover, the beneficial aspects of nano-theranostics of nanoparticles are their multifunctional systems proportioned towards personalized disease management via comprising diagnostic and therapeutic abilities in a single biodegradable nanomaterial. This review highlights the emerging aspects of engineered nanomaterials to reach and deliver therapeutics to the brain and how to improve this by adopting the imaging modalities for theranostic applications.